Pretectum’s Composable Customer Master Data Management (CMDM) platform is a strategic solution that helps organizations centralize and manage customer data to deliver personalized experiences, ensure data accuracy and compliance, and drive revenue growth
The platform provides a centralized repository that integrates customer information from various sources
This enables businesses to have a holistic view of each customer, facilitating better organizational decision-making, customer interaction, and more personalized experiences
Key features of Pretectum CMDM include data modeling, enrichment, maintenance, quality management, golden record management and data stewardship
It serves diverse stakeholders including sales, marketing, service and partners
The composable architecture allows configuring the solution to specific business needs
It follows five core principles: collection, consolidation, cleaning, control, and compliance
Pretectum recommends a centralized implementation approach for maximum control, while also supporting registry, consolidated and co-existent deployment models
The architecture enables both vertical and horizontal scalability to accommodate growing data volumes and business expansion
The platform provides tools for defining data governance policies, quality rules, and ownership responsibilities
It enables active data governance with clear ownership and accountability for customer data across the organization
Pretectum CMDM is a strategic solution that helps organizations centralize and manage customer data to deliver personalized experiences, ensure data quality and compliance, and drive revenue growth through a flexible, scalable and composable platform.
Visit https://www.pretectum.com/datasheets/ to learn more
In the modern business landscape, the importance of efficient customer data management within Business Intelligence Competency Centers (BICCs) is crucial for making strategic decisions. BICCs serve as pivotal entities that facilitate the deployment of BI solutions with sustainability and strategic precision. They operate as driving forces, establishing policies, governance structures, and methodologies to enable timely decision-making and transform insights into tangible assets for a competitive advantage.
BICCs are cross-functional teams focusing on promoting best practices in BI, data management, and analytics. They develop strategic plans, prioritize BI initiatives, ensure data quality and governance, and promote BI usage. Organizations with BICCs report increased BI usage, user satisfaction, decision-making speed, and cost efficiency.
The integration of data warehouses and technologies like Pretectum CMDM streamlines information management, emphasizing the need for a centralized approach to deliver BI efficiently. BICCs, comprising technical and business experts, represent a shift towards a holistic approach where BI experts collaborate with the business to align knowledge strategies with broader objectives, leading to higher ROI for BI projects.
Pretectum CMDM plays a pivotal role in ensuring accurate and complete Customer Master Data within BICCs, enhancing the accessibility, quality, and relevance of customer data for strategic decision-making. Its advanced capabilities create a unified view of customer information, enabling organizations to enhance customer experiences, drive targeted marketing, and improve BICC output.
The integration of Pretectum CMDM in BICCs enables organizations to derive deeper insights into customer characteristics, behavior, preferences, and trends, facilitating tailored products and services, strategic adjustments, personalized interactions, and stronger customer relationships. Centralized control and standardization of customer data enhance data quality, integrity, and consistency, leading to more reliable BI outcomes and providing a solid foundation for strategic initiatives.
Overall, integrating a Customer Master Data Management system like Pretectum CMDM within BICCs enhances customer data management, amplifies BI impact, unlocks capabilities and insights from customer data, drives innovation, and helps organizations stay competitive in a dynamic business environment.
Information is a currency in modern business and strategic decisions that are tied to it, can make or break the enterprise.
The relative significance of efficient customer data management cannot be overstated. There has been a sustained surge in demand for business intelligence (BI) tools for years now, and this is a testament to the competitive business landscape, where the ability to access timely and relevant information is essential for good decision-making.
At the center of some, is the Business Intelligence Competency Center (BICC). For some businesses, the BICC is a pivotal entity that ensures organizations can deploy BI solutions with sustainability, efficiency, and strategic precision.
Often a BICC operates as a driving force, establishing policies, governance structures, methodologies, and support models that foster just-in-time decision-making. The mandate of the BICC extends beyond mere functionality, encompassing the transformation of insights into tangible assets, thereby providing a competitive advantage and fueling business growth. Thatās the theory at least.
We think of the BICC as a cross-functional team within an organization that focuses on promoting and implementing best practices in business intelligence, data management, and analytics. The BICC develops the overall strategic plan and priorities for Business Intelligence (BI) and defines the requirements including data quality and governance, and fulfils the role of promoting the use of BI. Organizations with a BICC claim to have seen increased usage of Business Intelligence, increased business user satisfaction, better understanding of the value of BI, increased decision-making speed, and decreased staff and software costs.
Often there is a significant role played by data warehouses in managing business information. Organizations increasingly recognize that technology as an enabler means more effective information management. Recognition of this underscores the need for a centralized approach to information management that integrates policies, technologies, programs, and people to deliver BI efficiently.
BICCs are a growing trend in industry and are made up of both technical and business experts, they signal a departure from the conventional integration of BI with IT. Instead, a more holistic approach is adopted, where BI experts equipped with technical, analytical, and business skills collaborate with the business to align knowledge strategies with broader business objectives. In some organizations, the head of the BICC is often even part of C-level management resulting in an expectation of higher returns on investment for BI projects.
BICCs can be multifaceted and contribute significantly to the effective integration of BI into organizational processes. From conducting assessments for strategic services to actually implementing BI software, administering systems, providing training, mentoring users, and overseeing development activities, the BICC ensures that every facet of BI is optimized. This optimization, in turn, leads to a better understanding of the value of BI, increased user satisfaction, faster and more accurate decision-making, adaptability to changes, and enhanced collaboration between IT and business entities.
One of the key dependencies for many BICCs is accurate and complete Customer Master Data and systems like the Pretectum CMDM can be of assistance here. A CMDM system will often play a pivotal role in streamlining the process of referencing and analyzing customer data across the organization. The integration of CMDM within any BICC framework ensures that customer data is accessible, timely, of good quality and relevance and s highly suitable to be leveraged for strategic decision-making. Pretectum CMDM, with its advanced capabilities, facilitates the creation of a unified and accurate view of customer information, enabling organizations to not only enhance customer experiences and drive targeted marketing initiatives but also elevate the quality of the output of the BICC.
Integration of the Pretectum CMDM into the BICC ecosystem supports a new dimension of data insights and reporting by unifying the customer data in such a way that organizations can derive deeper insights into customer characteristics, behaviour, preferences, and trends. Such a comprehensive understanding enables businesses to tailor products and services, adjust tactically and strategically and also personalize customer interactions, and ultimately build longer-lasting customer relationships.
The centralized control and standardization of customer data provide greater assurances about customer master data quality, integrity, and consistency across the organization. This, in turn, leads to more reliable and accurate BI outcomes, providing decision-makers with a solid foundation for their strategic initiatives.
Integration of a Customer Master Data Management system like Pretectum CMDM within the broader framework of a Business Intelligence Competency Center elevates the capabilities of those organizations looking to customer data to advance BICC capabilities. Such an approach not only ensures more precise and efficient management of customer data but also amplifies the impact of BI initiatives. Modern organizations must navigate what is now a very dynamic business environment, the fusing of the BICC and CMDM systems holds great potential for unlocking the great capabilities and insights from customer data, driving innovation, and staying ahead of competitors.
Federated customer data governance is an approach to customer data management that allows organizations to implement data governance policies and controls in a decentralized manner across multiple domains or business units. This is an intrinsic characteristic of the Pretectum CMDM approach to Customer Master Data Management (CMDM)
Key aspects of federated data governance are the establishment of governance authorities within each data domain or business unit to define the rules, policies, and standards specific to that business or data domain. These domain-specific governance authorities work collaboratively to ensure alignment with overall organizational goals and data governance requirements. Where appropriate, enterprise or federated business data rules and structures are established and leveraged to influence and control the data creation and management processes.
Federated customer data governance supports the balance between decentralized data ownership/management and centralized data governance, allowing the business domains to work autonomously within their own defined interoperability standards, connecting to their business unit-specific data sources and sharing data internally.
This approach is essential for implementing a successful data mesh architecture, where data is treated as a product and managed in a decentralized manner. The key benefit of federated data governance for customer master data management is that it allows organizations to scale data governance practices across a complex, distributed data landscape while maintaining agility and business and data domain-specific requirements.
Federated data governance facilitates the centralization of data governance, data quality, and data lifecycle management across an organization.
There are several key steps for implementing a successful customer master data management program that need to be considered:
An organization should begin with an āas-isā state analysis and stakeholder engagement. Understand the vision and key drivers, assess the current state, and document all the āpain pointsā and goals of the different data stakeholders.
Selecting tools that are contextually appropriate for the organization is an important decision point. Any tooling that is considered should offer a ready-to-run platform for business leaders to easily carry out their customer master data governance, allowing easy access and updating of master data, and the support of seamless integration with any, and all, third-party and internal systems as required.
Approaches to Customer MDM
The adoption of new or different tooling has to be with one goal in mind, namely the establishment of better data governance by integrating business operations, data collection, and data optimization requirements. This goes a long way toward ensuring the business runs smoothly and effectively, all the while, complying with privacy, data handling, and regulatory policies; in accordance with local, regional, and international law.
It should also be recognized and acknowledged, that maintaining a customer-centric approach is a concept that, just like customer data itself, is constantly evolving. Any customer master data management solution should be composable, adaptable, and evolve with the compliance, integration, and business needs of the organization, seamlessly. Only through the best possible customer data can an organization hope to ultimately build and maintain strong customer relationships.
The user experiences within the tools and applications should also be supportive of employees and employee tasking while also helping in the handling and safe access and sharing of specific customer data to accelerate digital transformation, meet business needs, and ultimately support the organizationās pursuit of exceeding customer expectations.
Role-based-Access-Controls (RBAC) are an important control element in ensuring that only the right people have access to the right data and platform functionality. Extensive auditing and logging is an important aspect that needs to be in place here also.
Any platform under consideration should also continuously maintain the customer master data to ensure accurate and up-to-date information, avoid discrepancies in the customer master, and maintain the highest possible data quality.
By considering all of these aspects, organizations can better implement an effective customer master data management program that delivers trusted, high-quality data to drive operational efficiency, improve customer experience, and enable better business decisions.
āThick dataā refers to qualitative information that provides insights into the context, emotions, and human experiences associated with a particular phenomenon.
Thick Data is often contrasted with ābig data,ā which typically consists of large volumes of quantitative and structured data. While big data is valuable for statistical analysis and identifying patterns, thick data adds depth and richness by offering a more nuanced understanding of the social and cultural factors influencing a situation.
Thick data is usually collected through methods such as interviews, ethnographic studies, participant observations, and open-ended surveys. These approaches allow researchers to gather subjective and context-specific information that may be challenging to capture through quantitative means alone. The combination of big data and thick data is often seen as a holistic approach to gaining comprehensive insights into complex phenomena.
āThin dataā is a term that might be used to describe a small amount of information or data points that may lack depth or context. Unlike big data, which involves massive datasets with diverse and complex information, thin data typically refers to limited and less detailed datasets. This Thin Data may not provide a comprehensive understanding of a particular subject, and its analysis may be more straightforward compared to the intricate analysis required for big data.
In some cases, the distinction between thick data and thin data is made to highlight the depth of qualitative insights (thick data) versus the limited and often quantitative nature of some datasets (thin data). The Thin Data might be more readily available but may not capture the full complexity or richness of a situation. Itās essential to consider the quality, relevance, and depth of data when making decisions or drawing conclusions based on thin data.
Itās easy to say an organization should make customers their north star. Yet the reality is many organizations remain product and service-focused and are far from customer-centric. To tackle the challenge of customer-centricity and improve the overall customer experience, businesses need to execute a strategy that is business culture-aligned and technologically provides an advantage.
The concept of Thick Data gained prominence through a 2016 TEDx Cambridge talk and a compelling Ethnography Matters article by former Nokia researcher Tricia Wang. Thick Data is a derivative of qualitative methods, it offers insights into the emotional and motivational aspects of people, shedding light on their thought processes. This goes beyond mere facts and behaviors, providing crucial context and narrating the stories that ābreathe lifeā into the numbers and statistics associated with the customer.
Big Data emphasizes quantification and numerical analysis, Thick Data reminds us of the human side of business, capturing the nuances that might be overlooked in the proverbial sea of spreadsheets and graphs.
The Duality of Big Data and Thick Data
Big Data and Thick Data, though seemingly at odds, play complementary roles in driving optimal business decisions. Big Data analytics focuses on incremental improvements, optimizing existing systems based on data-generated insights. In contrast, Thick Data analytics ventures into the realm of change, challenging the status quo and uncovering transformative opportunities, albeit on a smaller scale.
The sweet spot lies in integrating both types of data, especially in understanding the customer experience. Big Data reveals what customers are doing and where improvements can be made, while Thick Data uncovers the reasons behind their behaviors and their desires for a different experience.
Customer Master Data Management: A Holistic Approach
With Customer Master Data Management (CMDM), the integration of Big Data and Thick Data can be pivotal. CMDM involves the meticulous process of gathering, curating, analyzing, and syndicating customer data.
The Thick
Thick Data in CMDM can originate from qualitative sources such as customer interviews, feedback sessions, and ethnographic studies, such methods delve into the emotional and motivational aspects of customers, with a deeper understanding of customer preferences, experiences, and expectations. Qualitative insights, for example, might reveal that a customerās loyalty is tied to personalized interactions rather than just transactional efficiency.
Thick Data in CMDM can be profoundly impactful as it adds a layer of context to the quantitative metrics gathered through CMDM processes, enabling organizations to tailor their strategies to align with the genuine needs and desires of their customers. When CMDM decisions are informed by Thick Data, they are rooted in statistical analysis and reflect a deep understanding of the humanness behind customer records.
Learn more at
https://www.pretectum.com/knowing-your-customers-through-the-think-and-the-thin/
At the intersection of optimal business operations and the discipline of appropriately aligned data governance principled master data management lies Customer Master Data. The practice includes dimensions that define the needs of the business including contact information, customer vitalstatics and pretty much any data attribute that the business needs to leverage for a perfectly harmonized customer relationship.
Thatās the dream, unfortunately, the reality is that for many organizations, their data governance practice is mired in conflicting interests of largely divergent stakeholders. There is also the challenge of inter-divisional competition of who owns the customer, and the proverbial data silos that arise from divergent divisional needs.
Some business applications, designed with specific and often narrow objectives in mind, operate within a confined scope of customer data requirements. These applications might be tailored for singular functions such as order processing, billing management, or customer support. In such instances, the focus is primarily on the immediate and specific needs of the application, and the depth of customer data required is limited to the operational necessities of that particular function. While this makes for efficient data processing at the business unit level, it retards opportunities for the whole organization which suffers from the lack of a single identity for the customer with all the salient attributes that make for personalized long-lasting and loyal relationships.
Recognizing the indispensability of a comprehensive customer master, some organizations will embark on a comprehensive rethink of their customer master data management practice. Doing so is a strategic decision and as such, requires a strategic approach to constructing a single, authoritative source of truth for the customer master data information asset accompanied by improved integrations and change management.
Practice not technology
Modern-day Customer Master Data Management also isnāt about the technology as much as it is a realignment of business principles around the most appropriate way to handle the customer and customer data, especially these days in the face of so many emerging and established privacy and consumer protective regulations.
Consider if you will, the fact that how and what you store and nurture as a customer data repository reflects the true essence of your companyās identity. Store it incomplete, haphazardly and with duplicates and youāre relating a narrative that suggests that you simply donāt care too much about data quality and the integrity of the customer master.
Think of the customer master as a reservoir of knowledge that if established properly, can deliver insights, smooth transaction processing, hone personalization and convey confidence and integrity in your teamās engagement with the customer. All this can be done on demand, providing a foundation for robust operational and financial structures. Depending on your industry and the relative intimacy of the relationship with the customer, your business may tap into that reservoir and find previously unexplored areas of opportunity and relationship sustainment.
If youāre in finance or sales, it is easy to see customer data management as a ballet of numbers, for marketing. logistics, service and support it might be other business intricacies like past engagements, previous purchases, warranties, returns and the like. For some, it may even just be about the legitimacy and legalities associated with the customer and their data.
Data governance is the systematic management, control, and oversight of customer-related information within a given organization.
Data governance involves the establishment and enforcement of policies, procedures, and standards to ensure the accuracy, integrity, and security of customer data throughout its lifecycle. The primary goal is to enhance the quality of customer information, facilitate compliance with regulations, and support reliable decision-making processes across the organization.
In his domain, this includes defining roles and responsibilities, implementing data quality measures, and establishing protocols for data access, usage, and privacy.
Some fundamentals
Meticulous management of data quality entails a systematic and detailed approach to ensuring the accuracy, consistency, and reliability of data within an organization. It involves implementing rigorous processes and practices to identify, rectify, and prevent errors, inconsistencies, and redundancies in the data.
The objective is to cultivate a dataset that serves as a trustworthy foundation for decision-making processes, minimizing the risk of misinformation and supporting the organizationās overall goals. This involves continuous monitoring, validation, and improvement efforts to uphold a high standard of data quality throughout its existence.
Security and privacy in the context of customer master data involve systematically implementing measures to protect sensitive customer information from unauthorized access, misuse, and breaches.
This would encompass the establishment and enforcement of policies, procedures, and controls to safeguard customer data against potential threats. The primary goal is to ensure the confidentiality and integrity of customer information, aligning with relevant data protection regulations.
Security and privacy measures also include access controls, encryption, authentication protocols, and ongoing monitoring to detect and respond to any potential security risks. The objective is to create a robust framework that instils confidence in customers, mitigates risks, and upholds the organizationās commitment to data protection.
Data lifecycle management (DLCM) is an integral component of data governance and involves a systematic and comprehensive approach to handling customer data from its creation or acquisition through various stages of utilization, storage, and eventual disposition or archival.
This essential process ensures that data is managed efficiently and in alignment with the organizational objectives and legal obligations of the organization. A DLCM framework includes the formulation of policies, procedures, and standards to govern the handling of data at each stage.
The primary goal of DLCM is to optimize the utility of data while also addressing issues related to data storage, access, and compliance. It requires organizations to define clear retention policies, in particular, specify how long data should be retained based on its value and regulatory requirements. DCLM also involves establishing protocols for secure data disposal or archival once it has fulfilled its purpose.
Executing a DLCM practice well, involves continuous monitoring, assessment, and adaptation of policies to align with changing business needs and regulatory landscapes. This structured approach ensures that data remains a valuable asset throughout its journey within the organization and is managed with efficiency, cost-effectiveness, and compliance in mind.
Thinking about the people
At the heart of any data governance program are people who may or may not be explicitly tagged as the data governance stewards. These are individuals or teams entrusted with the responsibility of maintaining data quality, upholding governance policies and serving as the data owners and people āin the knowā about all things about the data. They are the data domain experts.
Data stewards navigate the vast seas of data, ensuring that each byte is accounted for and that each dataset aligns with the broader goals of the organization. They are the custodians of the data practice.
A more explicit definition would have it, that a data steward is an individual or team responsible for overseeing the management, quality, and governance of data within the organization.
Duties include ensuring data accuracy, defining and enforcing data policies, and maintaining the integrity of data assets. Data stewards play a crucial role in facilitating communication between business units and IT, acting as custodians of data quality and providing expertise on data-related matters.
Their responsibilities encompass data profiling, monitoring, and resolving data issues, as well as collaborating with other stakeholders to establish and adhere to data governance policies. The role requires accountability for the reliability and usability of data across the organization.
Metadata matters
The descriptive information about the customer data, data that provides context, structure, and understanding of its characteristics, is metadata. Such information includes details about the origin, usage, format, and relationships of data. In any data governance program, metadata plays a crucial role in enhancing data discoverability, usability, and overall management.
For customer master data management, metadata associated with customer data would include information about data sources, data quality, and any transformations or processes applied to the data. It helps in maintaining a comprehensive understanding of customer data, ensuring its accuracy and facilitating effective data governance.
For data governance, metadata serves as a bridge between stakeholders and systems. It facilitates collaboration by offering a common language for business users, data stewards, and IT professionals. Stakeholders leverage the metadata to comprehend the meaning and lineage of the customer data, converging on a shared understanding for everyone across the organization. Metadata also enhances the interoperability of systems by providing a standardized framework for data exchange and integration, promoting consistency and coherence in the data landscape.
No respected data governance program is launched, adopted and survives without data governance and management policies. Data Governance policies define who can access specific data, how it can be used, and under what circumstances. These policies form a framework that prescribes how to prevent unauthorized access and ensures responsible data utilization as well as other behaviours and measures that serve to protect the integrity of the customer master.
A data governance council or committee overseeing and steering the program is helpful but not essential. Comprising representatives from various business units and the IT realm, this body ensures that data governance aligns with organizational objectives, and its impact is felt across the entire enterprise.
Fostering a culture of data awareness and responsibility becomes a crucial act in this governance play. Communication and training programs under the aegis of a data governance program are the conduits through which employees grasp the importance of data governance, the program aims to develop an understanding of their roles in maintaining data quality and integrity.
Culturally a data governance program requires a major shift where each employee becomes informed and empowered as a guardian of the data they interact with, hopefully thereby recognizing its intrinsic value.
Continuous improvement in data governance is another essential trait of a data governance program which is sustained through a dynamic and iterative process that prioritizes refinement, adaptability, and ongoing assessment.
Continuous improvement involves regular evaluations of data quality, security protocols, and adherence to established policies.
Organizations that foster a culture of feedback, with data stewards and relevant stakeholders providing insights into the efficacy of existing practices are the most successful.
Insights from continuous improvement initiatives guide adjustments to data governance policies and procedures, ensuring they align with evolving business needs and industry standards. Implementing feedback loops, periodic audits, and staying attuned to technological advancements in data management contribute to the ongoing enhancement of data governance strategies.
This commitment to continuous improvement not only safeguards the integrity of customer master data but also enables the organization to respond effectively to changes in the data landscape, maintaining a robust and adaptive foundation for strategic decision-making.
Effective risk management within customer master data management involves implementing robust processes to identify, assess, and mitigate potential risks associated with the handling of customer information. This includes ensuring the accuracy, completeness, and security of customer data to prevent errors, fraud, and unauthorized access.
A comprehensive risk management approach would also involve regular audits and monitoring to detect anomalies or irregularities in customer data, as well as establishing clear protocols for data governance and compliance with relevant regulations such as data protection laws.
By proactively addressing risks related to customer master data, organizations can enhance data quality, build trust with customers, and safeguard sensitive information, ultimately fostering a more resilient and secure customer data management environment.
Evaluating a prospective source of truth
The criteria for selecting the right home for your CMDM initiative will revolve around the accuracy and integrity of data. Whatever you choose for CMDM it must incorporate robust validation mechanisms and quality checks to uphold the sanctity of customer data, preventing errors and discrepancies that might reverberate through the entire organizational structure.
Integration capabilities will likely play a crucial role in the CMDM selection process, whether it be in support of Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), or other systems. Such integration will ensure a unified and consistent view of the customer data, eliminating silos and fostering a panoramic perspective across the enterprise.
Scalability becomes the next checkpoint in the CMDM evaluation. Will your choice accommodate a likely ever-growing number of occupants? A CMDM solution must exhibit scalability to handle an expanding volume of customer data. If your business landscape is dynamic, then the chosen system should gracefully scale to meet the demands of your expanding enterprise without compromising performance.
Security measures are non-negotiable when dealing with customer data. The selected CMDM home should have robust security, actively defending against unauthorized access, monitoring for data breaches, and proactively looking out for cyber threats. For customer data, sanctity and confidentiality are paramount, you must make security a top priority for your CMDM abode.
Quite naturally, user-friendliness and the proverbial UXD (User Experience and Design) is often a pivotal criterion in any selection process. The experience should be intuitive and provide a user-friendly interface that supports employeesā easy navigation and interaction with the customer data. Such a system would foster user adoption through its design and navigational simplicity; enhance productivity and ensure that the benefits of CMDM permeate throughout the organizational structure.
Data governance should be centre stage. CMDM home must shelter and govern the data within its confines. A CMDM that comprehensively supports your data governance framework is imperative. You will want to be able to outline and enforce policies, standards, and processes for the entire lifecycle of customer data. This ensures internal consistency and compliance with external regulatory requirements, safeguarding the organization against legal ramifications.
Flexibility and customization emerge as key facets in this selection saga. Every organization has unique preferences and requirements. Your choice of CMDM solution should mirror this diversity, offering flexibility and customization options that align with specific business processes and evolving data management needs. The home for your customer data should not be an entirely rigid structure but rather an adaptable space that flexes with the unique rhythm of the organization it serves.
AI and Machine Learning Integration bring a futuristic dimension to the CMDM narrative. The idea of CMDM solutions leveraging AI and machine learning suggests opportunities to plumb the depths of the data with advanced data matching, deduplication, and predictive analytics. Such an infusion of intelligence would enhance the accuracy and utility of the customer master and provide insights that transcend traditional data management boundaries.
We believe that the Pretectum CMDM will address all of these expectations and provide you with some surprising additional ones. Contact us today to learn more.
You might have more recently heard of ācomposableā solutions, this composability refers to the flexibility and modularity of systems, allowing organizations to adapt, customize, and integrate them into their existing technology landscape efficiently.
The concept of composable solutions has been largely in the shadows for the past decade, with its roots tracing back to the evolution of modular and service-oriented architectures in software development. However, it is gaining more prominence in the context of enterprise systems descriptions.
In the 2010ās there was a notable shift towards more flexible and agile approaches to software design and integration within enterprises. This shift was driven by factors such as the increasing complexity of business requirements, the rise of cloud computing, the growing demand for scalability and interoperability, and the emergence of microservices architecture. Itās fair to say that the term started gaining traction notably around the mid-2010s and has since become a key aspect of discussions surrounding modern enterprise software architecture and integration strategies.
For master data management and customer master data management in particular, a composable approach involves breaking down data management processes into modular components that can be easily assembled or reconfigured to meet specific data governance and data quality requirements.
Composable CMDM solutions allow organizations to adapt to evolving data landscapes and support various varied demands of organizations about customer master data management, including ensuring data accuracy, consistency, and compliance. Additionally, these solutions enable organizations to scale more effectively and integrate seamlessly with existing technology ecosystems.
Overall, composable solutions represent a significant paradigm shift in enterprise systems architecture, offering organizations the flexibility and agility needed to navigate the complexities of modern business environments.
Pretectum CMDM aligns with the concept of the composable solution by offering a flexible, scalable, and interoperable platform that supports the modular and service-oriented architecture businesses are increasingly adopting.
The platformās design allows for seamless integration with various software applications, facilitating smooth data flow across different departments and systems.
This integration capability is crucial for promoting collaboration, enhancing productivity, and enabling a more agile response to customer demands. Furthermore, Pretectum CMDMās ability to scale both vertically and horizontally accommodates the growing volume and complexity of data, ensuring that businesses can rely on it as a foundational data management solution that evolves with their needs.
By automating data integration, cleansing, and standardization processes, Pretectum CMDM reduces manual effort and human error, supporting the principles of composable solutions where efficiency and adaptability are key.
Pretectum CMDM vs monolithic solutions
Older monolithic Customer Master Data Management (CMDM) architectures have all components of the CMDM tightly integrated into a single, cohesive application. In this architecture, all functionalities, such as data storage, data processing, data governance, and user interfaces, are bundled together within a single application or platform.
Traditional stacks with their tightly integrated components are difficult to separate or modify. Changes often require extensive reconfiguration or redevelopment of the entire system. Such platforms struggle with adapting to change due to their tightly coupled nature. Upgrades or changes often involve significant downtime and risk of system instability.
Integrating these traditional stacks with newer technologies or external systems can be challenging and may require custom development efforts. Interoperability issues are common, leading to data silos and inefficiencies. Scaling the traditional stacks often involves scaling the entire system, which can be costly and inefficient.
Vertical scaling may lead to performance bottlenecks, while horizontal scaling can be complex and disruptive. Automation capabilities in traditional stacks may also be limited, leading to manual intervention in repetitive tasks and increased risk of errors.
The Pretectum CMDM, with its composable architecture, offers benefits in terms of flexibility and modularity, adaptability to change, integration and interoperability, scalability, automation, and efficiency to all shapes and sizes of organizations.
Pretectum CMDM employs a modular architecture, which allows organizations to break down data management processes into smaller, reusable components. This modularity enables greater flexibility in configuring the CMDM solution to meet specific business requirements. An organization can choose which parts of the platform they want to use, based on their needs. Part of this is also covered by the deployment approaches for CMDM. Adding or removing components as necessary gives the organization many options and a great deal of flexibility. This flexibility ensures that the CMDM solution can evolve alongside the changing business landscape and evolving data governance requirements.
With the composable architecture, Pretectum CMDM supports high adaptability to changes in business requirements, technology advancements, and regulatory frameworks. Organizations can easily take advantage of new functionality as it becomes available or switch approaches to individual components or discrete functionality with minimal disruption. This adaptability enables organizations to respond quickly to emerging trends, regulatory updates, or shifts in customer demands, ensuring that the CMDM solution remains relevant and effective over time.
Seamless integration with existing systems and technologies is essential with all modern systems, the promotion of interoperability across the organizationās data landscape is emphasized by support for meshed customer data management. The modularity of the platform allows for easy integration with department or division or business unit-specific software applications, databases, and third-party services.
By facilitating data flow across different departments and systems, Pretectum CMDM promotes collaboration, enhances productivity, and ensures consistent data across the organization.
Pretectum CMDMās composable architecture enables both vertical and horizontal scalability, allowing organizations to scale their CMDM solution to accommodate growing data volumes, user loads, or business expansion. Vertical scaling involves adding resources such as CPU, memory, or storage with minimal impact ā this is achieved as a result of the SaaS architecture of the platform. Horizontal scaling involves adding more instances of components to distribute the workload, this is not a problem for the platform because it is built multi-tenant from the bottom up and makes use of on-demand compute resources. This scalability ensures that the platform services the needs of your organization and many others, as required.
Automation is a key feature of Pretectum CMDM, streamlining integration, loading, standardization, quality assessment and deduplication, and other data management processes. By automating repetitive tasks, the Pretectum CMDM reduces manual effort and human error, improving your teamsā overall efficiency. Automated workflows and business rules also help drive improved data quality, consistency, and compliance, supporting the principles of composable solutions where efficiency and adaptability are paramount.
Omicommerce is a convergence on 1:1 brand : consumer engagement.
There have been several pieces of research and surveys published since the start of 2024 from Mintel, UoM, Capgemini, and Qualtrics.
Mintelās report identifies five behavior trends shaping consumer markets beyond 2024 and their insights cover topics like sustainability, personalization, and changing consumer expectations.
UoM found that consumer sentiment rose significantly in January 2024, reaching its highest level since July 2021 and year-over-year consumer sentiment also showed a substantial increase.
Capgeminiās āWhat matters to todayās consumerā survey of 10,000 people, in 10 countries just one vital question āWhat matters to you?ā It found that in its focus on consumer behavior in the consumer product and retail industries, it could come up with strategies for success in innovation and new product development that focus on the impact of emerging technologies and changing consumer expectations.
Qualtricsā survey was based on responses from over 28,000 consumers across 26 countries. focused on preferences, complex customer journeys, and rising expectations with some valuable insights for businesses aiming to build meaningful connections with consumers.
The combined results reveal some important trends and sentiments amongst consumers to create compelling and positive experiences.
The combined reports emphasize the significance of human connection in customer experiences alongside the rise of AI technologies.
Consumers prioritize human interaction for critical tasks but accept AI for simpler activities. As such successful AI strategies entail understanding customer preferences for human versus digital interactions and leveraging AI to augment these connections.
There has been a resurgence in in-store shopping and continued strength of eCommerce ā OmniCommerce and the Phygital. As a result quality customer service and post-purchase experiences foster consumer loyalty more than price competitiveness. Organizations that invest heavily in frontline employee training and service quality stand to gain customer loyalty.
Digital support experiences trail human interactions in satisfaction but present significant improvement opportunities. Enhancing digital experiences is vital for customer retention and loyalty.
Consumers are also inclined to provide less direct feedback, necessitating diverse listening tools beyond traditional surveys. Integrating operational data with feedback from various sources provides insights into customer sentiments and behaviors.
A trend towards direct ordering (D2C) from brands, signaling a shift in purchasing behavior supports the view that there is an increased importance accordingly, of efficient delivery and fulfillment services, particularly in certain retail categories.
Consumer priorities are centered around healthy, sustainable living, influencing purchase decisions. The reports determined that there are four key actions for brands and retailers to capitalize on these trends.
There is accordingly a blurring distinction between online and in-store shopping, with consumers expecting comparable levels of service and experience across both channels. All this underscores the need for organizations to prioritize human connections, improve customer service quality, enhance digital support experiences, and adapt to changing feedback dynamics to meet evolving consumer expectations in 2024 and beyond.
These insights provide valuable guidance for retailers and brands aiming to navigate the evolving consumer landscape, emphasizing a customer-centric approach, data-driven decision-making, ethical data practices, personalization, real-time insights, multichannel engagement, and sustainability.
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https://www.pretectum.com/is-your-business-powered-by-customer-data/
You might have more recently heard of ācomposableā solutions, this composability refers to the flexibility and modularity of systems, allowing organizations to adapt, customize, and integrate them into their existing technology landscape efficiently.
The concept of composable solutions has been largely in the shadows for the past decade, with its roots tracing back to the evolution of modular and service-oriented architectures in software development. However, it is gaining more prominence in the context of enterprise systems descriptions.
In the 2010ās there was a notable shift towards more flexible and agile approaches to software design and integration within enterprises. This shift was driven by factors such as the increasing complexity of business requirements, the rise of cloud computing, the growing demand for scalability and interoperability, and the emergence of microservices architecture. Itās fair to say that the term started gaining traction notably around the mid-2010s and has since become a key aspect of discussions surrounding modern enterprise software architecture and integration strategies.
For master data management and customer master data management in particular, a composable approach involves breaking down data management processes into modular components that can be easily assembled or reconfigured to meet specific data governance and data quality requirements.
Composable CMDM solutions allow organizations to adapt to evolving data landscapes and support various varied demands of organizations about customer master data management, including ensuring data accuracy, consistency, and compliance. Additionally, these solutions enable organizations to scale more effectively and integrate seamlessly with existing technology ecosystems.
Overall, composable solutions represent a significant paradigm shift in enterprise systems architecture, offering organizations the flexibility and agility needed to navigate the complexities of modern business environments.
Pretectum CMDM aligns with the concept of the composable solution by offering a flexible, scalable, and interoperable platform that supports the modular and service-oriented architecture businesses are increasingly adopting.
The platformās design allows for seamless integration with various software applications, facilitating smooth data flow across different departments and systems.
This integration capability is crucial for promoting collaboration, enhancing productivity, and enabling a more agile response to customer demands. Furthermore, Pretectum CMDMās ability to scale both vertically and horizontally accommodates the growing volume and complexity of data, ensuring that businesses can rely on it as a foundational data management solution that evolves with their needs.
By automating data integration, cleansing, and standardization processes, Pretectum CMDM reduces manual effort and human error, supporting the principles of composable solutions where efficiency and adaptability are key.
Pretectum CMDM vs monolithic solutions
Older monolithic Customer Master Data Management (CMDM) architectures have all components of the CMDM tightly integrated into a single, cohesive application. In this architecture, all functionalities, such as data storage, data processing, data governance, and user interfaces, are bundled together within a single application or platform.
Traditional stacks with their tightly integrated components are difficult to separate or modify. Changes often require extensive reconfiguration or redevelopment of the entire system. Such platforms struggle with adapting to change due to their tightly coupled nature. Upgrades or changes often involve significant downtime and risk of system instability.
Integrating these traditional stacks with newer technologies or external systems can be challenging and may require custom development efforts. Interoperability issues are common, leading to data silos and inefficiencies. Scaling the traditional stacks often involves scaling the entire system, which can be costly and inefficient.
Vertical scaling may lead to performance bottlenecks, while horizontal scaling can be complex and disruptive. Automation capabilities in traditional stacks may also be limited, leading to manual intervention in repetitive tasks and increased risk of errors.
The Pretectum CMDM, with its composable architecture, offers benefits in terms of flexibility and modularity, adaptability to change, integration and interoperability, scalability, automation, and efficiency to all shapes and sizes of organizations.
Visit https://www.pretectum.com/composable-customer-master-data-management-cmdm/ to learn more
Jardine Cycle & CarriageĀ is a well-known brand in Singapore and Malaysia with a reputation that has been built up over the past 125 years and nowĀ servingĀ Singapore, Malaysia Indonesia, Thailand, Vietnam, and Myanmar. As a premier automotive dealership on the Malayan peninsula, they have operated since 1899 offering iconic automotive brands like Mercedes-Benz, Mitsubishi, Chrysler, Jaguar, Kia, and CitroĆ«n brands.
As the tides of technology continue to reshape industries, JC&C, with its clientele spanning the affluent and high-affluent segments, has seemingly embarked on a new transformative journey by forging an innovative strategic partnership with ada to integrate AI/NLP technologies and āredefine the automotive experienceā.
Malaysian multinational Telecomms conglomerate Axiataās ada (analytics, data, advertising), is headquartered in Singapore and Malaysia, and partners with leading brands across Asia to drive their digital & data maturity and achieve their business goals. In sharp contrast to JC&C, theyāre a relatively young company vested by Axiata in 2014 and supported by renowned regional brands like Mitsui, Sumitomo Corporation and SoftBank Group. They bill themselves as a leader in digital transformation across Asia focused on automated customer service solutions and data-driven marketing strategies. Serving 12 markets, working with a composable CDP that makes use of best in class components and leveraging tools like Databricks, ada complements its unique digital expertise with deep proprietary data of 375 Million consumers served by over fourteen hundred employees associated with just as many commercial clients. ada have been recipients of numerous awards like the Effie Awards with Gold, Silver, and Bronze accolades for innovative campaigns in multiple markets.
In an article from The Edge Malaysia Weekly, dated July 8, 2019, Axiata Groupās digital advertising arm, ada, unveiled a plan to revolutionize the advertising industry through the strategic use of tech data and innovative business models.
At the time, led by CEO Srinivas Gattamneni, ada aimed to cater to the evolving landscape of digital consumers by providing digital marketing, data science, and platform-building solutions. Backed by Axiata Digital, ada aspired to become the agency of the future, blending data science, consulting, and agency services.
The substantial investments and ambitious goals aimed to disrupt business models and focus on value-driven approaches to shift industry norms. Central to adaās digital strategy is emphasis on data-driven advertising, leveraging deep consumer insights to deliver targeted and impactful campaigns. By harnessing data from various sources and investing in technology, ada sought to maximize advertising ROI and drive business outcomes for clients. ada anticipated the seismic shift towards programmatic and automated ad buying, albeit with the concomitant challenges of bad actors using technologies like bots to drive activity and commit fraud.
Despite being a young player in the industry, adaās apparent rapid growth and innovative approach continue to signal its potential to disrupt the marketing landscape as a whole and shape digital futures in marketing.
Their collaboration with JC&C of course will not come without challenges, amongst them those related to data privacy and security as well as compliance with regulatory requirements. Transparency in what data is used and how it is used is essential in maintaining customer trust and so the integration of AI requires careful planning and ethical considerations.
As Cycle & Carriage and ADA continue on their collaborative journey, the fruits of their labor appear to becoming manifest. From enhanced customer engagement to streamlined operations, the impact of AI integration is apparently palpable, Cycle & Carriage leverages ADAās expertise to implement AI-powered chatbots, personalized marketing campaigns, and data-driven insights, driving tangible business outcomes and setting a new standard for digital transformation in the automotive industry.
Not every organization can be a JC&C nor will they be able to afford a relationship with an agency like ada. It might not even be that relevant given they are a regionally focused player, however consider the following.
Letās be clear, Pretectum CMDM is not a part of the tech stack in use in this example, we present it, because it demonstrates some great possibilities for any organization. What we would like you to consider, is how any composable CDP that incorporates something like the Pretectum Customer Master Data Management (CMDM) system, could be leveraged to support more personalized engagement with customers through various touch points in marketing, sales, service, and support channels for any organization.
By centralizing and standardizing customer data across departments and systems, Pretectum CMDM enables businesses to have a holistic view of each customer.
This approach allows for better organizational decision-making, enhanced customer interactions, and the delivery of more personalized customer experiences. More specifically using Pretectum CMDM could involve the following strategies to enhance customer engagement:
Personalized Marketing Campaigns: By using the centralized repository of customer data in Pretectum CMDM, you can create targeted and personalized marketing campaigns tailored to individual customer preferences and behaviors.
AI-Powered Chatbots: Implementing AI-powered chatbots integrated with CMDM data can provide real-time assistance and personalized responses to customer queries across various channels.
Data-Driven Insights: Use the comprehensive customer data stored in CMDM to derive valuable insights that can drive strategic decision-making in marketing, sales, and service operations.
Enhanced Customer Service: Ensure that all parts of the organization have access to up-to-date, verified, and consented, reliable customer information from the CMDM system, improving customer service interactions and overall satisfaction.
Streamlined Operations: By centralizing and synchronizing customer data, organizations can streamline operations, leading to more efficient processes in marketing, sales, and service functions.
By adopting these kinds of strategies with a CMDM platform like the Pretectum CMDM, organizations can enhance their customer engagement efforts across multiple touch points, ultimately leading to improved customer relationships, increased brand loyalty, and better business outcomes.
There is a logical progression of concepts that build upon each other to articulate the comprehensive benefits of Customer Master Data Management (CMDM).
This starts with the foundational importance of data quality in a solution like the Pretectum CMDM. Data quality serves as the bedrock upon which all subsequent benefits rely. Without accurate and reliable customer data, organizations cannot effectively streamline operations, make informed decisions, or enhance the customer experience. Therefore, itās crucial to establish data quality as a primary focus of any CMDM program.
CMDM streamlines customer data management operations. By centralizing and unifying customer data, organizations can eliminate inefficiencies associated with managing disparate data sources. This streamlined approach not only reduces operational costs but also lays the groundwork for more effective decision-making and customer engagement.
With operations streamlined, the question then, is how CMDM empowers organizations to make better decisions. By providing comprehensive insights into customer behavior and preferences, CMDM enables decision-makers to formulate more targeted strategies and initiatives. This, in turn, leads to more impactful customer interactions and ultimately drives business success.
Building upon the theme of decision-making, CMDM enhances the customer experience. Organizations can deliver personalized interactions and seamless experiences across all touchpoints by leveraging deep insights into customer data. This not only fosters customer satisfaction but also strengthens brand loyalty and advocacy.
Everything is done in pursuit of driving revenue growth. By optimizing operations, decision-making, and customer experience, CMDM enables organizations to capitalize on revenue opportunities and maximize customer lifetime value. This solidifies the value proposition of CMDM as a strategic imperative for organizations looking to achieve sustainable growth and success in todayās competitive business landscape.
Enhanced Data Quality
Ensuring superior data quality is fundamental for any organization leveraging a Customer Master Data Management (CMDM) solution. It is the cornerstone of all customer-related initiatives, ensuring that every interaction, analysis, and decision is based on accurate and consistent customer information. By meticulously identifying and rectifying discrepancies, purging redundancies, and maintaining data integrity across customer datasets, CMDM guarantees that businesses have a reliable foundation for their customer-centric strategies. This commitment to data quality not only instills trust in customer data but also minimizes the risk of errors, misinformation, and misguided decisions, ultimately leading to more effective customer engagement and sustained business success.
Streamlined Operations
Streamlining operations through Customer Master Data Management (CMDM) is essential for organizations aiming to enhance efficiency and agility in customer-facing activities. By establishing a unified and centralized repository of customer information, CMDM eliminates the complexities and inefficiencies associated with managing disparate customer data sources. This unified approach not only accelerates customer-related processes but also reduces operational costs stemming from data redundancy, manual reconciliation efforts, and inconsistent workflows. With streamlined operations enabled by CMDM, organizations can respond more swiftly to customer needs, deliver personalized experiences, and seize market opportunities, thereby maintaining a competitive edge and driving business growth.
Improved Decision-Making
Enhanced decision-making facilitated by Customer Master Data Management (CMDM) is critical for organizations seeking to optimize customer interactions and drive sustainable growth. By providing decision-makers with comprehensive and accurate insights into customer behavior, preferences, and interactions across various channels, CMDM empowers them to make informed decisions with confidence. This holistic view of customer data enables executives to identify trends, forecast demand, and anticipate customer needs more accurately. As a result, organizations can develop targeted marketing strategies, optimize resource allocation, and deliver personalized experiences that resonate with their customers, ultimately driving customer satisfaction, loyalty, and profitability.
An Ability to Drive New Customer Experiences
Elevating the customer experience through Customer Master Data Management (CMDM) is paramount for businesses aiming to build enduring relationships and foster brand loyalty. Only by consolidating and centralizing customer data from disparate sources, CMDM systems enable organizations to gain a holistic understanding of their customerās preferences, behaviors, and interactions. Armed with this comprehensive insight, businesses can personalize interactions, tailor products and services, and deliver seamless experiences across touchpoints, thereby enhancing customer satisfaction and fostering long-term loyalty. Moreover, by leveraging CMDM to anticipate and address customer needs proactively, organizations can differentiate themselves in the market and position themselves as trusted advisors, driving customer advocacy and revenue growth.
Increased Revenue
Driving revenue growth through Customer Master Data Management (CMDM) is a strategic imperative for businesses seeking to capitalize on customer insights and market opportunities. By leveraging CMDM to analyze customer data, segment audiences, and target the right customers with personalized offerings, organizations can enhance conversion rates, increase sales performance, and maximize customer lifetime value. Additionally, by delivering consistent and compelling experiences across channels, CMDM helps organizations cultivate customer loyalty and advocacy, driving repeat business and revenue growth.
Customer Benefits
Based on their significance in directly impacting the customer experience and fostering long-term relationships with customers, consider these important customer benefits when you focus on your customer master data management.
Personalization is a key driver of customer satisfaction and loyalty. When businesses understand their customersā preferences and tailor interactions accordingly, it creates a more engaging and meaningful experience for the customer, ultimately leading to higher satisfaction and repeat business.
Customers expect businesses to have accurate information about them. By ensuring data accuracy, businesses can make informed decisions that directly impact the customer experience. For example, offering relevant products or services based on accurate customer data leads to more positive interactions and increased trust.
Quick and effective customer support is crucial for resolving issues and building trust with customers. By providing support representatives with a holistic view of the customer and any journeys with the customer, an organization can address relationship needs more efficiently, leading to higher satisfaction and loyalty.
Customers appreciate relevant and appropriate suggestions and recommendations at the right and best time to cater to their interests preferences and situations. Leveraging customer data, an organizationās teams and applications can make more precise, targeted, and accurate recommendations, businesses can enhance the shopping experience, increase sales, and build stronger relationships with customers.
I f your organization is in the business of selling goods, or services, or simply having a relationship with consumers; targeted marketing campaigns are more effective in engaging than generic messaging. By segmenting customers based on their characteristics and behaviors, businesses can tailor their marketing efforts to specific audience segments, resulting in higher engagement and conversion rates.
These five benefits directly contribute to a positive customer experience by providing personalized interactions, accurate information, efficient support, relevant recommendations, and targeted marketing efforts. By focusing on these areas, organizations can strengthen their relationships with consumers and audiences and drive long-term loyalty and satisfaction.
The value proposition of a Customer Master Data Management (CMDM) system like the Pretectum CMDM, lies in its ability to holistically enhance the entire customer experience journey.
By ensuring superior data quality, streamlining operations, improving decision-making, enabling new customer experiences, and driving increased revenue, CMDM becomes a strategic imperative for organizations. The system provides personalized interactions, accurate information, efficient support, relevant recommendations, and targeted marketing efforts, ultimately fostering enduring relationships, customer loyalty, and satisfaction in todayās competitive business landscape.
Pretectum CMDM serves as the foundation for businesses seeking sustainable growth and success by leveraging comprehensive customer insights and delivering exceptional experiences across touchpoints; Pretectum CMDM serves up the single customer view, integrates it with your business sources and analytics platforms, and provides your personnel with a unified view of the customer with data that can be as rich and comprehensive as your imagination permits.
Customer data, while frequently abundant, is not always reliable. in their Winter 2016 Compendium on Customer Experience: Creating Value through transforming customer journeys. McKinsey & Co. point out that a staggering 25 percent of customers will defect after just one bad experience. Bad experiences can be fomented by bad data, bad products, and bad interactions. But the one thing that costs the least to remediate, is often the data.
Just 20% of organizations publish data provenance and data lineage. Most donāt say they have no plans to start, thatās according to a 2020 OāReilly survey. Without an understanding of where data comes from, what hope is there of improving its quality?
Annual data decay rates, may be as high as 30% across companiesā customer data each year, a figure that escalates to 70% for B2B companies. This decline in data integrity intensifies over time, posing a critical challenge for businesses aiming to provide exceptional customer experiences.
In this data turmoil, the significance of Customer Master Data Management (CMDM) systems cannot be overstated. These systems act as custodians of customer data, ensuring its accuracy, completeness, and currency. Within this realm, customer consent, self-service consumer data verification, and curation play pivotal roles. CMDM systems empower businesses to navigate the intricate landscape of customer data, addressing issues like missing or incomplete data, duplicates, inaccuracies, and expired data.
At the core of this challenge lies the concept of data quality, a term with profound implications for businesses. Data quality is not just a technical concern; it is the foundation upon which successful customer experiences are built. Dependable data forms the basis for businesses to segment and target customers for marketing, a strategy employed by two-thirds of companies. The importance of data quality initiatives can be distilled into three key pillars: data quality, data governance, and leadership support. Companies with higher data quality invariably exhibit traits such as leadership awareness of data issues, a robust governance structure, and data management being the responsibility of a cross-functional team.
read more at https://www.pretectum.com/data-is-the-differentiator-for-customer-experience/
The Pretectum CMDM system, as a SaaS offering, ensures robust security and compliance while efficiently managing membership data, facilitating seamless processes such as renewal events, membership segmentation, and integration with other systems, ultimately empowering organizations to enhance member value and drive growth.
Managing membership data efficiently and securely is paramount for organizations across many industries and interest areas.
Software as a Service (SaaS) offerings like that of the Pretectum Customer Master Data Management (CMDM) system offer effective membership data management as a critical capability. Key features and focus areas are security, compliance, storage of personal data, renewal events, segmentation, reporting, and integration with other systems.
Security and compliance are fundamental aspects of membership data management. The Pretectum CMDM system employs robust security measures to safeguard sensitive member information, to keep it encrypted, securely stored, and away from the prying eyes (and hands) of unauthorized users.
This includes encryption techniques, access controls, and support for regular security audits to mitigate potential risks such as data breaches or unauthorized access.
Pretectumās Role-Based Access Control (RBAC) is a key feature in securing and protecting membership data. It works by assigning users to specific business areas where they have certain levels of permission. These business areas, in turn, have control over data schemas and data itself.
Users are granted access to objects within the Pretectum CMDM platform through a āleast permissionsā model. This means they only have the necessary permissions to perform their tasks and no more, reducing the risk of unauthorized access or data manipulation.
Access is granted to users via an identifier with an accompanying password for UI access, and the same with a token via API. Users are then further restricted based on a hierarchy of permissions based on their organizational assignment and very fine-grained permissions within that organizational assignment.
All these measures ensure that the right people have the right access, helping to maintain the confidentiality and privacy of your membership data in support of various privacy and compliance regulations that your organization might be subject to, anywhere in the world.
Storing Membership Personal Data
The Pretectum CMDM system efficiently stores membership personal data, including demographic information, contact details, preferences, and aggregated history according to the models (schemas) and grouped datasets according to your organizational needs.
The centralized repository enables organizations to access comprehensive member profiles, facilitating personalized interactions and tailored services. By categorizing data according to membership types or levels, organizations can streamline communication, target promotions effectively, and enhance member satisfaction.
Continuous contact with consent
Managing membership renewal events is essential for sustaining member engagement and revenue generation. The Pretectum CMDM system tracks renewal dates if you maintain them, could be leveraged for sending customers reminders, and ultimately facilitates seamless renewal processes.
Regularised requests to members to update their contact details or to provide consent for the use of their data support the sustainment of a long term membership relationship.
Automated process flows streamline administrative tasks for the back office, reducing manual intervention and minimizing errors. The ability to support integration with your payment processing systems ensures support for uninterrupted membership benefits for members.
Non-Transactional Data Management
In addition to supporting the storage of aggregated transactional data from your various back office systems, the non-transactional aspocts of member data plays a crucial role in understanding member behavior and preferences.
The Pretectum CMDM system could be used to capture non-transactional data such as interest or participation in events, engagement with digital content, and feedback survey results. Analyzing this data provides valuable insights into member interests, enabling organizations to tailor offerings, anticipate needs, and enhance member experiences.
Member onboarding
Efficient member approval processes are vital for attracting and retaining members. The Pretectum CMDM system assists in being able to support the streamlining of membership application procedures through integrations. This allows you to automate validation checks and approval workflows.
Integration with identity verification services ensures the authenticity of member credentials, reducing the risk of fraudulent registrations. Real-time updates enable organizations to track the status of membership applications and promptly address any issues, enhancing operational efficiency and member satisfaction.
Once the record appears in the system, the ability to provide contact data or personal data verification is built-in and can be augmented with requests for affirmation of consent to the use of membership data.
Segmentation and Reporting
Segmentation and reporting capabilities empower organizations to target specific member segments and evaluate performance effectively. The Pretectum CMDM system enables dynamic segmentation based on criteria such as demographics, of other data stored which could include preferences, tastes, and interests.
A powerful natural language search and customizable reporting provide actionable insights into membership trends, retention rates, and revenue generation. By analyzing segmentation data, organizations can tailor membership campaigns, optimize resource allocation, and maximize ROI.
Membership Tracking and Contact Information Management
Tracking member interactions and managing contact information are essential for maintaining accurate member records. The Pretectum CMDM system can be used to store the results of any tracked member interactions across any touchpoints, including website visits, email communications, and social media engagement. Centralized contact management ensures that organizations have up-to-date contact information, facilitating targeted communication and personalized outreach efforts.
The member profile serves as a central hub for integrating with other systems within the organization. Integration with Customer Relationship Management (CRM) systems enables seamless communication and collaboration between marketing, sales, and support teams. Integration with analytics platforms facilitates data-driven decision-making, enabling organizations to measure performance, track KPIs, and identify areas for improvement. Integration with e-commerce platforms enables personalized product recommendations, upselling opportunities, and seamless checkout experiences, driving revenue growth and member satisfaction.
Effective membership data management is essential for organizations seeking to maximize member value, drive growth, and enhance organizational effectiveness. The Pretectum CMDM system offers a comprehensive solution for managing membership data securely and efficiently in a SaaS environment. By prioritizing features such as security, compliance, personalized experiences, and integration capabilities, organizations can unlock the full potential of their membership programs, foster member loyalty, and achieve sustainable success in the digital era.
Setting precise objectives is an indispensable factor in the successful implementation of Customer Master Data Management (CMDM).
The fundamental threat to a burgeoning CMDM program lies in its initiation with unclear or ambiguous business objectives. Although overarching goals such as enhancing data quality, supporting informed decision-making, achieving a unified truth, or obtaining a 360-degree customer view might seem logically sound, they often lack the specificity required for the effective execution of a CMDM program.
Gartner, a leading research and advisory company, highlights four key reasons for Master Data Management (MDM) program failures, among them insufficient executive sponsorship, inadequate adjustment of business processes, a lack of validation, and the potential pitfalls of an āall at onceā or ābig-bangā implementation strategy. These pitfalls underscore the critical importance of a carefully structured and well-defined approach in implementing CMDM initiatives.
One notable aspect contributing to failure might be the absence of a structured framework to measure the value of data management for an organization, particularly within the domain of customer data. Without well-defined objectives, CMDM initiatives often struggle to progress beyond their initial stages or may fail outright during implementation.
To mitigate the risk of CMDM failure and ensure the success of the program, it is imperative to follow a systematic approach. The first step involves defining measurable business outcomes related specifically to customer data. The litmus test for these objectives lies in the ability to articulate CMDM outcomes in non-technical terms that resonate with both business and IT stakeholders. If an organization cannot express its objectives without relying on technical jargon, it raises a red flag, indicating the need for re-evaluation.
A helpful technique in this regard is to encourage organizations to state their objectives without using the word ādataā Instead, the focus should be on articulating business objectives related to customer data that CMDM aims to address.
Increasing customer retention rates: Achieved by reducing customer service response times to a specific duration, for example.
Augmenting cross-sell opportunities: Achieved through a more personalized enhancement of the customer experience. This might be another.
Improving CSAT scores: As a lagging indicator through more accurate and timely responses to customer interactions.
By steering away from technical language and concentrating on specific business outcomes linked to customer data, organizations can ensure that CMDM objectives are clear, understandable, and relevant to all stakeholders.
Understanding the core motivations behind CMDM initiatives is paramount. Whether the objective is to increase customer loyalty, optimize marketing strategies, or personalize customer interactions, there must be a compelling business reason underpinning CMDM efforts. Organizations need to document these customer-centric business challenges and connect them to the āwhatā and āhowā of the CMDM project.
Failure to establish this connection can lead to confusion and a loss of focus. To prevent this, organizations must emphasize the value of CMDM by demonstrating its ability to drive customer-centric outcomes, such as personalized marketing campaigns, improved customer service, or enhanced customer loyalty programs. Identifying specific quick wins related to customer data is crucial to showcasing the tangible value of the CMDM program.
Beyond traditional Return on Investment (ROI) studies, CMDM initiatives focused on customer data require a roadmap that outlines the core business problem and provides a detailed plan to address it. This roadmap should encompass stakeholder engagement and commitment strategies, ensuring that the CMDM program progresses smoothly from conception to implementation, specifically in the domain of customer master data.
An effective āStrategic Outcomes Blueprintā (SOB) is instrumental in identifying quick wins related to customer data that prioritize business outcomes, thereby highlighting the value of the CMDM program.
A āStrategic Outcomes Blueprintā should include:
A clear description of the customer-centric business opportunity, such as increasing customer lifetime value or improving customer retention rates.
Prioritized initiatives and resource allocation focusing on customer data management.
Key performance indicators specific to customer data quality, customer satisfaction, or customer engagement.
Quantification of projected ROI related to customer-centric outcomes.
By creating a compelling business case through the SOB, organizations can think big while starting small, focusing on targeted problem-solving related to customer data and demonstrating the immediate value of the CMDM program.
Itās crucial to recognize that CMDM in the context of customer master data is not a one-time project but a continuous journey. By tying CMDM implementations to real-world business challenges specific to customer data and showcasing their value through quick wins, organizations can establish CMDM as an ongoing initiative. Celebrating achievements and sharing insights derived from clean, trusted customer data helps maintain momentum and enthusiasm among stakeholders.
Furthermore, CMDM programs related to customer data often involve multi-domain challenges, such as customer relationships, product preferences, and service histories. By mastering one customer data domain at a time and celebrating successes, organizations can expand their CMDM efforts gradually, addressing various aspects of customer interactions. This incremental approach enables businesses to build expertise, tackle specific challenges related to customer data, and continuously demonstrate value to stakeholders.
Any successful CMDM program focused on customer master data necessitates clear and customer-centric objectives, active collaboration between business and IT teams, a deep understanding of underlying customer-centric business challenges, and a well-defined roadmap specific to customer data management.
By following these steps, organizations can steer clear of potential pitfalls, reduce risks, and ensure that CMDM initiatives focused on customer data deliver meaningful and measurable results. Implementation of CMDM in the context of customer master data is not merely a project; itās a continuous journey toward customer data excellence, personalized customer experiences, and sustainable growth in todayās customer-centric business landscape.
This Winter 2023 release of the Pretectum CMDM features some cool new features that customers can take advantage of.
These features range from new additional navigations from the ribbon to an objects relationship map; enhancements to business area data that has these attached to metadata tags; new merge and survivorship capabilities in the Duplicate Record search screens and visualisations around key data quality and duplicate search.
Many businesses today rely heavily on robust software as a service (SaaS) based systems to establish a stable and consistent system of record for various business activities.
Customer Master Data Management (CMDM) are a critical component in the data supply chain for many businesses either through manual data management practices or more systematically with various technologies; concerns about data integrity and security have often held businesses back from pushing their customer data to the cloud due to the opaqueness of the understanding of just how exactly the data is secured.
Establishing a Centralized Data Repository
At the core of an effective CMDM system lies a centralized data repository. This repository acts as a comprehensive storehouse of business-wide customer data, ensuring accessibility and reliability across various functions. Whether itās customer account planning, customer engagement order scheduling or simply informing the business about the customer relationship. Having a single source of truth facilitates better-informed decision-making. A robust CMDM system integrates diverse customer data sets, allowing the business to more easily discern patterns, make predictions, and optimize customer relationships, and process events more seamlessly.
Validation Protocols and Data Accuracy
A key expectation from a SaaS-based CMDM system is the implementation of stringent user, access, and content validation protocols. The data must align with business rules to guarantee accuracy and consistency. By employing machine logic and cross-referencing techniques, discrepancies and redundancies in operational files can be identified and rectified. Users need to have the right levels of access to data and the data needs to be adequately available and accessible to meet business objectives. This validation ensures that everything the business does, operates on appropriate and reliable data, maximizing the potential of the information at hand to meet the business needs.
Data Standardization, Consolidation, and Cleansing
Another crucial aspect is the implementation of a multi-pronged strategy involving data standardization, consolidation, cleansing, and de-duplication. This strategy ensures that data across internal and external systems is not only accurate but also uniform. By promoting data accountability and establishing clear governance rules, businesses create a culture of data integrity. Standardized data sets facilitate efficient communication, enabling different departments to collaborate seamlessly. A CMDM system that actively promotes these practices ensures that businesses have a reliable foundation upon which to build their operations.
Establishing a Culture of Visibility and Transparency
Transparency and visibility are the cornerstones of effective customer data management. A robust CMDM system fosters a culture of transparency by providing quick and easy access to quality data while also informing the data owners and providers of the various characteristics of the data. Zero-party data, for example, data provided by actual customers, holds a higher value than data acquired from third parties. The ability of customers to provide their consent to the use of their data for specific purposes further reinforces the seriousness with which the business respects consumer privacy and data security and integrity.
Data accessibility supports rapid decision-making, enabling the business to respond promptly to risks and opportunities. Cross-functional collaboration through data provisioning facilitates a thriving data culture in an environment where the data is transparent and readily available as appropriate. Plans and decisions, when based on accurate and consistent data, are made with better coordination, leading to enhanced efficiency across the organization.
The Path to Data Intelligence
SaaS-based CMDM systems like the Pretectum CMDM go beyond being a mere data repository. They are a dynamic tool that empowers businesses with accurate, standardized, and transparent customer data.
The minimum expectations for such a system include establishing a centralized data repository, stringent validation protocols, data standardization, consolidation, and cleansing.
They foster a culture of visibility and transparency, which is essential. By meeting these expectations, you business can pave the way for improved data intelligence, ensuring that your decisions are well-informed, agile, and aligned with your strategic objectives.
In such a data-centric landscape, a high-quality CMDM system is not just an asset; it is a necessity, propelling any customer-centred business towards unprecedented heights of efficiency and competitiveness in the global market.
Learn more at https://www.pretectum.com/the-minimum-expectations-of-a-customer-mdm/
Every market has its unique flavor, Japan stands out as a challenge and opportunity in equal measure for global brands seeking to impress a discerning Japanese customer audience. A Japan nuanced approach to branding is not just advisable; itās imperative.
Japan, a nation steeped in rich culture and tradition, possesses a substantial consumer landscape shaped by distinct regional preferences and culturally bound behaviors. Navigating the country requires careful planning and the same is true for the consumer terrain. To be successful you need to do more than just introduce a product you need to have a comprehensive understanding of the Japanese consumer mindset.
The significance of effective regional branding cannot be overstated. Itās not merely about showcasing the product; itās about weaving a narrative that resonates deeply with the Japanese consumer psyche.
A matter of trust
One of the key hurdles faced by international brands in Japan is the inherent distrust that consumers harbor for non-domestic products. Japanese consumers, with their high scores on Hofstedeās Uncertainty Avoidance Index, exhibit a natural aversion to risk, especially when it comes to lesser-known brands. Hence, to gain their trust, a brand must not only offer quality and competitive pricing but also craft a holistic brand experience tailored to local tastes and expectations.
Psychologist Dr. Geert Hofstede published the first edition of the cultural dimensions model at the end of the 1970s. It was based on research of people who worked for IBM in more than 50 countries. Hofstede is recognized as one of the most prominent theorists of the day, with significant influence in the field of intercultural communication, in particular.
Hofstedeās Cultureās Consequences first edition was published in 1980 and translated into 17 languages. At the same time, there was a dramatic increase in the number of studies on culture in business journals, and a total of 500 journals were published in the 1980s, increasing to 1700 publications in the 1990s, and 2200 publications in the 2000s according to Cheryl Nakata, in āBeyond Hofstede: Culture frameworks for global marketing and managementā.
Of note, is the fact that the data was based upon surveys of thousands of respondents from many countries. More than 88,000 employees from 72 countries participated in the survey in 2001. In 2010 a follow-up survey recorded respondents from 93 countries.
While the initial research was IBM-centric, the frameworkās applicability and usefulness led to its adoption in a broader range of research settings. Researchers have adapted the methodology to explore cultural dimensions among different groups of people, making the framework a valuable tool for cross-cultural analysis in diverse contexts.
One could argue that a shortcoming of the studies is that the samples are limited to a specific group of people who could be categorized as coming from a well-educated elite of business people. Such people might be considered atypical in any country.
Nonetheless, the model is an internationally recognized standard for understanding cultural differences.
According to Hofstedeās model, Japan scores high in masculinity, uncertainty avoidance, and long-term orientation compared to other Asian countries. However, Japan scores relatively low in power distance, individualism, and indulgence. Japanās relatively low score in power distance indicates that Japanese people are more likely to question authority and expect equal distribution of power in society.
In the paper āHow Foreigners Experience Japan: Beyond Hofstedeās Modelā Akiko Asai discusses how the experience of foreigners from East Asia in Japan differs from that of other foreigners.
The fundamental message of Asaiās paper is that the experience of foreigners in Japan is not monolithic and cannot be explained by Hofstedeās cultural dimensions alone.
Asai argues that while Hofstedeās model is useful for understanding cultural differences, it has limitations and cannot fully capture the complexity of cross-cultural interactions. The author proposes instead, a more nuanced approach that takes into account factors such as language, ethnicity, and nationality even though at face value one is dealing simply with consumers in the Japanese market.
From all this, we could say that we have some sort of a sense of what factors might influence a brandās positioning in the Japanese market but as with many things, absolutes do not necessarily hold steadfast.
learn more at
https://www.pretectum.com/impressing-a-customer/
Customer Master Data Management matters
Some reasons why you should care
1Reducing business friction ā when you donāt have a customer MDM, every business department is responsible for collecting and maintaining master data ā marketing, sales, service, support, billing and collections.
The result is that the same master data may be collected multiple times, and worse, the exact same data may be maintained by more than one department.
If it is consumer data that may land your business in a non-compliance situation when dealing with GDPR and privacy laws.
A customer MDM defines a clear governance process; this means every aspect of the customer master needs to be collected only once. this reduces the number of collection points for the master data and in turn, can reduce the workload for customer data collection for each department. There is less time collecting and verifying and less time needing to be spent on reconciliation.
2Having a customer MDM will lead to improved customer data quality. One of the main weaknesses in an unstructured, decentralized data management function is that data quality gets compromised.
Every department holds a version of the truth as they see it. This inevitably leads to reconciliation and consolidation problems and can even introduce issues in the transaction processing process for the customer.
Sales sell, but the credit risk department assesses risk and sets credit thresholds. If the two departments are working off different views of the customer because the customer master is out of synch or never gets reconciled then sales may not sell because they suspect that the customer is not current with their payments or they may oversell to a customer who has a poor likelihood of settlement. A unified customer master that both references will give a better view of the customer.
When the Customer MDM is the one single source of truth it will provide all relevant master data and directly deliver all the benefits of superior data quality. Data quality here isnāt only about the correct data but also the customer data that is the most up-to-date.
The best possible customer record and experience for all, is the result.
3When all the customer master data is located centrally, the organization is placed in a better position for compliance and governance assessment. The Customer MDM provides the ability to clearly structure data responsibilities.
This structure tells you who is responsible for definition, creation, amendment, viewing/retrieving, deletion and archiving. Moreover, when the data is found centrally, when there are subject access requests, you only have to go to one place to provide details of what you have and what you know about the customer.
Having the customer MDM as your single source of truth will assist in meeting all the expectations of audit, risk, compliance and the customer themselves. Master data management systems in general represent perfect single-source of truth repositories in that they often provide evidence of origin and sourcing lineage. These exist to support business processes but can also be valuable for compliance reporting. S
4Make better decisions now that you have all your customer data in one place and can have a comprehensive, and complete view of the customer master. Organization-wide decision processes can rely on the latest set of common customer master data which will help operations, executives, managers and marketers make informed, fact-based decisions.
Actually, this is a very important aspect you have to understand. When it comes to decision making, dynamic data is most often in the spotlight. However, as mentioned in my initial statement, master data is actually the powerhouse that drives your dynamic data.
5Automation doesnāt have to be a dirty people-displacing word. In fact, it can be a boon to your business efficiency and effectiveness since data exchanges and data hygiene tasks can be performed automatically.
For most companies, the implementation of a customer MDM will eliminate a lot of highly manual tasks engaged in by multiple participants in the creation and maintenance of customer master data.
You can still collect data in Excel if necessary but as long as those spreadsheets land in the master data system through an automated method, you will still have what you consider a tactically effective mechanism as something complementary to the overall needs that the business
Your centralized, system-based Customer Master Data Management eliminates many operational and logistics issues.
With the Pretectum CMDM, thereās no longer a need for creating and maintaining personal Excel files and isolated databases of customer data. Instead, data governance processes restrict that approach and since people always want the most complete and freshest data, why wouldnāt they go to a system that has all that?
To learn more visit https://www.pretectum.com/customer-master-data-management-matters/
Customer master data attributes are essential pieces of information about your customers that in Pretectum CMDM, are stored in the central repository, referred to as the Pretectum CMDM system. Managing your customer master data effectively is crucial for your organization to enhance its customer relationships, improve your organizational decision-making, and streamline operations and business processes.
Here are what we consider key considerations regarding your customer master data attributes:
Accuracy: Ensure that the data is accurate, up-to-date, and free from errors. Inaccurate information can lead to misunderstandings, poor decision-making, and customer dissatisfaction. The Pretectum CMDM ensures accuracy by centralizing customer data and integrating it from multiple sources. This process includes customer self-service and native integrations to maintain up-to-date and correct information, thereby reducing the risk of using incorrect or outdated data. The system also automates data management tasks, which helps in reducing human error and maintaining a high level of data quality.
Completeness: Capture all relevant customer information required for business processes. Incomplete data may hinder your ability to understand customers fully and provide them with the best possible service. Pretectum CMDM addresses completeness by ensuring that all essential customer data fields are present and accurately filled. It supports the definition of comprehensive data requirements, helps in identifying missing information, and enables reporting on data governance policies and data inconsistencies. This approach maintains a consistently high level of data completeness within your customer data, which is crucial for effective analysis and decision-making.
Consistency: Maintain consistency across all systems and platforms where customer data is stored. Inconsistencies can lead to confusion, duplication of efforts, and inaccuracies in reporting. Pretectum CMDM handles consistency by harmonizing customer data across various channels and platforms. It standardizes data formats, employs master data management practices, and resolves data conflicts efficiently. This ensures that customer data is consistent wherever it is used, which is essential for providing seamless customer experiences and maintaining data integrity across the business.
Uniqueness: Ensure that each customer has a unique identifier or key to prevent duplicates. Duplicate records can cause confusion, lead to errors, and impact the accuracy of analytics. Pretectum CMDM helps with uniqueness by identifying and merging duplicate records to create a single, authoritative view of each customer. It uses sophisticated matching algorithms to detect duplicates and provides tools for data stewards to review and merge records as needed. This ensures that each customer is represented once in the database, eliminating redundancies and improving the accuracy of customer profiles.
Security: Implement robust security measures to protect sensitive customer information. Customer data should be handled with care to comply with privacy regulations and maintain the trust of your customers. Pretectum takes the security of customer data very seriously. The platform employs robust security measures to protect data from unauthorized access and breaches. This includes encryption of sensitive data, implementing access controls, and adhering to industry standards and regulations for data security. Pretectumās commitment to data security ensures that customer information is safeguarded throughout its lifecycle within the CMDM system.
Relevance: Include only the necessary information that is relevant to your business processes. Avoid collecting excessive data that may not be useful and could lead to increased maintenance efforts. Pretectum CMDM ensures the relevance of customer master data by implementing real-time monitoring systems to identify and address data staleness issues promptly. It supports efficient data capture and updating mechanisms, streamlines data processing pipelines, and employs master data management practices to keep customer data current and relevant. This approach helps in avoiding missed opportunities and maintaining the ability to inform about customer data needs effectively.
Entering the world of freelance as a data professional offers freedom, diversity in projects, and the thrill of entrepreneurship. But how does one transition from a traditional job to a successful freelance career in the data field? Insights from an experienced freelance data consultant shed light on this journey. Table Of Contents 1Key Skills and [ā¦]
Competition is fierce and customer choices are abundant, businesses may find solace and success in the art of cultivating meaningful customer relationships.
The art, often referred to as Customer Relationship Management (CRM), has become more than just a marketing strategy; itās the cornerstone upon which businesses thrive and flourish.
Building Bridges Beyond the Transaction
At its essence, CRM isnāt just software; itās a philosophical way of doing business that prioritizes people over profits; the practice of understanding and managing relationships and interactions with customers, with the goal of creating mutual benefits.
CRM extends beyond the initial customer purchase, it focuses on enhancing customer satisfaction, loyalty, and retention. Sustaining a long-term relationship, and maximizing customer lifetime value (CLV).
Something Pretectum tags as being encapsulated in the hashtag #loyaltyisupforgrabs.
In this competitive market, where attracting a new customer is a costly endeavor, CRM shifts the focus to the existing customers. You do this by promptly resolving issues, offering excellent and consistent customer service, and keeping customers updated about products and promotions. Through these activities, businesses can foster loyalty and drive repeat sales.
Retention, Loyalty, and Satisfaction
There is a triad associated with CRM, doing it well offers numerous advantages for businesses. It reputedly costs 5 times more money to acquire a new customer than to get an existing customer to make a purchase!
Firstly, it enhances customer retention rates, ensuring that customers keep returning, thus stabilizing revenue streams.
Secondly, it fortifies customer loyalty, making it difficult for competitors to lure customers away.
Lastly, it amplifies customer satisfaction, a metric vital in the age of digital influence where a dissatisfied customer can tarnish a brandās reputation across mediums like social media platforms.
Good CRM is about Facts and Figures
The impact of CRM on businesses is substantiated by compelling data.
Increasing customer retention by a mere 5% is suggested as having the potential to surge profits by 25% to 95%.
For 73% of customers, the quality of their experience is often the linchpin of their purchasing decisions.
According to Zippia, following a poor customer experience, up to 89% of consumers have switched to a competitor. On average, customers will tell 16 people about a negative experience, while they will only tell 9 people about a positive one
Learning with machines
Artificial Intelligence (AI) is the next step towards a novel and more capable management of customer relationship management, CRM āis the outcome of the continuing evolution and integration of marketing ideas and newly available data, technologies, and organizational formsā (Boulding et al., 2005).
AI algorithms can analyze vast amounts of customer data in real time. By processing this data, an integrated form of AI can identify patterns, trends, and correlations that human analysts might miss.
Predictive analytics powered by AI alongside CRM can forecast customer behavior, helping businesses anticipate needs and preferences. This proactive approach allows for targeted marketing, personalized product recommendations, and strategic decision-making.
Chatbots and virtual assistants are capable of handling routine customer inquiries and tasks 24/7 especially when AI is instrumented. These chatbots are able to engage customers in natural language conversations, answer frequently asked questions, and assist with basic problem-solving. By automating these interactions, businesses can improve response times and enhance customer satisfaction.
Algorithms analyze customer data to create highly personalized experiences. By understanding individual preferences and behaviors, these AI can recommend products or services tailored to the unique characteristics of the customer. Personalized marketing messages and offers significantly improve customer engagement, leading to higher conversion rates and customer loyalty.
AI-powered sentiment analysis tools assess customer sentiments based on their interactions with a company, through emails, social media, or customer service calls. Understanding customer emotions and feedback in real-time allows businesses to respond promptly to negative experiences, mitigating potential issues and preserving customer relationships.
This can also analyze sales patterns and customer interactions to identify high-value leads. The algorithms can score leads based on their likelihood to convert, allowing sales teams to prioritize their efforts effectively. They can also analyze sales conversations, providing insights to improve sales techniques and close rates.
Automating various CRM processes, such as data entry, task assignments, and follow-up reminders. Automation reduces the administrative burden on employees, allowing them to focus on more strategic tasks and meaningful customer interactions.
Detection of unusual patterns or behaviors in customer transactions has long been a quest for all types of organizations, using AI to perform the analysis helps businesses identify potential fraudulent activities. By flagging suspicious activities in real time, businesses can take immediate action to protect both customers and their own interests.
Top Tips for Lasting Connections
Implementing CRM effectively doesnāt have to be daunting. Consider these practical tips to guide your business.
Continuously collect and update customer profiles, and use preferences for personalized recommendations and promotions, especially through the use of a zero or first-party data strategy with a customer master data management system like the Pretectum CMDM at the core.
Focus on quality, ensure your products or services meet the highest standards to prevent dissatisfaction and negative reviews ā drive quality in the customer data too! Pretectumās data quality is integral to the CMDM journey.
Train and empower your staff to provide exceptional customer service, encouraging personalized interactions that make customers feel valued. The best way to do this is to make your CMDM solution central to your various systems in a syndicated or hub-and-spoke deployment.
Maintain regular communication with customers through various channels, fostering a sense of community and excitement. Maintaining top-notch customer contact information is key, getting customers to verify it regularly, can help.
Encourage customer feedback, promptly address issues to show customers their opinions matter, and improve your offerings accordingly. Here you can also add that feedback to the CMDM as a part of your Customer master history.
Implement loyalty programs, discounts, and special merchandise to reward customers, enhancing their sense of belonging.
Greet customers warmly, making them feel acknowledged, and always express gratitude for their patronage. Part of the key here is knowing your customers. How exactly you achieve a certain state of KYC hinges on how far you integrate solutions like CMDM with your other systems like POS and eCommerce.
Explore CMDM systems like Pretectum CMDM, which streamlines processes, manages customer data, provides valuable insights, and facilitates personalized experiences.
In essence, CRM is the heart of a successful business. By investing in relationships, understanding customer needs, and leveraging modern tools, businesses can create a customer-centric ecosystem where loyalty thrives, and profits follow suit. Itās more than just a strategy; itās a commitment to building lasting connections that stand the test of time, ensuring business growth in a competitive world.
Unlock the potential of Customer Master Data Management (CMDM) as it transcends sales and marketing, becoming the orchestrator of a holistic business symphony. CMDM transforms data into a strategic asset, ensuring quality, collaboration, and efficiency across all organizational functions. From eliminating data redundancy to strategic distribution, CMDM strikes a delicate balance between control and accessibility, emerging as the backbone of organizational data strategy for continuous innovation and growth.
A customer-centric business strives to create a positive, consistent, and memorable customer experience at every touchpoint, which leads to customer loyalty, advocacy, and ultimately, business growth.
Customer-centric businesses foster a culture that prioritizes customer satisfaction and values customer feedback with every employee, from top management to frontline staff, understanding the importance of the customer and their role in delivering exceptional experiences. Such businesses invest in gaining a deep understanding of their customers, including customer preferences, pain points, and behaviors. By using data from systems like the Pretectum CMDM accompanied by customer data insights, they are able to segment their customer base and tailor their products, services, and marketing strategies accordingly.
Such a business offers personalized experiences through personal product recommendations, marketing messages, and interactions to make customers feel valued and understood. Customer feedback is actively sought and used for driving continuous improvement through mechanisms like customer complaints and suggestions, addressing issues promptly, and making enhancements to offerings based on customer input.
Walmart founder, Sam Walton succinctly put it, āThereās only one boss; the customer.ā These words reverberate through the hallways of companies that handle consumer data, as they signify the central role customers play in shaping a companyās trajectory. However, itās essential to understand that customers are not just passive entities; they are active partners in the companyās mission.
A seamless and consistent experience across multiple channels, including in-store, online, mobile, social media, and customer support is important in supporting customers in interacting with the business through their preferred channel, and their history and preferences are accessible to employees across all touchpoints. The end goal is the cultivation of long-term relationships where, rather than focusing solely on short-term transactions, customer-centric businesses aim to build long-term relationships with their customers. This requires understanding that customer loyalty and lifetime value are more valuable than one-time sales.
Shep Hyken, a customer service and experience (CX) expert and keynote speaker and CAO (Chief Amazement Officer) designate of Shepard Presentations, a company that helps organizations create an amazing customer-focused culture suggests that āAll of your customers are partners in your mission,ā therein underscoring the point that customer data management is not merely about recording transactions; itās about forging enduring relationships. When customers are seen as partners, the data collected becomes a means to strengthen this partnership, rather than a mere record of transactions.
Such businesses are adaptable and responsive to changing customer preferences and market dynamics. They are willing to pivot their strategies and offerings to meet evolving customer needs and they use metrics and measurements to be customer-centric businesses. They use metrics like Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Customer Lifetime Value (CLV) to measure their success in delivering exceptional customer experiences. These metrics help them to track progress and make data-driven decisions.
Feedback and listening are integral to understanding and meeting customer needs. Actively seek feedback from customers through surveys, social media, and other channels. Demonstrating that you value their opinions and acting on their feedback shows responsiveness and care.
Jeff Bezos, the visionary behind Amazon, recognized that āFocusing on the customer makes a company more resilient.ā This recognition links customer-centricity with a companyās ability to adapt to market disruptions. Effective customer data management builds a loyal and adaptable customer base, a strategic asset that can help companies weather various challenges.
This is more generally only achievable by prioritizing transparency and building trust with customers by being honest about product offerings, policies, and pricing. Trust is considered a foundational element of the customer relationship. These all form part of the customer experience (CX).
Customer experience and employee engagement Stan Phelps is the founder of PurpleGoldfish.com, a think tank of customer experience and employee engagement experts based at the Frontier in Research Triangle Park. Phelps highlights an often-overlooked aspect of customer experience: āCustomer experience isnāt an expense. Managing customer experience bolsters your brand.ā This perspective emphasizes that investing in data management isnāt a financial burden; itās an investment that enhances the brandās reputation and fosters customer …
Customer Relationship Management 101
Competition is fierce and customer choices are abundant, businesses may find solace and success in the art of cultivating meaningful customer relationships.
The art, often referred to as Customer Relationship Management (CRM), has become more than just a marketing strategy; itās the cornerstone upon which businesses thrive and flourish.
Building Bridges Beyond the Transaction
At its essence, CRM isnāt just software; itās a philosophical way of doing business that prioritizes people over profits; the practice of understanding and managing relationships and interactions with customers, with the goal of creating mutual benefits.
CRM extends beyond the initial customer purchase, it focuses on enhancing customer satisfaction, loyalty, and retention. Sustaining a long-term relationship, and maximizing customer lifetime value (CLV).
Something Pretectum tags as being encapsulated in the hashtag #loyaltyisupforgrabs.
In this competitive market, where attracting a new customer is a costly endeavor, CRM shifts the focus to the existing customers. You do this by promptly resolving issues, offering excellent and consistent customer service, and keeping customers updated about products and promotions. Through these activities, businesses can foster loyalty and drive repeat sales.
Retention, Loyalty, and Satisfaction
There is a triad associated with CRM, doing it well offers numerous advantages for businesses. It reputedly costs 5 times more money to acquire a new customer than to get an existing customer to make a purchase!
Firstly, it enhances customer retention rates, ensuring that customers keep returning, thus stabilizing revenue streams.
Secondly, it fortifies customer loyalty, making it difficult for competitors to lure customers away.
Lastly, it amplifies customer satisfaction, a metric vital in the age of digital influence where a dissatisfied customer can tarnish a brandās reputation across mediums like social media platforms.
Good CRM is about Facts and Figures
The impact of CRM on businesses is substantiated by compelling data.
Increasing customer retention by a mere 5% is suggested as having the potential to surge profits by 25% to 95%.
For 73% of customers, the quality of their experience is often the linchpin of their purchasing decisions.
According to Zippia, following a poor customer experience, up to 89% of consumers have switched to a competitor. On average, customers will tell 16 people about a negative experience, while they will only tell 9 people about a positive one
Learning with machines
Artificial Intelligence (AI) is the next step towards a novel and more capable management of customer relationship management, CRM āis the outcome of the continuing evolution and integration of marketing ideas and newly available data, technologies, and organizational formsā (Boulding et al., 2005).
AI algorithms can analyze vast amounts of customer data in real time. By processing this data, an integrated form of AI can identify patterns, trends, and correlations that human analysts might miss.
Predictive analytics powered by AI alongside CRM can forecast customer behavior, helping businesses anticipate needs and preferences. This proactive approach allows for targeted marketing, personalized product recommendations, and strategic decision-making.
Chatbots and virtual assistants are capable of handling routine customer inquiries and tasks 24/7 especially when AI is instrumented. These chatbots are able to engage customers in natural language conversations, answer frequently asked questions, and assist with basic problem-solving. By automating these interactions, businesses can improve response times and enhance customer satisfaction.
Algorithms analyze customer data to create highly personalized experiences. By understanding individual preferences and behaviors, these AI can recommend products or services tailored to the unique characteristics of the customer. Personalized marketing messages and offers significantly improve customer engagement, leading to higher conversion rates and customer loyalty.
read more at https://www.pretectum.com/customer-relationship-management-101/
In the complex landscape of enterprise-level Master Data Management (MDM) implementation, several critical challenges often obstruct the path to success.
learn more by visiting: https://www.pretectum.com/avoiding-pitfalls-in-mdm-implementation/
