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.
“Thick data” 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 “big data,” 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.
“Thin data” 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. It’s essential to consider the quality, relevance, and depth of data when making decisions or drawing conclusions based on thin data.
It’s 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 “breathe life” 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 customer’s 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/
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.
Mintel’s 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.
Capgemini’s “What matters to today’s consumer” survey of 10,000 people, in 10 countries just one vital question “What matters to you?” 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.
Qualtrics’ 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 – 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.
learn more by visiting
https://www.pretectum.com/is-your-business-powered-by-customer-data/
You might have more recently heard of “composable” 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 2010’s 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. It’s 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 platform’s 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 CMDM’s 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
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 don’t say they have no plans to start, that’s according to a 2020 O’Reilly 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 companies’ 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/
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 it’s 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/
Customer Master Data Management matters
Some reasons why you should care
1Reducing business friction – when you don’t have a customer MDM, every business department is responsible for collecting and maintaining master data – 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 isn’t 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 doesn’t 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, there’s 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 wouldn’t they go to a system that has all that?
To learn more visit https://www.pretectum.com/customer-master-data-management-matters/
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; it’s 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. It’s not merely about showcasing the product; it’s 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 Hofstede’s 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.
Hofstede’s Culture’s 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 “Beyond Hofstede: Culture frameworks for global marketing and management“.
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 framework’s 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 Hofstede’s 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. Japan’s 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 “How Foreigners Experience Japan: Beyond Hofstede’s Model” Akiko Asai discusses how the experience of foreigners from East Asia in Japan differs from that of other foreigners.
The fundamental message of Asai’s paper is that the experience of foreigners in Japan is not monolithic and cannot be explained by Hofstede’s cultural dimensions alone.
Asai argues that while Hofstede’s 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 brand’s 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 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. Pretectum’s 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.
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.
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/
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; it’s the cornerstone upon which businesses thrive and flourish.
Building Bridges Beyond the Transaction
At its essence, CRM isn’t just software; it’s 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 brand’s 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 “is the outcome of the continuing evolution and integration of marketing ideas and newly available data, technologies, and organizational forms” (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/
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, “There’s only one boss; the customer.” These words reverberate through the hallways of companies that handle consumer data, as they signify the central role customers play in shaping a company’s trajectory. However, it’s essential to understand that customers are not just passive entities; they are active partners in the company’s 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 “All of your customers are partners in your mission,” therein underscoring the point that customer data management is not merely about recording transactions; it’s 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 “Focusing on the customer makes a company more resilient.” This recognition links customer-centricity with a company’s 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: “Customer experience isn’t an expense. Managing customer experience bolsters your brand.” This perspective emphasizes that investing in data management isn’t a financial burden; it’s an investment that enhances the brand’s reputation and fosters customer …
The future, a realm of infinite possibilities and uncertainties, remains an enigma that continuously eludes our grasp.
Technological advancements and societal shifts drive unprecedented change, businesses must grapple with the challenge of predicting and adapting to evolving customer expectations.
In such a dynamic landscape, the concept of holding the “universal remote” to customer master data emerges as a beacon of preparedness, offering enterprises a strategic advantage to not only survive but thrive amidst uncertainty.
“We do not know what the future holds, but if you hold the universal remote to your customer master data, you’d be best prepared and ready to meet your customers’ expectations when it changes again.”
The cornerstone of any successful business venture is a deep understanding of customer expectations. However, these expectations are far from static; they morph almost continuously in response to technological innovations, societal transformations, and evolving market trends. Factoring in shifting customer preferences and the factors influencing them is paramount to staying ahead in an ever-changing marketplace.
Technological advancements have emerged as a driving force behind the evolution of customer expectations. The omnipresence of digital interfaces, coupled with the rapid integration of artificial intelligence and data analytics, has fundamentally altered the way customers engage with businesses. Taking notice of how these technological shifts shape consumer behaviour and the imperative for businesses to leverage data mastery in harnessing these changes is essential.
Customer Data, sometimes dubbed a part of the “new oil” of the digital age, holds the key to deciphering emerging trends and predicting future customer demand. However, the sheer volume of data is overwhelming. Herein lies the significance of data mastery—navigating, interpreting, and harnessing data to gain actionable insights. Being able to gather, analyse and dissect the data into the techniques and strategies to achieve mastery is pivotal for businesses aiming to wield that universal remote effectively.
Ancient Greek philosopher Heraclitus observed that the natural world was in a constant state of movement, along with that, people age, develop habits and move environments. You can’t step into the same river twice — even rocks are subject to change by the impacting elements around them, with the passage of time.
Uncertainty is the bedrock of the future, and businesses that acknowledge this reality are better positioned to navigate the storm. The ability to pivot, realign strategies, and recalibrate offerings in response to unforeseen shifts in customer expectations is essential to research as a hallmark of resilience.
Agility has become synonymous with survival in our volatile business landscape. An analysis of agile methodologies, which emphasize iterative development, cross-functional collaboration, and customer feedback, showcases how such approaches empower companies to remain adaptive and responsive in an era of constant change.
The universal remote to data mastery encompasses not only the data a company generates but also the feedback it receives from customers. The significance of robust feedback loops in refining products, services, and customer experiences is underscored, illustrating how an organization’s willingness to listen can foster customer loyalty amid evolving expectations.
As businesses amass vast reservoirs of customer data, ethical concerns surrounding its collection, storage, and usage come to the forefront. Exploring the ethical nuances of data utilization—balancing personalization with privacy—sheds light on the ethical responsibilities that accompany the power of universal data mastery.
The age of mass production has resulted in an era of necessary hyper-personalization, in order to differentiate, where customers expect tailored experiences that resonate with their unique preferences. The role of universal data mastery in deciphering individual behaviours and crafting personalized offerings is laid bare as a means to meet these escalating expectations.
Future-proofing your business involves an amalgamation of visionary thinking and pragmatic planning. Delving into strategic approaches such as scenario planning, trend analysis, and innovation incubation underscores the proactive stance your business must adopt to anticipate customer expectations before they materialize.
The notion of the solitary business is interesting but unrealistic, few can argue against the fact that a lot of what exists, existed before, in some form or another. The trick is in evolving into a business of interconnectedness with the customer.
Each client is important, but some lay the foundation and keep you afloat.
They exist at the core of your business – sometimes they are responsible for most of your revenue; in other cases, a valuable customer that stays with you is more important than bringing tens of new ones.
How to identify them and use the knowledge of their lifecycle to repeat that success? The answer is measuring CLV – an incredibly important metric in every marketeer’s book. What is customer lifetime value? Read on to find out.
CLV meaning is, relatively speaking, how much a customer is worth to your business. When the client first receives any information about your business, service, or ware and decides to check it out, their lifetime value begins to accumulate. It sums up the amount of revenue a customer has brought to you, creating a clear picture of the dynamic between your company and them.
A customer lifetime value (CLV) is one of the most important metrics in marketing, outlining the total value a company is expected to reap from a customer relationship. But how can a marketer determine a customer’s lifetime value? And what modelling provides the best outcome? Rokas Salasevicius and Justas Jankunas from management consultancy CIVITTA shed light on the topic.
While there are different definitions of customer lifetime value, at CIVITTA we follow the following definition: “Customer lifetime value is a concept which estimates how much money the customer is going to bring to a company in the long run.”
Calculating and tracking customer lifetime value is of huge importance for marketers, for a number of reasons. First, it enables marketers to observe the business – CLV is used as one of the KPIs that provide information about the health of the business and customer base. CLV allows understanding how strong the current customer base is and track how it is changing over time, as well as identify reasons why it is changing.
Sales reps need to wear many hats and have a lot to juggle during a working day. With so many demands on reps today and having to navigate long B2B sales cycles, a tool that can help sellers along the way is welcomed.
Sales enablement and using enablement technology is becoming increasingly important for B2B organizations. According to research released by McKinsey & Company, “roughly two in three buyers prefer remote human interaction or digital self-service.
But if you are using an enablement platform now, or are considering it, have you done an ROI calculation to quantify how much time and money you could save by having one?
As a consumer, you’ve probably encountered this sort of question dozens of times—after an online purchase, at the end of a customer service interaction, or even after a hospital stay.
If you work at one of the thousands of companies that ask this question of their customers, you’re familiar with the Net Promoter System (NPS), which Reichheld invented and first wrote about in HBR almost 20 years ago. (See “The One Number You Need to Grow,” December 2003.)
NPS has spread rapidly around the world. It has become the predominant customer success framework—used today by two-thirds of the Fortune 1000. Why has it been embraced so enthusiastically?
Because it solves a vital challenge that our financial systems fail to address.
Financials can easily tell us when we have extracted $1 million from our customers’ wallets, but they can’t tell us when our work has improved customers’ lives.
Lifetime value (LTV) is a significant metric that helps estimate the growth of a company.
By comparing LTV to customer acquisition cost, the results can help make crucial decisions. This might include devising your advertising and marketing budget, for example.
Businesses can use LTV to acquire and retain high-profile customers.
This means more income, thus scaling. But, if customer acquisition costs are higher than LTV, scaling is impossible.
For you to predict and improve customer lifetime value successfully, you’ll need to know how to measure customer lifetime value.
Companies have employed digital analytics, advertising and marketing solutions to track customers and connect their behaviors across touch points.
This enabled the creation of data profiles, which have been leveraged to deliver personalized experiences that resonate through relevance and context.
Now, however, this practice of profiling and identifying customers is increasingly coming under scrutiny.
Regulators are adopting new data and consumer privacy legislation, most recently seen with the Colorado Privacy Act. Moreover, Apple’s privacy implementations in iOS 14.8 and iOS 15 have been adopted by an estimated 96% of users, who have opted to stop apps from tracking their activity for ad targeting.
HPE has confirmed that a “limited subset” of customer data was taken in a data breach involving its subsidiary Aruba Networks, a maker of networking equipment.
The enterprise technology giant said in a statement that an unauthorized person used a private key to gain access to customer data stored in its Aruba Central cloud. HPE did not say how the hacker obtained the private key, but said the key allowed access to cloud servers in multiple regions where customer data was stored.
HPE bought Aruba Networks in 2015 for $3 billion in cash. Aruba provides networking gear, like wireless access points, and network security for companies. Through its dashboard, Aruba Central, companies can centrally monitor and manage their Wi-Fi networks.
According to a statement, the hacker first used the key on October 9, but HPE did not detect the intrusion until November 2. HPE automatically purges data from its cloud servers every 30 days, so the amount of compromised data was limited to records dating back to September 10.
If machines are generating things, they’ll generate things in the same form every time, so we should have a much easier time understanding and combining data from myriad sources.
The precedents for standardization fueled by automation were in the classical Industrial Revolution, where there was an incentive for all parties to standardize on shared resources like transportation and shipping as well as on product specifications.
It seemed like that same set of principles should hold true for the new Industrial Revolution of Data as well, and economics and other forces would drive standardization of data. That has not happened at all….
Who is to blame and why, and what could they do about it?
When most people think of personal health data, they think about their medical records.
These reside — usually unconnected — in the offices of primary care physicians and specialists, in imaging companies, hospitals, and elsewhere.
These records contain information such as vital signs, prescriptions and allergies, illnesses and injuries, physicians’ notes, and more.
But health data represent so much more than that, since most “health” happens outside of medical care settings.
It includes your personal circumstances, the choices you make, and the things you do.
This includes information from apps that log your workouts. It’s information from your past, like trauma or adverse childhood events. It’s information about where you live, what you eat and drink, your education, salary, emotional and social history, and other things, all combining to provide the whole picture of your health.
With health data scattered across each facility and provider you’ve ever visited and across each app and wearable you’ve ever used, it’s impossible to see the full picture. But that is something that should be available to everyone.
