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Mar 11 2024
The Customer Master Data Management Top 10 for 2024

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, it’s 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 today’s 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 customer’s 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 customers’ 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 organization’s 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 today’s 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.

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Sep 24 2023
The Rise and Importance of Identity Verification

Establishing and Verifying Identity in a modern and more connected world

In the expansion of our digital world, the management of identities has become a critical concern. Personally, for individuals, and more holistically for organizations in many sectors, including finance, healthcare, e-commerce, and government.

The proliferation of online services and the constant threat of cyberattacks and identity theft have underscored the importance of robust identity verification systems.

Digital Transformation and Identity Management

A more digital society has brought numerous conveniences, enabling the individual, to access services, conduct transactions, and communicate seamlessly across the globe. This digital evolution has also given rise to new challenges, primarily in the realm of identity management and verification.

The many online services have created a demand for efficient and secure identity verification systems. People now perform a myriad of activities online, from shopping and banking to social networking and e-health consultation.

As more personal information is stored online, bad actors and cybercriminals have increasingly targeted individuals’ identities for malicious purposes. Identity theft and fraud pose significant threats to both the individual and the many organizations that they potentially engage with.

Governments and regulatory bodies have recognized the importance of safeguarding personal information. Regulations like the General Data Protection Regulation (GDPR) and Know Your Customer (KYC) requirements in the financial and health sector emphasize the need for robust identity verification.

Users expect seamless and user-friendly experiences when interacting with online services and the cumbersome identity verification processes and systems of yesteryear can lead to user frustration and disengagement.

The rise of digital identity and IVS

Identity verification systems (IVS) have emerged as a vital component of modern digital ecosystems. They play a pivotal role in confirming the identity of individuals, enabling secure access to online services, and mitigating the risk of identity-related fraud.

IVS plays a crucial role in various sectors, including finance, healthcare, e-commerce, and government, to ensure that users are who they claim to be, enhance security, and comply with regulatory requirements.

For the public, organizations that rely on establishing a strong identity verification process foster increased trust between the user and the service providers. Users are more likely to engage with services they trust, leading to increased customer retention and loyalty.

Efficiency in the identity verification process also streamlines onboarding processes and reduces the need for manual verification, lowering operational costs for organizations.

Verified identities also provide improved opportunities for personalized experiences and recommendations, enhancing user engagement and satisfaction.

E-government (short for electronic government) is the use of technological communications devices, such as computers and the Internet, to provide public services to citizens and other persons in a country or region. E-government offers new opportunities for more direct and convenient citizen access to government and for government provision of services directly to citizens. Effective E-government is more easily achieved through the establishment of IVS.

His Majesty’s Revenue and Customs (HMRC) is the tax authority in the United Kingdom. HMRC uses a digital identity verification system to ensure secure access to its online services. Similarly, the US IRS (Internal Revenue Service) is the tax authority in the United States. It has implemented various digital identity verification systems to protect taxpayers’ information and prevent fraud.

Singpass is Singapore’s national digital identity system. It provides residents with a trusted digital identity for secure transactions with over 2,700 services offered by more than 800 government agencies and businesses. The Singpass National Digital Identity (NDI) scheme allows residents to seamlessly access government services and third-party apps, such as banks, colleges, professional bodies, and insurance companies.

Estonia has built one of the world’s leading e-governments with a robust digital identity verification system. Estonia’s digital public infrastructure delivers automated and reusable government services in a human-centric, secure, and private way. The country has made its building blocks open-source, available as global digital public goods for others to use. Estonia’s digital services have played a crucial role during the COVID-19 pandemic, enabling citizens to access services online without the need for physical presence

ID.me offers a US-based identity proofing and group affiliation verification that also meets the federal standards for consumer authentication. NIST 800-63-3 IAL2 and AAL2 conformant and EPCS standards, amongst others.

ID.me’s digital wallet and identity verification service simplifies how over 112M individuals discover and access benefits and services through a single login and verified identity from over 600 partners. It provides users with a trusted digital ID card to access government services and benefits. or example, you can use your verified digital ID card to manage your IRS online account, access Social Security Administration benefits and services, manage unemployment benefits and services from various state departments of labor. ID.me also offers discounts and cashback from over 5,000 stores. ID.me also provides an Rx Card that can help you save up to $95 per prescription at participating pharmacies.

ID.me’s simplicity is that it reaches out to consumers to promote the simplicity of proving their identity online, as well as helping businesses provide marketing promotions and bonuses to verified eligible users. Under the hood, it checks to see whether the customer belongs to an eligible group and triggers an invitation to the promotion. The ID.me mission statement stresses “No Identity Left Behind” promising to enable this functionality to everyone, regardless of background or banked status.

Identity Verification Approaches

The establishment and verification of identity are multifaceted processes that require careful consideration of various factors. Several approaches and technologies are employed to verify identities effectively.

In some instances the eGovernment services provide a means of identity verification that a business can leverage however these services may not be available or authorized for commercial use.

Biometrics for identity verification uses physiological characteristics to identify individuals. Biometric features may include facial recognition, fingerprints, iris or retina scans, voice recognition, hand geometry, or even behavioral traits such as typing patterns or walking gait. Such features are captured by sensors and compared with pre-existing biometric data stored in a database to confirm or deny the identity of the person. Biometric authentication systems are increasingly popular in areas such as banking, security, and mobile devices since they are considered to be more secure than traditional methods of identification, such as passwords or personal identification numbers (PINs), they are much harder to forge or steal.

Document scanning of ID documents such as passports or driver’s licenses for identity verification is a common practice in various contexts. Organizations and agencies may use ID scanning to take electronic copies of documents that prove your identity, such as driver’s licenses. ID scanning can help verify the authenticity of government-issued identifications and streamline identity verification processes.

Knowledge-Based Authentication (KBA) is an authentication method that verifies user identity by asking specific security questions. When setting up a new account, users are often required to create a password and choose security questions and answers, such as “What is your mother’s maiden name?”. During login or other actions, users are prompted to answer these security questions based on personal information. KBA can be categorized into two types: Static Knowledge-Based Authentication (SKBA) and Dynamic Knowledge-Based Authentication (DKBA).

Static Knowledge-Based Authentication requires users to provide answers to one or more security questions during account creation. The answers can be accurate or made up, as long as the user remembers them when prompted later. Enterprises need to be cautious when selecting the type and number of questions to avoid being intrusive or excessive.

Dynamic Knowledge-Based Authentication (DKBA) provides a higher level of security but is used less frequently. It relies on information collected from different data sources to generate real-time questions. For example, a user may be asked, “Which of the following companies did you not work for?” and presented with a list of former employers and one incorrect answer.

While KBA is still widely used, it has certain limitations. Personal information used for KBA can often be discovered or stolen through research, phishing, social engineering, or data breaches. People also freely share the same information on social media sites, reducing its security value. Passwords can be shared, stolen, or cracked using password-cracking tools. To enhance security, enterprises relying on KBA should reinforce it with more secure methods like MFA (Multi-Factor Authentication).

SMS or Email Codes are increasingly popular for identity verification, wherein users receive a one-time code via SMS or email, which they must enter to complete the verification process. These are extensions to older, but still popular methods like tokens; where physical devices or mobile device software generates time-based or event-based codes for authentication.

Contemporary blockchain technology offers a decentralized and tamper-resistant approach to identity verification, allowing users to control their identity data securely.

Challenges in Identity Verification

Biometric data, such as fingerprints or facial scans, is highly personal and sensitive. If not adequately protected, it can be vulnerable to data breaches or unauthorized access. Further, storing biometric data in centralized databases can create a single point of failure and increase the risk of identity theft or misuse.

Organizations must comply with local, regional, and national data protection regulations when collecting, storing, and processing biometric and other personal data. There needs to be proper consent, secure storage, and appropriate retention periods for identity and other personally identifiable information.

Biometric systems may have false acceptance or false rejection rates, leading to incorrect identification or denial of access. Factors such as changes in physical appearance, injuries, or aging can affect the accuracy of biometric matching. Denial of service or access can prove challenging under such circumstances. Compromised credentials and stolen devices present the same risks. Some of these approaches may also not work equally well for everyone. Factors such as skin color, gender, age, or disabilities can impact the accuracy and inclusivity of biometric identification systems, for example. Biases in training data or algorithms can also result in discriminatory outcomes.

Ultimately, users should have control over their biometric and other data and be able to provide informed consent for its collection and use. Organizations should be transparent about how individuals’ data is used and allow them to opt-out if desired.

IVS Market offerings

Identity verification systems have risen to prominence due to the digital transformation and the growing importance of securing personal information in the digital age. These systems provide enhanced security, regulatory compliance, improved user trust, and operational efficiencies. Various approaches, including biometric authentication, document verification, and blockchain-based solutions, are employed to establish and verify identity.

Customer Master Data Management (CMDM) primarily revolves around managing and maintaining customer data within the organization. Its core purpose is to create a unified and accurate view of customer information, ensuring consistency and reliability across various systems and departments. The Pretectum CMDM achieves this through data integration, quality management, governance practices, and consolidation efforts. Its use cases span a wide spectrum, from improving customer relationship management to enhancing data analytics and supporting marketing campaigns, sales, and customer service. Customer MDM aggregates customer data from diverse sources within your organization, amongst them, CRM, ERP. CDP, marketing and sales systems, and databases.

In contrast, IVS is tailored specifically for the critical task of verifying the identity of individuals accessing online services or systems. Its primary objective is to confirm that the person claiming to be a customer is indeed who they claim to be. IVS accomplishes this through a range of methods. IVS finds applications in online services, financial institutions, government agencies, and any organization that requires secure user authentication. Its role is to prevent fraud, secure access to sensitive data, and adhere to regulatory mandates such as Know Your Customer (KYC) requirements. IVS primarily relies on data provided by users during the verification process, including biometric data, scanned identification documents, or responses to security questions.

When comparing CMDM and IVS, several distinctions and intersections emerge. CMDM is more encompassing in scope, addressing all facets of customer data management, including data quality, integration, and governance. IVS, conversely, maintains a narrower focus on identity verification. Both CMDM and IVS contribute to regulatory compliance, with CMDM ensuring data accuracy and consistency, which is vital for adhering to data protection regulations, while IVS plays a pivotal role in identity verification and KYC compliance.

In essence, CMDM and IVS are complementary elements in the digital ecosystem. CMDM like the Pretectum Customer MDM aids in maintaining data accuracy and providing a holistic view of customer data for internal purposes within an organization, while IVS specializes in the crucial task of verifying the identity of users for the sake of security and controlled access. Both are indispensable for ensuring data accuracy, safeguarding digital interactions, and aligning with regulatory requirements. While their scopes and functions differ, they work in tandem to support trustworthy and efficient digital operations in an increasingly connected world.

Organizations must navigate the many challenges related to privacy, user experience, false positives/negatives, scalability, regulatory compliance, and continuous monitoring by appropriately selecting technologies and practices aligned with their specific operational needs.

By adopting appropriate identity verification and data management approaches, organizations can build trust with their users, enhance security, and deliver seamless digital experiences in an increasingly interconnected world. The adoption of appropriate customer master data management and identity verification systems can shape the way customers interact with organizations for their joint success and confidence in dealing with one another in the years to come.

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Aug 19 2023
Data Privacy Acts from around the world

Since the introduction of GDPR, there has been a broadening and legislated clarification of data privacy and protection measures across the globe. If you store or manage customer data in your systems you should be familiar with the expectations around how and what you handle.

General Data Protection Regulation (GDPR)
The GDPR is a comprehensive data protection regulation in the European Union (EU) that sets strict standards for the collection, processing, and protection of personal data of EU residents. It applies to businesses operating within the EU and those outside the EU that process the data of EU residents.

California Consumer Privacy Act (CCPA)
The CCPA is a privacy law in California, USA, that grants consumers certain rights over their personal information. It requires businesses that collect and process the personal data of California residents to provide transparency, control, and security for that data.

Personal Information Protection and Electronic Documents Act (PIPEDA)
PIPEDA is Canada’s federal privacy law that governs how private sector organizations handle personal information. It applies to the collection, use, and disclosure of personal data in commercial activities.

Health Insurance Portability and Accountability Act (HIPAA)
HIPAA is a US federal law that focuses on the privacy and security of medical information. It mandates safeguards to protect patients’ medical records and other health-related information.

Personal Data Protection Act (PDPA)
Singapore’s PDPA regulates the collection, use, and disclosure of personal data by organizations. It aims to balance individuals’ right to privacy with the need for organizations to collect and use data for legitimate purposes.

Privacy Act of 1974 (USA)
This US federal law governs the collection, use, and disclosure of personal information by federal agencies. It provides individuals with certain rights regarding access to and correction of their records.

Australian Privacy Principles (APPs)
The APPs are a set of privacy principles under the Privacy Act 1988 in Australia. They regulate the handling of personal information by Australian government agencies and businesses.

Personal Information Protection Law (PIPL)
China’s PIPL is a comprehensive privacy law that focuses on the protection of personal data. It includes provisions for data processing, cross-border transfers, and individual rights.

Data Protection Act 2018 (DPA 2018)
The UK’s DPA 2018 supplements the GDPR and provides specific provisions for how data protection is implemented in the UK after its departure from the EU.

Kenya Data Protection Act (2019)
Kenya’s data protection law governs the processing of personal data in Kenya. It outlines data protection principles, individual rights, and obligations for data controllers and processors.

Personal Data Protection Law (PDPL)
The PDPL is South Korea’s data protection law that aims to protect personal data while enabling its effective use. It regulates data processing by both private and public entities.

Brazilian General Data Protection Law (LGPD)
LGPD is Brazil’s comprehensive data protection law that governs the processing of personal data. It provides guidelines for collecting, using, and transferring data while respecting individuals’ rights.

Find out how Pretectum CMDM can be of assistance in ensuring you keep your consumer data compliant.

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Jul 12 2023
The Significance of Consumer Data Verification, Consent Management, and Privacy Regulations: Safeguarding Consumer Privacy in the Digital Era

Consumer data has become a valuable asset for digitally-minded businesses across the globe. Companies are able to collect and analyze vast amounts of data in the pursuit of a better understanding of consumers and their behavior.

Through consumer insights, businesses are able to better tailor their products and services, and personalize marketing efforts. However, with the increasing concerns surrounding privacy and data protection, consumer data verification and obtaining explicit consent have emerged as crucial elements in maintaining consumer trust and complying with privacy regulations.

Pretectum, feel that managing your customer data with verification and consent is equally important and here they try to explore the concept of consumer data verification, highlight the importance of consumer consent, and examine the significance of consent management in relation to consumer privacy and global privacy acts.

Consumer Data Verification: Ensuring Accuracy and Authenticity

Consumer data verification refers to the process of confirming the accuracy, reliability, and authenticity of consumer information collected by businesses.

With the abundance of data often already in place or available for collection, ensuring its quality and veracity is critical. Data verification involves various techniques such as cross-referencing information with trusted sources, validating identities, and detecting fraudulent or misleading data. By verifying consumer data, businesses can enhance the quality of their databases, improve decision-making processes, and mitigate potential risks associated with incorrect or unreliable information.

Global Privacy Acts and Consent

Privacy acts around the world, such as the GDPR and CCPA, have significantly influenced data protection practices and highlighted the importance of consumer consent.

These acts set a precedent for privacy regulations worldwide, emphasizing the need for businesses to obtain explicit consent and respect consumer rights.

Implementing consent management not only ensures compliance with these regulations but also reflects an organization’s commitment to respecting privacy and building consumer trust.

The Importance of Consumer Consent

While data verification ensures the accuracy of consumer information, obtaining consumer consent is equally vital. Consumer consent refers to the explicit permission granted by individuals for businesses to collect, store, process, and use their personal data for specific purposes.

Consent is the cornerstone of data protection and privacy regulations, as it empowers individuals with control over their personal information. It ensures that businesses operate transparently and responsibly, respecting consumer privacy rights.

Consumer Consent and Privacy Regulations

In recent years, privacy regulations such as the General Data Protection Regulation (GDPR) in the European Union and the California Consumer Privacy Act (CCPA) have been enacted to safeguard consumer privacy and provide individuals with greater control over their data.

These regulations emphasize the importance of obtaining informed consent from consumers before collecting and processing their personal information. Consent must be freely given, specific, and unambiguous, enabling individuals to make informed decisions about their data.

An example of Data Verification within the Pretectum CMDM

The Role of Consent Management

While many data-gathering solutions and systems overlook consent management, its inclusion is an important aspect for businesses to ensure compliance and strengthen consumer trust.

Consent management encompasses the processes and mechanisms through which businesses obtain, document, and manage consumer consent. It involves obtaining consent in a clear and concise manner, providing individuals with meaningful choices, and enabling them to withdraw or modify their consent easily.

By implementing robust consent management practices, like those offered by the Pretectum CMDM, businesses can demonstrate accountability, foster transparency, and build long-term relationships with consumers.

Verification requests can be batched or on demand for specific records

The Impact on Consumer Master Data

Consumer master data refers to the comprehensive and accurate information about individuals that businesses possess. When consent management is incorporated into consumer data gathering, it transforms the value and significance of consumer master data.

With verified and consented data, businesses can confidently engage with consumers, deliver personalized experiences, and create targeted marketing campaigns that resonate with individuals’ preferences and interests.

Moreover, businesses can proactively manage data breaches, comply with privacy regulations, and establish a reputation for responsible data handling.

Consumer data verification and obtaining consent are integral components of ethical data practices in the modern business landscape.

By verifying data for accuracy and authenticity, businesses can enhance the reliability of their databases.

Simultaneously, obtaining consumer consent is crucial for ensuring transparency, respecting privacy rights, and complying with privacy regulations. Consent Management like that offered by the Pretectum CMDM serves as a vital tool for businesses, enabling them to establish trust, foster transparency, and leverage accurate and consented consumer master data.

As privacy regulations continue to evolve globally, organizations must prioritize consumer consent and embrace robust consent management practices to safeguard consumer privacy and maintain a competitive edge.

Uli LOKSHIN 0 Comments
Oct 15 2022
Meeting customer expectations on the road

Japan’s third-largest car manufacturer is Nissan and they are currently improving their operation practices as they aim for better sales output and of course brand awareness.

Nissan is considered an example of one a European car brand that is notable and successful. Founded in 1933 by Engineer Kenjiro Den, Nissan initially produced just motorcycle engines before branching out into automobile production in 1934.

For more than 80 years Nissan has built cars in Japan and in developing markets around Europe (and beyond) selling more than 4M units annually under the Nissan brand – including well-known models like the Nissan Leaf and Nissan X-Trail SUVs.

Nissan is also the owner of the premium Infiniti brand and the heritage brand Datsun which it discontinued on April 22. In addition to cars and trucks, it has in-house performance tuning products and cars labelled Nismo

It is a tough job, focusing on the environment, vehicle and product quality and customer loyalty. The approach has to be multi-pronged and is driven by data.

In the late 1990s, Nissan was Europe’s best-selling Asian car brand thanks to the Micra, Almera and Primera, which were the epitome of Japanese cars in that period “not very exciting, but extremely reliable”.

By the early noughties, Nissan tried to bring more frivolous design into their cars with the 2002 Micra K12 and 2002 Primera P12, and as a result, the once faithful customers looking for anonymous transportation stayed away.

Nissan recently referenced a project whose plan is anchored on providing improved consumer service. The new program aimed to make Nissan dealerships a strong competition to outside repair facilities. This is important because once the manufacturer warranty expires, car owners more often than not approach independent repair facilities.

A data Project

Some years earlier, Nissan’s Valérie Clert and CGI’s Christophe Jeandidier presented some important insights on customer master data to an Informatica World conference audience.

The results that Nissan harvested from taking a good hard look at their data suggested that for marketing organizations at least, they could see improved campaign conversion rates using a “preferred channels” approach. This would in turn lead to 1.5 to 2.5-factor increases in campaign effectiveness. How did they do it? Implementing more rigour around customer master data management.

According to technofunc, the top players in the automotive industry globally, are Toyota, General Motors, Volkswagen, Hyundai, Ford, and Honda. Nissan isn’t in that top 6, yet today in Europe Nissan places as No5 according to WheelsInquirer.

The automotive industry is quite competitive at the brand level.

Although dealerships possess some of the localized market power, the retail market in general is still quite competitive. Demand is relatively elastic because consumers have different dealerships and cars to choose from but more importantly, the brands that they chase have different appeals according to brand recognition and perceived status, understood utility, styling and other factors.

Customer loyalty and rewards

As can be seen, the perception vs. the reality also varied depending on regional market differences. Although Nissan has dealerships all over the world the desire is to make the Nissan experience even more fulfilling for customers, hence the launch of a special loyalty program – Nissan: One to One Rewards – Customers earn points for spending money on vehicles, parts and services. Buying a vehicle provides a $250 discount for the next vehicle purchase Enrolled members in the Nissan loyalty program are also eligible for a physical loyalty card.

Every industry has its own challenges and the automotive industry is no different.

In an interview with Hervé Moulin: Alliance Project Leader – Telematics in Finished Vehicle Logistics and Transport Means Specialist in Alliance Logistics Europe – Vehicle Operations, Moulin suggested there would be major challenges in future years.

“Customers are now changing their behaviour – they are more reliant on the internet and prefer car sharing than going somewhere themselves. Customers now prefer staying in large cities, where they must, understandably, share their transport capabilities. Also, local authorities don’t want traditional freight deliveries anymore. Cities are getting increasingly congested and trucks are not welcome in the cities. ”

Nissan Europe had been facing a declining customer retention rate and a customer renewal rate lagging behind that of competitors. Shortfalls were driven by poor customer data management leading to poor customer communications and interaction. Personalized communication is viewed as key to sustaining customer loyalty.

A reinvention of the corporate mission

Nissan’s plan as part of the Renault-Nissan-Mitsubishi Motors groups was to move from being considered just a carmaker, to a mobility service provider serving urban markets. Part of this strategy considered introducing an Electric Car-sharing Service something it has actively partnered with auto brand – Renault on delivering. This is in line with urban residents increasingly looking to multi-modal transportation systems to meet their needs.

Renault Group also supported Karhoo, a taxi, ride-hailing and private vehicle hiring service provider and offers a very broad choice of services with a total of more than 1.8 million vehicles as part of a signed partnership agreement with Karhoo. The company is also supporting Yuso through, RCI Bank and Services, a subsidiary of the Renault-Nissan-Mitsubishi Motors group.

While electric vehicles are quiet, cheap to operate, and offer most of the same conveniences available through conventionally-fueled vehicles; they are currently more expensive, have a reduced range of travel and taking longer to refuel. While these negative characteristics present the cars as being less capable, they are still possess the range and charging capabilities to meet the needs of almost every urban commuter, for 95% of their daily usage patterns. Yet perceptions persist for electric vehicles of being unattainable and undesirable. Providing the public with a positive first impression and direct experience with electric vehicles remains a challenge for any automotive manufacturer who is looking to enter the EV market.

James Hallam, PhD – Design Researcher, Design Strategist

All auto manufacturers would suggest that an improved unified view of the customer is needed to support the personalization of customer interaction but the challenges often include over one hundred data sources with silos of customer data, heterogenous data models and a lack of visibility into the end-to-end customer lifecycle. Every country in which Nissan operates for example also has different needs.

In 2021, Nissan laid out a plan to reach 50% electrification by 2030, spending 2 trillion yen ($13.8 billion) over five years. Based on customer demands for a diverse range of exciting vehicles, launching 23 new electrified models, including 15 new EVs, aiming for a 50% electrification mix by the fiscal year 2030. Nissan’s refurbishing infrastructure aims to support a circular economy in energy management, and Nissan aims to fully commercialize its vehicle-to-everything and home battery systems in the mid-2020s. Additionally investing up to 20 billion yen by 2026 towards charging infrastructure. The greatest success in all of these spheres has to include developing an ever closer relationship with the customer.

The Nissan Europe-CGI-Informatica tie-up at one point, saw 16 countries of Nissan Europe with their variability in data, live with the Nissan Customer Database and experiencing the benefits of improved customer insights, of course, a single view of each customer allowing Nissan to communicate in a personalized way too.

Personalization at work

According to Sinch, Nissan used their CRM data with Adobe Campaign to customize personalized Rich SMS campaigns in France and Spain, building long-lasting customer relationships after purchase that resulted in 4.7 times higher engagement, an 80% conversion rate and all off of a base of 200,000 customers targeted in the first 6 months.

Reinforcing its commitment to electric mobility and creating a carbon-neutral society, Nissan also announced a partnership with leading EV charging suppliers, Allego and E.ON, to update and increase the rapid charger offering provided by Nissan’s extensive European dealership network.

Nissan Europe also announced the launch of the GigCX peer-to-peer support. This is for pre-sale queries surrounding the Nissan LEAF® a leader in mainstream electric vehicles.

The partnership between Nissan Europe and Nissan United, Limitless, Amplify.ai and Facebook Messenger – offers a solution that features a combination of Facebook Messenger, Conversational AI, and seamless hand-off to humans for the peer-to-peer support model, a first for the automotive industry at the time and accelerated with the pandemic-driven digital shift.

Many prospective buyers of electric vehicles are first-time car buyers for whom empathy has become paramount when it comes to answering questions, increasing the importance of personal connection more than ever before.

As you can tell, the data is coming from a lot of places, different systems, different partnerships and in different formats.

The single-customer view

The approach to formulating the best possible golden nominal and single customer view means you need to make some careful choices about the data that you need to retain and curate. In the case of the CGI, Informatica and Nissan projects, this was done by focusing on the accuracy and reliability of the data coming from the different source systems. The analysis allowed source priority scoring so that the team could determine the leading system-of-record for each of the entities in the customer database. Data latency was also a factor with the recent data receiving a higher score.

The combination of both source priority and latency score determines which source data is kept in the Nissan Customer Database.

With so many sources in different formats, converging on a single, unique version of what a customer is, becomes a necessary part of establishing the Nissan Customer Database, ideally with the best possible version of the digital customer.

Advanced clustering and matching techniques identify groups of data that most likely belonged to the same customer, then cleansed the data, and then applied matching algorithms to identify the likelihood of two entities being the same customer.

This all paints a picture of the typical multithreaded nature of a big business pulling on many strings to improve top and bottom-line growth. The most important thing is that we should remember that the customer and customer records are central to the story. Without knowledge and insight, without convergence on a single source of definition for the customer, it is incredibly difficult to know whether all these efforts are being as effective as they possibly can be. It is a journey that never really ends.

Just like the transition from motorcycle engines to urban charging stations and local manufacturer-branded dealerships to maintain the smooth operations of after-sales service and fuel, maintaining customer data has to be considered a continuous activity and one where we believe Pretectum CMDM can help. Contact us today to learn more on how.

redbuttondata 0 Comments
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Jul 11 2022
Customer Master Data Management – what to expect

Defining the approach for Customer Master Data Management (MDM) for your organization means also understanding the boundaries of functionality. Define it right and you will have a goldmine of opportunities.

The term MDM has become progressively ambiguous over the years as vendors have branched out into areas of functionality that are not necessarily aligned with the optimal concept of master data management. This is just as true for the customer MDM as it is for the supplier, the employee and other master data elements.

While different classes of MDM can be defined as providing particular functions, MDM as a broad tool description is probably not that useful to business leaders. The ultimate question has to be, what do you want the Customer MDM to do for you? Knowing the answer to that question will direct you to the right combination of features and functionality to evaluate in a vendor or homegrown solution.

MDM technology and functionality overlap many types of software solutions that have addressed the issue of customer records and customer engagement in the past. These include Customer Data Platforms (CDP), Customer Relationship Management (CRM), and Marketing Automation (MA) platforms and technologies.

CRM and MA systems focus on customer interactions at the account level as well as at the individual contact level. Many CRMs are not purpose-built to be master record management systems, though they will have data mastering as an important part of their architecture. CRMs in particular, focus on sales events and pipeline call-off activities. As CRMs and Marketing Automation systems evolve they will subsume more MDM functionality and they will converge, however, CRMs will remain focused on what they do best, which is to gather and curate the interactions that your organization has with its contracted audiences and prospects. CRM and MA tools typically focus on known users.

CDPs capture anonymous data and verified or authenticated data. CDPs can also collect data on the customer journey and are built for the integration and collection of large amounts of data.  The core functionality of CDPs is focused on building out a unified database of existing and prospective customers, but they can also be used to manage customer engagement, provide analytics, campaign and event attribution and market segmentation, as well as enable personalization, message selection and campaign management.

Customer Master Data Management programs seek to have a golden record of the customer but probably should not include interactions from other systems except when those interactions alter the main customer record. While some MDM solutions are aimed at technical audiences, they do not necessarily need to be exclusively for technical teams since many mid-tier organizations don’t necessarily have data stewardship or data governance function. You’re either working in the business or you are in IT.

The view, at Pretectum, is that IT should not own or manage the content of the MDM, they should care for the platform but the ownership of the data and the quality of the data should rest within the business and business users.

Since MDMs come in all shapes and sizes, your needs will be determined by how you choose to frame the challenge and the degree of maturity of supporting processes for customer master data management. A suitable solution will support a litany of pieces of functionality, not all of which you will need.

As an example, if you need a master but you have teams that require personalized structures and attributes for specific tasks, then you should be able to do this the golden thread of the core master record is always accessible and at hand. There will be prerequisites but the system should support flexible usage and appropriate data syndication accompanied by high-quality data and a detailed understanding of what you have at your disposal in terms of the customer master record.

Learn more about the Pretectum CMDM advantage for your organization

    redbuttondata 0 Comments
    Jun 22 2022
    Customer types, patterns, and segments

    Whether you’re in Product or Service management, Sales, or Marketing you know that having an understanding of the customer, analyzing, and keeping track of their behaviour is critical for the effectiveness of your business.

    Customers make thousands of calculated and spur-of-the-moment decisions every waking hour of the day from deciding what they will eat to what they’ll wear. It is easy to think that the many ‘buy’ decisions, in particular, are made without too much thought, particularly the less significant ones.

    Decoding the thought processes behind customer decisions is no mean feat, particularly if you don’t have the data to back up your hypotheses around why customers do certain things.

    The Customer Data Model

    We try to decode the thinking because ultimately it can help us understand how customers arrive at their decisions and choices. In the study of customer behaviours, in particular, you’re looking at the processes customers apply to choose, use and dispose of your products and services and this includes factoring in their emotional, mental, and behavioural responses. Behaviour analytics examines the customer through the analytical lenses of psychology, biology, chemistry, and economic practices. For marketers, these analyses help in understanding what influences the acquire, buy and discard decisions. This in turn leads to a rehoning of the message, branding, positioning, promotions, advertising, and even what is ultimately formulated as a product or service.

    Only through an in-depth understanding of the customer can businesses hope how best to decide on products and service offerings and how adequately they fill gaps in the market and are needed and wanted.

    Revealing the customer

    There are three categories of factors that are considered an influence customer behaviour:

    • Personal: the customer’s interests and opinions as influenced by their age, gender, ethnicity, and culture.
    • Psychological: the customer’s reaction to particular kinds of messaging, which is dependent on their personal perceptions, attitudes, and mentality.
    • Social: factors such as family, friends, education level, social media, income, and socioeconomic status all have an influence on customer behaviour.

    In addition, there are four principal types of “buy” behaviour outcomes amongst customers; complex, dissonance-reducing, habitual, and variety or variability buy behaviours.

    Complex buying behaviour is typically associated with infrequent big-ticket product or service purchases. Such buy activities are complex in that the customers of engaging in a great deal of research before committing to the investment. Examples are purchases of high-end luxury goods, houses, cars, and holidays.

    Dissonance-reducing buy behaviour sees the customer encountering difficulties in determining the differences between specific products or brands. This ‘Dissonance’ often occurs when the customer fears making a bad choice. Clothing purchases may manifest this but equally, this can be present when buying appliances or electronic goods. Habitual buying behaviour.

    Habitual purchases typically involve very little preference, bias, or influence in the product or brand category because the risk is relatively low and there is no major emotional or cognitive investment. While grocery brands will often suggest that this implies brand loyalty, the reality is that in many cases the customer chooses based on past positive experiences which may be tied to price, look, feel, scent, taste, or overall experience. The repeat purchases are habitual rather than carefully thought through.

    Variety and variability in purchase behaviour are typically directly associated with past frustration, disappointment, or a bad experience with a previous purchase decision.

    The highly configurable Pretectum CMDM schema


    Pretectum believes that for you to have the best effect in terms of influence on the subscription to your services or the purchase of your products, you need to have the best possible understanding of your customer through the customer master data repository. This can help to inform your business in relation to how to target customers, what their purchasing power is like, their likes and dislikes and who influences their decision-making processes.

    The Pretectum CMDM enables you to decide the aspects that you need to maintain within the customer master, from an understanding of buying patterns to what they are buying, where, and when they buy, and how they pay.

    Consider what you store about your customers today and consider what you could store with the Pretectum CMDM to help your business in getting closer to your customers and being able to more appropriately understand and provide them with the goods and services that they want.

    Red Button 0 Comments
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    Jun 3 2022
    Social Shopping and Social Commerce

    Social shopping or S Commerce is a type of eCommerce that seeks to involve people with similar tastes in an online shopping experience. Sites like Pinterest claim to differentiate because on the one hand they offer the ability to pin items of interest but on the other hand they allow targeted marketing and click-through referral opportunities through image relationships. Arguably TikTok and Snapchat are also powerful channels for brands to launch their eCommerce campaigns. In fact, perhaps more than 50% of Snap’s business is in Direct Response advertising.

    Many social shopping sites are similar in feel and design to social curation site Pinterest. E-commerce experts suggest this is not coincidental, that the approach is catering to a new generation of shoppers who enjoy and expect a “Facebook experience” where users like and share as part of their online life and are seen to do this.

    Social shopping sites, like Kaboodle and ShopStyle, offer recommendations to members in the same way that you’ll see on Amazon Etsy and eBay.

    The concept of Social Shopping makes presentations personal, by providing members with the ability to create personal boards, preferences and lists. For these sites, stickiness comes in the concept of community and the opportunity to engage in a dialogue with friends and peers. The goal is to build community by encouraging members to talk about products and preferences and make suggestions directly to their friends and social contacts as they might if they were shopping together in actual bricks and mortar stores.

    Social commerce is that segment of eCommerce where sellers can actually sell and not just market their products directly through the social media platform, they can also browse goods catalogues and make those direct purchases.

    Unlike the more limited, social media marketing, true social commerce gives the customer the option to perform a direct checkout and settlement.

    Right now this is a $90Bn market, so what are the implications for customer data and your business?

    Social commerce is a subset of eCommerce makes it easy to measure and evaluate the performance of your ad spend with the various platforms. The social media platforms have built-in eCommerce metrics for impressions, engagement and reach. you can see the number of clicks, the number of views and the level of engagement and perhaps even the response sentiment. All these capabilities come at a price which erodes your potential customer lifetime value. With the average consumer spending around $400 – $500 per annum on social commerce, there are the many costs that are loaded up by the platforms to consider, from the ad spend through the commerce fees and charge and pay commission.

    In reality, social commerce is there for shoppers, not businesses. Since the entire process is focused on the particulars of the Social Media platform and if it includes checkout you lose website traffic and the opportunity to harvest some important customer characteristics.

    Further, unless you build customer contacts from your shipping or Logistics Execution System (LES), it is questionable who owns the actual customer. The more social platforms take over the buying process, the more they take power away from your business. The less data you have the less personalised the experience you can offer both online and offline.

    If those same platforms also sell the customer data they have to others, the further the cut into brand allegiance with shoppers potentially being redirected to competitors including the platform itself if it decides to branch out into retail.

    Contact us to learn more about Pretectum’s Customer Master Data Management system.

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      Red Button 0 Comments
      Mar 28 2022
      What is a CMDM platform?

      Answering the question of “what is a Customer MDM?”

      Across the globe, in all industry segments, data drives business processes, and systems.

      The overall organization, its employees, and its customers benefit when this data is shared and accessible across all business units. A unified single point of access for the same customer lists and data used to run the business. On the whole, business data users within the organization generally assume that the customer data that they have access to is consistent across the whole business until they identify anomalies.

      The reality though, is that customer data evolves in a more organic and somewhat haphazard way than data management professionals would prefer. This is especially true in larger organizations. Mergers and business acquisitions, projects and initiatives, and other general business activities often result in multiple systems being created, that often perform a similar or exact same function but for a variety of reasons, these redundancies must coexist.

      The result is that these conditions inevitably lead to inconsistencies in the overall data structures and the data values between the various systems. This variance leads to increased data management costs and organizational risks.

      The general consensus is that both data management and organizational costs and risk can be reduced through the dual strategies of Master Data Management and Reference Data Management.

      Master Data Management is about the management of data that relates to organizational entities. These organizational entities are objects like logical financial structures, assets, locations, products, customers, suppliers, and employees.

      These same structures provide the necessary context for smoothing of business transactions and transactional and business activity analysis.

      Within them, are entities, real-world persons, organizations, places, and things as virtual objects. These same entities are represented by entity instances. In digital forms, they are effectively digital entities but really they are data records. Master Data should represent the authoritative, most accurate data available about key business entities.

      When managed well, Master Data entities are trustworthy and can be used by employees in partner engagement with confidence. Surrounding these entities, are business rules that dictate formats, allowable ranges, and characteristics that should be applied to appropriately frame the master data values held.

      Common organizational master data may include data that relates to partners that are made up of private individuals, organizations, and their employees. That same data may describe their role, their relationships, and essential attributes that might be useful for engaging with them as an organization.

      Typical people-based master data entities are objects like customer, citizen, patient, vendor, supplier, agent, business partner, competitor, employee, or student.

      Seeking the truth

      When multiple repositories of these entities exist, there are potentially different versions of ‘the truth’ and it becomes difficult to work out which one is correct and whether in fact, two or more entities are referring to the same thing.

      In order to do so, one must have an understanding of the origins of the data. A defined System of Record (SoR) is often considered an authoritative system where that data is created/captured and maintained in a disciplined and controlled way.

      The capture and maintenance are undertaken with defined rules and expected outcomes. Historically this would mean that the Point of Sale system is there to support selling activities, ERP to support make-to-sell or buy-to-sell, and CRM to support selling, service, and support of customers.

      For any of these systems to be deemed trustworthy sources, they need to be generally recognized as holding “the best version of the truth” in relation to records they hold, based on automated and manual data curation. That trusted source is sometimes also referred to as a Single View. Within that system, the entities are often referred to as Golden Records.

      Systems of Reference similarly, are authoritative systems where reliable data is held and maintained to support proper transaction processing and analysis. Those systems of reference may or may not originate their own data.

      Historically, Master Data Management (MDM) applications, Data Sharing Hubs, and Data Warehouses have often served as systems of reference.

      The challenge is that different systems have different purposes and often no single system describing the same entity, needs to be describing the exact same characteristics of that entity. The question then becomes, can any of these systems truly be “the single source of truth”?

      Master data management efforts often pursue the consolidation of entities from the many sources that create and contain them and then formulate a composite record that may be incomplete and only a partially accurate representation of all the entities held. For different entity users that can mean that they have less faith in the “golden records” that the system presents. When this is the situation, the representation may switch from “Single Source” to “Trusted Source” suggesting that measures are in place to drive consistency, accuracy, and completeness in the entity records with minimal ambiguity and contentiousness.

      Gartner defines Master Data Management as “a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise’s official shared Master Data assets.”

      MDM is therefore a discipline, made up of people, processes, and technology. There is often no specific application solution despite the fact that vendors will often use the acronym to describe their products, systems, and platforms that manage master data but that does not mean that they are effectively managing the master data, simply that they have characteristics that, when used correctly. can assist in proper master data management.

      As you can imagine then, when something is described as a Customer MDM, it is a practice that relates to the management of digital customer entities. That practice could be paper-based also but we’re assuming that at scale you’re more interested in digital record-keeping.

      The CMDM systems then, are the people processes and technology that support the customer master data management practice. The CMDM platform concept is therefore a composite software application on-premise or in the cloud, that provides metadata and data that relates to the management of the customer entities.

      CMDM Platforms and related technologies for Customer Master Data Management are offered by many of the leading global software brands as parts of multidomain MDM like SAP, Oracle, IBM, and Informatica but there are some specialist offerings that you might not have heard like Ataccama, Pretectum, Profisee, Reltio, Riversand, Semarchy and Stibo Systems

      The original version of this article was posted as What is a CMDM platform?

      Red Button 0 Comments
      Mar 11 2022
      CUSTOMER MDM

      Data quality and consistency should not be neglected, market research suggests that poor quality, data redundancy, and data inconsistency are what most businesses struggle with on a daily basis. Customer data says Pretectum, is amongst the most common of the data that represent challenges to marketing, sales, service, support and billing, and collections functions. There has never been a better time to implement a more disciplined approach to customer data management than today!

      Customer Master data management (“CMDM”) itself is the convergence of people process and technology to maintain a disciplined approach to the definition, creation, maintenance, and distribution of customer data. Customers can be consumers or businesses and when you consider consumer customers these encompass those that visit a brick and mortar stores and locations as well as those that your business engages with via eCommerce or via phone, mail, or home visits.

      The discipline of master data management as a whole is an element of data governance which in turn is an element of business information management.

      Although MDM has historically been the exclusive domain of specialized data groups and IT.

      The Pretectum C-MDM platform view is that master data management and Customer MDM in particular, as an area of data management, cannot be realistically managed and controlled by technologists and IT.

      Instead, we view it as something that should be controlled and managed by business data managers and stakeholders

      Any Customer MDM seeks to ensure there is uniformity, accuracy, semantic consistency, controls, and accountability of the organizational customer master data. There should be the expectation that the data is to be used by multiple groups with different needs and expectations in relation to that data.

      A typical set of traits in your customer master data management system should provide infrastructure, methods, and processes in support of the following key activities:

      • Business Area partitioning
      • Multi-user role and team definition
      • Metadata definitions of one or more customer master object(s)
      • Metadata definitions of the key attributes and what are acceptable data types and values
      • Definition of a semantic data model and classifiers
      • Definitions and mechanisms to support data governance procedures
      • The collection of master data in a central repository via manual entry & automation
      • Data maintenance processes including data quality and statistical reporting
      • Provision of the master data to systems and stakeholders manually & via automation

      What about machine learning and artificial intelligence?

      While the use of artificial intelligence and machine learning is advantageous and can prove to be accelerators in the implementation and adoption of any MDM, these are technical approaches to ensuring the efficacy of data governance and data management where the processes policies and procedures are clearly defined.

      The presence of AI and ML should not be mistakenly considered a prerequisite for MDM particularly if there is a low level of organization data governance maturity or where the business is nascent in it’s data governance program.

      Pretectum C-MDM comes with AI and ML but it is not necessarily technology that is suited for every kind of scenario. The Pretectum C-MDM provides businesses with a single source of the core customer data that you define, in one or more ways, for use across the entire organization. This centrally trustable and governed data repository helps businesses to gain valuable insights and engage in better decision-making.

      What do I get from implementing MDM?

      As a business, implementing a master data management program in support of the customer master will bring a great many hidden and obvious business benefits, among these your business should expect:

      • Reduced or eliminated poor quality data and duplicates which leads to improved speed in identifying customers and maximizing your understanding of those customers
      • More effective customer prioritization and reduced friction and the likelihood of mistaken identity when interacting with customers.
      • Improve confidence in customer interaction opportunities and a likely higher yield from targeted customer event-based activities.
      • Improved decision-making across all divisions and improved value from existing and new data assets

      To achieve the best results, in considering an MDM for the customer, it is essential to assess your overall business goals and examine your business data priorities in particular. Your customer master may not be your main priority, the main priority may lie in inventory management, your product catalog, or some other area of your business.

      If you identify that you have a high degree of issues with your customer data, consider what your business is missing in terms of opportunities and determine what you consider would be success criteria for any initiative that you would implement in pursuit of improved data governance and in particular, the implementation of a Customer Master Data Management program.

      Pretectum C-MDM is a power platform focused on the customer.

      From instantiation through onboarding, data maintenance, and data syndication; businesses will adopt and get desirable results from leveraging Pretectum C-MDM in improving the overall performance of the data governance program using the platform’s customer data specialism.

      Contact us to learn more about how we can help with your customer master data management ( Customer MDM )

        redbuttondata 0 Comments
        Mar 9 2022
        CONSUMER LOYALTY AND CUSTOMER MASTER DATA

        Pretectum previously mentioned how some airlines leveraged their loyalty programs to secure loans from various backers. At face value, this tells you that though we as consumers store value in our reward points or air miles, so do the airlines and retailers themselves!

        Customer loyalty programs like Airmiles and rewards are forged relationships between brands and customers. This is one of the reasons that when a rewards or loyalty program changes the terms and conditions of the relationship, sometimes you will see a sharp uptick or drop-off in the use or support of that program. Launching a loyalty program is also expensive and complex.

        In the US alone, companies spend a staggering $2 billion on loyalty programs every year according to Capgemini.

        Typically loyalty programs serve as a way for the brand to offer membership-related exclusive products, promotions, or pricing. The reciprocated offer from the customer is their agreement to sustain the relationship with preference against that product line or service through repeat purchases or brand engagement.

        In a nutshell, a loyalty program is another marketing mix element. A part of any marketing strategy Loyalty Programs is designed to encourage customers to sustain their shopping or use the services of a business associated with the brand and program.

        Loyalty programs cover most types of commerce, each having different features and rewards. Industry segments that have leveraged broad loyalty programs include financial credit, hospitality & travel, retail and entertainment.

        According to Sallie Burnett, a loyalty consultant and Founder of Customer Insight Group. in a Forbes article, one of the most successful loyalty program examples is that of Nordstrom retail stores. Nordstrom customers move up through levels from Member to Insider, Influencer and Ambassador.

        Annex Cloud a loyalty experience solution suggests however that not all loyalty programs are a guarantee of success. Annex Cloud cite, a report by Capgemini wherein a high percentage of loyalty programs are considered to be failing.

        53% of consumers stated that they abandoned at least one loyalty program within the last year which means businesses are putting money and energy into strategies that aren’t being successful. The main reasons vary, from a lack of reward relevance, flexibility, and value (44%) through a lack of a seamless multi-channel experience (33%) to customer service issues (17%).

        Pretectum feels that one of the ways to mitigate some of the aspects of customer service and multi-channel interaction is through the convergence on a single-source-of-truth in relation to the customer master. If your sales, service, support and loyalty programs are all reading from the same song-sheet, a centralized customer master data hub, then the ability to service the same message consistently and coherently is greatly improved. This in turn leads to a greater likelihood of retention.

        Here are some interesting statistics in relation to loyalty programs and the customer relationship.

        • 82% of companies say retention is cheaper than acquisition.
        • 75% of consumers say they prefer brands that offer rewards.
        • 56% of customers stay loyal to brands that “get them”
        • 58% of companies use personalization to retain customers 

          redbuttondata 0 Comments
          Jan 24 2022
          Reimagining Customer Data

          Brands and retailers need to reevaluate how they think about customer data

          In a survey conducted by SuperOffice, it was found that 45.9% of business professionals are prioritizing customer service over products (20.5%) and price (33.6%).

          There has been a customer revolution of late, brand loyalty is now not limited to just products or price; they are willing to invest more in a purchase if the customer service is above average.

          It goes without saying, that customers want straightforward answers to their queries and that they appreciate brands that personalize the interaction experience from the start with offers that communicate clear expectations on what the customer can expect in return. Businesses that fail to customize the message and fail to personalize the offer in the presence (or absence ) of customer data are likely to leave customers disinterested or frustrated. Neither of these outcomes is desirable and puts retention and repeat purchases at risk.

          Statistically speaking, brands that offer omnichannel experiences retain 89% of their customers compared to 33% of those that don’t. The reason this is an important “stat” to pay attention to, is that the old paradigm of perhaps exclusively engaging in business via brick-and-mortar stores often now sees those same customers expecting a digital experience too. Leveraging digital channels means that they can interact regularly with brands in a way that they couldn’t before. These could be by way of email, website chatbots, mobile apps, customer service chat sessions, Twitter, Facebook, Whatsapp, telegram, and a host of other platforms and interaction methods.

          If you believe that data can fuel your digital transformation journey then you will also recognise that it offers the potential for more interaction and communciation consistency. By leveraging centrally stored well-managed detailed customer information, all manner of services and support can be made use of in the honing of the customer message to provide a personalized and distinctive customer experience.

          Curbside Pickup as a data point

          A curbside pickup service is one where retailers allow customers to place an order online for them to then self or courier pick up at a local store. In some respects this is an evolution of drive-through with the principle difference being that curbside pickup can simply be an extension to normal pick and pack but without the ship part.

          When the order is ready, the customer is notified, either by email, SMS or mobile app message and the consumer walks or drives to the store and in a designated area collects their order. In some instances they may nominate a courier or home delivery service provider to make the collection for them. Either way, the seller is not responsible for collection/delivery beyond making the consignment available for pickup.

          The COVID-19 pandemic saw demand for curbside pickup increase by 85%. Customers would often make this choice because they want to be safe and prefer the click-and-collect method instead of physically visiting the store.

          For businesses that already supported a click-and-collect (C&C) operation, the pressure was more on whether infrastructure could cope with the increase in orders. For those who had never offered C&C the pressure was to implement the data capture mechanism for not just the customer details but also their payment processing, preferences, contact information and a eCommerce or webshop element. The stores would also need to be geared up to do more order-based picking where previously the main focus would have been on shelf packing and checkout.

          Connecting the web front with back end systems may sound like a straightforward IT integration but often that would not be true where the logistics execution or point of sale systems operate in complete isolation from eCommerce and webshop systems. From the Pretectum perspective, this is where Customer Master Data Management can operate as a central hub for the many functional spokes that represent different aspects of business operations.

          Data is a key to aligning the customer experience

          98% of Fortune 500 companies leverage data to enhance the customer experience. Businesses need to have a defined data strategy that helps them scale to an ever-evolving environment.

          Business decisions and marketing initiatives are ideally driven from data insights and those are best established when they come from analyzing the various aspects of your customer’s data.

          Your customer data management system can serve as your single source of truth and can neutralize the concept of data silos. Silos of customer data can be very common in businesses that have implemented systems and approaches to dealing with customers in an isolated and tactical way.

          Every department that is potentially customer-facing, including sales, marketing, finance, service, and support, requires specific kinds of information to undertake their role. This information when stored separately can become fragmented, inconsistent, and incomplete. thereby making it difficult for other departments to access and draw conclusions that may be tied to the data held cross-operationally.

          Data silos might seem harmless and fit for purpose through the narrow lens of a particular department or function but even within a narrow frame of focus, that data will develop inconsistencies over time. With so many business area-specific data silos popping up, it will be difficult for business leaders to draw appropriate conclusions and in turn provide customers with an optimised experience.

          Breaking the silos is crucial for businesses. The route to this elimination of the silos is to provide data centralization and save time (and resources) that is spent on dealing with trying to create an optimized picture of the customer and the customer circumstances

           Customer Master Data Management offers the potential for the controlled flow of batched and real-time customer data through all appropriate business channels with a consistent and unified aspect.

          Almost all C suite execs believe that customer data is critical for their businesses to get ahead of competitors.

          Uli LOKSHIN 0 Comments
          Jan 4 2022
          What Is Customer Lifetime Value (CLV): All You Need to Know

          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.

          read more

          Juwel Tan 0 Comments
          Dec 28 2021
          Customer Lifetime Value – The Essential Marketing Mantra

          Post-Covid the basic human lifestyle changes have started to happen. To put it in a nutshell, slowly the mouse and keypad will be antique pieces, and “voice and hand gestures” will be the new user interface with all devices.

          Don’t be surprised if your 55-inch TV becomes “obsolete” as more and more wearable glasses or even contact lenses become your basic visual devices. We all would be having our very own virtual assistants who will help us throughout the day doing all the work and chores. Therefore, the predicted mobile traffic by 2025 is going to be more than 100 exabytes.

          With so much talk on technology, where does it leave the marketing teams of the future?

          The digital trends used for marketing are bound to change as more artificial intelligence, voice search and gestures, mobile-oriented campaigns and emotional visual content will be used.

          But having used all these latest or future technologies, how do you measure the Return On Investment (ROI)? The future marketeers who may refuse to acknowledge or ascertain the returns will not succeed and fade out soon. Irrespective of the trends or means of marketing the one thing we all need to keep in mind is the “Customer Lifetime Value.”

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          Uli LOKSHIN 0 Comments
          Dec 21 2021
          Customer lifetime value modelling

          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.

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          Juwel Tan 0 Comments
          Nov 30 2021
          Customer Fundamentals – time to take a big step

          Master Data Management may be positioned as a “silver bullet” for the woes of poor customer master data but it doesn’t solve for long-standing systemic organizational deficiencies.

          Any organization embarking on any kind of Master Data Management (MDM) initiative will need to look long and hard at a number of characteristics of how data is created, described and managed that are independent of the MDM itself if they wish to get the best value from their MDM.

          That highly desirable 360º view of the customer, for example, what is it exactly?

          Benefits as described by vendors and industry experts are numerous, but perhaps a small handful is the most important and most achievable.

          • Reducing the costs and risks of customer data ownership
          • Reducing friction in transacting or engaging with the customer
          • Improved customer segmentation and targeting lists

          All three of these outcomes are however heavily contingent on a number of important behaviours and organizational culture shifts.

          Continue reading at Pretectum.com

          Red Button 0 Comments
          Nov 30 2021
          Some customer data is missing
          The incomplete person

          How often does this come up as a problem to solve? It may happen more frequently than you think.

          Having clean, comprehensive, and consistent data is paramount to the most appropriate customer engagement and interaction. If your business is also an advocate and heavy user of automation, machine learning and artificial intelligence then your technical teams will tell you that the results of their efforts are commensurate not only with their efforts but also with the quality of the data that they are working with.

          Without the best possible customer data, your staff and systems are exposed to a partial picture which can result in bad decisions, model bias and skewed results.

          The US National Library of Medicine and National Institute of Health (PMC) journal contains an article from May 2013 describing three types of potential data deficiency in any given data set. While the focus in this case by the author, Hyun Kang would be on suitability for studies, this basis is useful for considering customer master data in general.

          The three types are Missing Completely at Random (MCAR), Missing at Random (MAR), and MNAR (Missing Not at Random). Each with its own cause and potential solutions.

          We’ll look at this through the lens of a customer master data management system. Read more at Pretectum.com

          Red Button 0 Comments
          Nov 25 2021
          How Manufacturers Can Get Started Selling Directly To Consumers

          Let’s face it: Manufacturers’ traditional sales models can hurt both the company and the customer. Because of the pandemic causing havoc on supply chains, selling direct has become a more popular option for many manufacturers. 

          Looking forward to the 2020s, the old model of selling through a distribution/broker/retailer channel may still be alive, but many company leaders are finding that their customers prefer to buy directly from them. On top of that, restrictive middleman margins can increasingly put a chokehold on manufacturers’ profits.

          When Covid-19 hit, people ran to the internet to shop for just about everything. I think manufacturing as an industry reached a tipping point between the pandemic, a global supply chain malfunction where production halted and even stopped for some companies, and some online retailers refusing to change policies to adapt to these situations.

          These factors led many manufacturers to ramp up and increase their investments in a direct-to-consumer (DTC) strategy, where they have 100% control over pricing, inventory levels, and — increasingly — access to critical customer data. As the co-founder of a company that creates digital sales channels for manufacturers, I have some advice for those just getting started with selling directly to consumers.

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          Uli LOKSHIN 0 Comments
          Nov 23 2021
          Customer Data’s impact on Digital Transformation

          When we hear the words “digital transformation”, the first thought that might come into your mind might be the shift from a traditional manual office environment into one that is leveraging all things digital.

          That perspective is valid to some extent. Many companies and businesses shift from traditional physical business practices to more modern digital ones to improve not just operational efficiency but also to accentuate their digital presence.

          They might do this either by creating a mobile app, revamping or launching their website to support e-commerce or even by ramping up their social media presence. All of these decisions and behaviours fall under the umbrella of digital transformation initiatives.

          Continue reading at Pretectum.com

          Red Button 0 Comments
          Nov 23 2021
          Net Promoter 3.0

          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.

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          Juwel Tan 0 Comments
          Nov 16 2021
          How To Calculate (And Improve) Lifetime Value

          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.

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          Juwel Tan 0 Comments
          Nov 15 2021
          Deploying AI beneficial for firms and may help governments identify corruption networks

          Fintechs are already looking into methods to leverage data and artificial intelligence (AI) in services and products so that they can provide relevant, trustworthy insights, suggestions, and controls.

          Today, businesses employ supervised and unsupervised machine learning to train models so that they can detect fraud attempts faster than they can use human (rule-based) methods.

          KYC and identity verification are other important areas where AI can be very effectively used. Earlier, humans had to manually verify if the given documents of customers are accurate or not. This tedious task used a lot of time and resources. Now, AI can assist banking applications and other online financial services in automatically and securely verifying clients’ identities. This is referred to as KYC.

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          Uli LOKSHIN 0 Comments
          Nov 15 2021
          The Key Factor in Marketing to Hispanics This Holiday Season

          With more than $1.5T buying power on the line, brands must understand what matters most to the Hispanic and Latinx community

          A look at Americans of Hispanic origins, three-fourths (77%) of surveyed Hispanic adults in the U.S. stated strong familiarity with their origins and 71% stated that they felt a “strong connection” to their roots—nearly double that of white adults surveyed from Pew Research

          The data comes as no shock to those of us who are either part of, or at the very least familiar with the Latinx communities in the U.S. As Cynthia Correa says “Our roots cross every element of our lives, from our tastes in food and music, to the sports we love, the hobbies we enjoy and the holidays we celebrate with loved ones. It’s a core part of our identity, a sentiment I’ve long known but Pew has given us the data to back it up.“

          Read more at Adweek

          Uli LOKSHIN 0 Comments
          Nov 15 2021
          Costco customers complain of fraudulent charges before company confirms card skimming attack

          Costco is offering victims 12 months of credit monitoring, a $1 million insurance reimbursement policy, and ID theft recovery services according to ZDNET.

          Costco has sent out breach notification letters to an unknown number of victims after multiple people took to social media to complain about fraudulent charges connected to the company.

          First reported by Bleeping Computer, the letter says payment card information was compromised through a card skimming device at certain Costco locations.

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          Uli LOKSHIN 0 Comments
          Nov 10 2021
          Yet another data breach: Is your password on the dark web now?

          Stock-trading app Robinhood announced Monday that a Nov. 3 data breach had leaked the personal information of 7 million customers.

          The compromised data was mostly email addresses. But according to a press release, names, dates of birth, ZIP codes and “more extensive account details” were leaked for a small subset of users as well.

          Robinhood, which was best known before the leak for its role in the GameStop meme stock saga, is only the latest data breach victim, in a long list of companies that seems to grow every week.

          That means if your personal information hasn’t been stolen yet, it probably will be someday. 

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          Juwel Tan 0 Comments
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