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Jewel Tan - Blog

Page: 1 | 2

Good customer analytics starts with good data

Consumer data helps companies a great deal to improve nearly every aspect of their business. With proper data analytics and a data-driven marketing approach, brands are able to gain actionable customer insights, generate quality leads and increase customer loyalty, among other things.

According to a survey done by Harvard Business Review, 58% of enterprises have experienced a hike in customer retention and loyalty by making the right use of customer analytics. 

Elevating the quality of your customer data can benefit your business in a number of ways and here are a few thoughts on aspects you might want to consider:

The enhanced customer experience (CX): There is evidence to suggest that businesses that are customer-centric tend to be way ahead of their competitors. To follow a customer-driven approach, you need access to comprehensive customer-specific data. The gathered and enhanced customer data can be useful in being able to understanding and predicting customer behaviour which in turn can be used to improve customer experience through customized offerings, messaging, interaction and services. Without the data, it is hard to provide anything more than a generic message or offer which may not resonate.

Precise targeting and lead generation accompanied with a lower CAC: Effective marketing can translate into a shorter sales cycle, greater sales volume, or appeal to a wider customer audience. For a marketing campaign to be effective though, it needs to have good data to support the estimation of the potential target market or market segment. Having good customer data opens up the opportunity to segment based on customer demographics, showing where the customers are, their age group, their gender, education, likely income, potential disposable income, and other critical traits that you might consider for targeting.

Drawing customers in for multiple engagements or appealing to new customers is made more likely with comprehensive and correct customer data that allow your business to focus on customer-characteristic-based marketing strategies to generate quality leads.

According to Thomas Griffin Co-Founder and President of OptinMonster in a piece on Forbes – customer acquisition cost (CAC) can be lowered if you have the right targeted message aimed at the right audience, whether it be PPC or contact-based marketing campaigns. To have that message, you need to know something about your audience, particularly if you’re running contact-based campaigns

Brand Improvement: Customer feedback and reviews form an important part of customer data but for this kind of data to be really useful, it needs to be tied to the best possible customer master data. To run effective customer review and survey data analytics you want to be able to paint a complete picture of respondents. Survey submissions that support uncovering the strengths and weaknesses of your brand and offerings can be effective in isolation by conveying a sense of general measures of customer satisfaction but they ultimately reduce their usefulness without reference to customer data.

Survey responses may impair your ability to derive maximum value from responses by being unable to tie them back to the respondent’s lifetime customer value. The CLV model informs you on whether the commenting customers are actually high-value customers or one-off customers who bought on a deal or opportunistically and that may never buy from you again.

Tools matter: we’ve talked about tools before, principally tools like your Customer Data Platform (CDP) and Customer Relationship Management (CRM) solution where you store large amounts of data and consumer profiles. You may even have an ERP (Enterprise Resource Planning) system or a CDM (Customer Data Management) platform. Your business may in fact have all of these., but the question of whether they are fit for purpose or suitable for all the jobs that your business needs to undertake needs to be carefully considered.

We’ve observed that there is a lot of enthusiasm about using AI for data collection accompanied by scraping tools and social media trawlers and transaction aggregators to increase the volume of data collected.  What we’ve also observed is that some of the fundamentals of knowing your customer remain missing or incomplete. This is partially due to poor data collection, collation, and assessment processes but it is also a function of the nature of the tools. Some tools are better suited to transaction processing, interaction or engagement, etc. Very few of the tools that we’ve mentioned, are suited to mastery of the digital customer and if they are, it is typically in the service of a specific application objective.

Customer data is presently experiencing a revolution in the business world. Data for every kind of business, from B2B sales and eCommerce brands to digital content creators, service and hospitality, healthcare and financial services, and a number of others too. All depend on gaining a source of appropriate and correct customer data to increase their leads, opportunities, and ultimately business., Knowing the audience, creating personalized marketing strategies, generating quality leads, and reaching a wider audience is the brass ring that leads to business success.

There is no exaggeration in saying that in today’s world of digital advancement, your company cannot survive without the best possible proper and relevant customer data.

You can achieve that with a Customer Master Data Management (CMDM) platform like that offered by Pretectum.


Publish Date: September 23, 2022 2:05 AM

Calculating the value of customers

The monetary value of a customer relationship is important in understanding how much you might choose to spend on acquiring a customer or how much you might choose to invest in a customer acquisition strategy over time.

82% of companies agree that retention is cheaper than acquisition and some three-quarters of consumers say they prefer brands that offer them rewards for their loyalty.

Just over half of customers claim that they stay loyal to those brands that relate most closely to them and 65% of most brands’ business comes from existing customers so it comes as no surprise that working out what those customers cost you to acquire and what it takes to retain them should be an important focus of what your organization does. All of this is encapsulated in the Customer Lifetime Value or CLV concept.

What is the average customer retention rate?

Customer Retention Rate (CRR) by Industry is variable, in Retail this tends to be around 63%, in Banking, 75% and in Telecom 78%.

However, churn (customer switching) is becoming increasingly commonplace in the telecom and banking sectors due to the more open approaches to doing business and the advocacy for consumers through initiatives like “open banking” and “number portability”.

In the perfect world, you would see 100% customer retention, where the products and services that you offer are uniquely distinguishable from those of others, such that they are considered indispensable and non-displaceable by competing brands. Where monopolies exist or where the difference between your brand and the next best competitor is massive, you may find that close to 100% retention is achievable. Retention above 90% is exceptional and retention above 75% is considered very good. Retention below 25% is not very good verging on bad or terrible.

It is important to measure retention nonetheless because the longer you can retain the customer the cheaper the acquisition costs and the higher the customer’s lifetime value.

Retention translates to customer loyalty and should be a Key Performance Indicator that determines whether your products and customer loyalty strategies are effective.

So just how would you calculate your customer retention rate?

Start with counting the total number of customers you have at the end of a time period (month, quarter, or year) – the Pretectum CMDM can be an aide in doing this. Next, subtract the number of new customers you acquired in the same period, here too, you could use the Pretectum CMDM to do this. Next, divide the remaining number by the number of customers you had at the start of the period.

Customer Loyalty

Customer loyalty is influenced by many factors, it has been found that the most loyal customers associate positive experiences they have with the brand or company with sustained and recurrent purchases. They may also be observed to have higher conversions (visits that result in a sale) and higher overall spending (higher event value).

Keeping customers happy and inducing them to return for more is vital to the success of any business. So, higher profitability often begins with existing customers. Repeat customers not only spend more money on a more frequent basis, but they also assist to increase the number of new consumers that come through your doors through recommendations and brand promotion. As a result, it is critical to maintaining a high customer retention rate (CRR).

Pretectum believes that one of the best ways to promote a high CRR and establish the highest possible CLV is through interaction personalization and a closely curated relationship with the customer.

This means knowing who your customers are, what their preferences are and conveying to them a disposition of caring and genuine knowledge about them and their circumstances and relationship with your brand or business. This relationship-building is best achieved through appropriately comprehensive and correct customer master data.



Publish Date: June 13, 2022 6:19 AM

Customer Master Data should matter to you

It has been suggested that companies that do not understand the importance of customer data management are less likely to survive in a post-pandemic modern economy.

Your customer data could be your business’s most valuable asset. But there are a few things to consider if your intentions are, to create a truly data-focused organization.

Pretectum feels that data is foundational for building business information.

They see it as essential for creating customer knowledge, and ultimately the driving force behind correct tactical and strategic decisions and business actions like optimizing your call center operations.

If your customer data is relevant, complete, accurate, meaningful, and actionable, it then becomes instrumental in driving the growth of the organization. If it has deficiencies it can prove to be a useless and even a harmful inhibitor to not just growth, but also business sustainment.

Customer data management initiatives should be put into play to systematically create and maintain customer master data and increase the organizational potential and these should focus on quality and control.

The most successful organizations manage their customer data cycle well by managing the way customer data is created, stored, maintained, used, and retired.

When customer data management is truly managed effectively, the customer data life cycle commences even before any customer data is acquired.

Data management as a discipline, is the function of planning, controlling, and delivering data effectively in any organization and includes practicing a discipline in the development, execution, and supervision of plans, programs, policies, and practices that protect, control, deliver and enhance the quality and value of data and information in the organization.

Risk mitigation

Not only is there an expectation as a result of privacy and compliance, but there is also the question of business reputation. Any organization that fails to maintain and assess its customer master data can be subject to non-compliance prosection or personal litigation. Security of customer master data is therefore very important and proper and appropriate data management helps in making sure that data is never accessed in an inappropriate or unauthorized way and is protected inside the organization. Data security is an essential part of data management and Pretectum takes pride in the fact that it uses the latest methods and techniques to ensure that customer data remains secure and protected but is still able to be used by the business as required.

Making use of a modern cloud platform like the Pretectum C-MDM protects not only the integrity of the data but also provides assurance to employees and companies that data loss, data breaches, and data thefts are less likely.

Effective data quality

There should be little doubt that a structured and planned approach to customer data collection, curation, and review, will lead to better data quality. Improvements to data management practice, however, do need to be considered as something progressive. It is rarely possible to simply implement a software solution and expect there to be an immediate change in the status of your customer master data. There likely needs to be a rethink of all the participants in the data management process, an evaluation of roles and responsibilities, and the establishment of some data quality measures. This is typically covered by a digital transformation project but can also be driven by a data management organization that functions at a level of maturity despite perhaps making use of largely manual controls, processes, and methods.

After the implementation of a platform like the Pretectum C-MDM, your business will see improved data management which in turn will help in improving data quality and data access. For the business as a whole, this often translates into less friction in engaging with customers and improved decision-making even at the call center agent level!

Doing things right is doing things better…

Peter Drucker is quoted as having said “Efficiency is doing better what is already being done“. At Pretectum the feeling is that there must be a better way to manage your customer data and that, data managed properly, updated, enhanced, and made accessible, will enhance organizational efficiency. Conversely, inaccurate, mismanaged data will waste precious time and resources.

Eliminate errors, eliminate waste…

Only through effective customer data management will you minimize the occurrence of errors and reduce the damage that bad master data can cause. Transcription, poor integration, and legacy methods used for capturing customer data introduce a greater likelihood of customer master data errors. With centralized customer master data management underpinned by data validation and data quality, your business has the best chance at creating and retaining the most valuable business data asset – your customer master.

Publish Date: March 23, 2022 6:53 PM


Considering the alternatives

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.


Publish Date: March 11, 2022 3:31 AM


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

Publish Date: March 9, 2022 10:44 AM

The Gen Z customer and brands´╗┐

The Gen Z customer and brands

red car sport portrait

Pew Research Center has been studying the Millennial generation for years but in 2018 decided there was a difference between Millennials and the next generation.

They decided to use 1996 as the last birth year for Millennials for their future work. Anyone born between 1981 and 1996 was considered a Millennial, and anyone born from 1997 onward is part of a new generation.

They hesitated at first to give this next generation a name but settled on Generation Z. In the interceding years, Gen Z has taken hold in popular culture and journalism. You will find it referenced in Merriam-Webster, Oxford, and Urban Dictionary as the generation that follows Millennials.

This is a generation with which you have an 8-second window to either perform or perish.

Sarwant Singh – Forbes

As cited in a 2019 article, “generational cutoff points aren’t an exact science. They should be viewed primarily as tools”, tools for analysis and classification of people, like your customers!

Why do we bring this up? Well, the answer is simple, Gen Z represents a significant customer market and they are a generation that has been raised on the internet and social media.

Most of them earn their own income and even if they haven’t quite flown the coop, their parents and family members likely support them financially with more robust purchasing power than prior generations of youth.

In China, for example, they have naturally become the main force that drives China’s consumer market.

As members of Gen Z take center stage in the consumer market, they are influencing the survivorship of brands and they aren’t necessarily going for the mainstream or traditional brands, and China, in particular, not even necessarily chasing global or foreign brands.

This represents a significant opportunity for newcomers, niche brands, and brands that choose to distinguish themselves from the rest of the pack.

Broadly speaking, Gen Zers are ethnically diverse, socially aware, and environmentally conscious” according to Singh. Authenticity and transparency are key and they prefer direct autonomy and control in their decision-making as opposed to being ‘sold to’. This implies a general distrust of big established brands, and favor for brands that focus on the individual. Purchase decisions are therefore based on peer reviews, accessible product information, and ratings – decision potentially by consensus. Who has all that? Actually, the heritage brands do, they just need to keep the volume and velocity of good ratings up.

Where global brands sometimes fail

We have to acknowledge that tastes change over time, and with them, brand preferences. Just ten years ago, if you were considering the purchase of a Tesla car say, you would have raised some eyebrows, today, not so much.

The eyebrows would likely have been raised by those born in an era that was dominated by global brands like Ford, Volkswagen, Hyundai, Nissan, Toyota, GM, Mazda, and the like. Other brands like Mercedes-Benz, BMW, Porsche, Ferrari, Lamborghini, Bentley, and Rolls Royce would have been regarded as premium brands. You’ll find a lot of sentiment out there about these brands because many of them have been multi-generationally familiar to us.

An article in the SCMP suggests “Your choice between, say, an Audi Q7, a BMW X5, a Porsche Cayenne or a Mercedes GLE (now) becomes more a matter of your brand preference than of significant product differences. The choice of options and materials is pretty much the same.” Engines used to be a differentiator, for example, but that difference may be moot with all-electric engines, and though the heritage brands are late to the game, they may still have their brand and their history with the past customers as the ultimate trump card.

Studies undertaken in 2020 and 2021 by YPulse in North America according to Inc, noted that young people were already thinking differently about mobility for example. Gen Z’ers are looking at alternatives to ride-share and public transport in favor of their own rides. 3.4% no longer want to ride public transport and 56% say they want safer transportation, options that they obviously feel ridesharing and public transport don’t necessarily offer.

E&Ys 2020 Mobility Consumer Index found that 45% of all first-time car buyers are Millennials, another powerhouse group with dollars to spend. Intuitively, one would expect the more ‘environment woke’ Gen Z and Millennial consumers would be interested in only all-electric vehicles like those offered initially by just Tesla and a few others, the analysis doesn’t necessarily support this viewpoint though.

Based on market research performed by Hedges & Company in 2018, it turns out the average Tesla owner is a 54-year-old white man making over $140,000 with no children; so what would it take to change that demographic to more Millennials and Gen Z?

According to Inc, what matters to these generations is not the flashy features that get Boomers and Gen Xers excited. Ypulse found that the younger buyers are more interested in comfort, reliability, and fuel efficiency – in that order, facets that are offered perhaps by Tesla but which traditional brands offer too, at a lower or comparable price point. Remember too, that peer reviews get factored in too!

Keeping their product lines aligned with their heritage and yet still seeking to appeal to the potentially more environmentally conscious Gen Z it is interesting then, that a heritage brand like Ford has “gassed” its business up with new and compelling offerings in the hybrid and full EV spaces. They’ve recognized the need and played their brand advantage but they’ve done it with data to back up their position.

What this is demonstrative of, is a well-established brand responding relatively quickly and introducing horizontal differentiation within the brand vertical that Ford is. The F-150 Lightning for the utilitarian persona perhaps, the Mustang Mach-E for those looking for something with wholly visual and performance appeal, and the E-Transit for the commercial sector. Three distinctive models for likely entirely different markets.

It is suggested that the Gen Z consumer distinguishes themself from other generations by being perhaps more emotional in terms of needs. There’s an element of their outward appearance and overt visible behavior, combined with a need to be distinctive and unique in the face of a great deal of societal homogeneity.

It is perhaps that reason that singles out their relative disinterest in the Tesla brand. Theirs is a personalized aesthetic perhaps, and the older more established brands like Ford, GM, Nissan, and Toyota et al may actually have a better shot at servicing this aesthetic as a result of having offered personalized customization in the past, while at the same time being ecologically and environmentally responsible. It is also about availability. Do I buy something I can drive off the lot today or do I wait? Time will tell. There’s still a relative scarcity factor a long waitlist for Tesla and that doesn’t help.

So what made Ford, take the ambitious objective of all-electric engineering on at the time that it did? According to Forbes contributor Dale Buss, “Ford futurist”, Sheryl Connelly looked at a global survey of thousands of consumers and articulated in Looking Further with Ford Trends Report that off-planet travel for leisure and entertainment Gen Z; and disinterest in next generations of humanity characterized Gen Z. This is backed up by 81% of adults saying climate change is a worry for future generations and at least 40% of Canadian women, for example, cited as having concerns about climate change as a reason for not wanting to have children.

I read that as potentially a story that suggests previous generations have ruined the planet and we need to look for alternatives – something not dissimilar to the message in the apocalyptic black comedy film “Don’t Look Up“. It’s conceivable that Gen Z believes that there are well-progressed invisible plans to colonize other planets and not everyone knows or is “in” on those plans.

Now you might ask, what does this all have to do with Customer Master Data and MDM in particular? Pretectum’s view is that there’s actually quite a lot. Companies that embrace authenticity will find that Gen Z customers will be their best brand ambassadors. What better to demonstrate authenticity than to be environmentally and socially responsible and yet support uniqueness, individualization, and personalization.

Accommodating individual preferences was ironically the aspect of Henry Ford’s pushback with the Model T that he is well known for. “Any customer can have a car painted any color that he wants, so long as it is black.” The Model T only came in black because the production line required compromise so that efficiency and improved quality could be achieved; modern vehicle production doesn’t have to be so rigid, and in fact, make-to-order (MTO) is increasingly commonplace today even at Ford.

Ford’s goal is to have MTO factory orders account for upwards of a quarter of vehicle sales and consequently, they can reduce overall finished vehicle inventory in US dealerships from a historic average of 75 days to a targeted range of 50-to-60 days.

So, if your business is in automotive for example, you likely have a generation or in fact, multiple generations of buyers of your vehicles. If your customers have had a good past buying and driving experience, they may even have bought multiple vehicles from you.

Those Gen Z’ers that chase a Ford likely grew up in a household where a Ford was owned. There may even be a degree of unintentional brand loyalty among them. As an auto manufacturer, the chances are, you know who those past buyers were, but more importantly, if you’ve afforded them credit, insurance, warranty, extended warranty, and even service and support you know heaps about them from all that interaction.

To maintain those relationships with past customers, and to benefit from the data you have collected in the past you need to consider that you can harvest unique insight that newcomers cannot. You can start to leverage the adequacy of responses to surveys for example. You have to be engaged with those past and present customers and keep them interested in actually engaging with you again and one of the best ways is through personalized communications which are driven by detailed and appropriate customer master data. You can only really do that if the data is aligned with your business needs and the intentions that you have in mind for your outreach programs.

This is where Pretectum as a customer master data management platform provider (CMDM) can be of help. 

Publish Date: February 23, 2022 8:29 AM

Why you may want to obsess about customer data management today

Over the years, many businesses have successfully held onto a loyal customer base while generating new relationships with new customers and retaining them through optimized and appropriate customer relationship management.

Oftentimes, this formation and retention of customer relations have been heavily tied not just to the brand and the products and services but also through how that business has managed customer data.

Interestingly, even businesses that have adopted customer data management are not necessarily household names and brands that you might recognize but they’ve still been able to stay in business sometimes in a multi-generational way because they work hard on building and maintaining the customer relationship and are leveraging data to do it.

Times have changed and often it may seem really hard to do business with customers in the way it used to be. At face value that means that only the strongest brands might survive. This doesn’t have to be true though, what this does mean though, is that now more than ever, businesses need to not only adapt the way that they think about the customer but in particular how they consider customer data management. They need to obsess about it because the competitive game of business around them has changed from something that perhaps seemed easy, to a more advanced level. Businesses that still want to play easy would be at risk of facing an imminent game over.

Old habits die hard” – the bad ones need to be killed off with persistence.

Fewer than 200,000 businesses in the United States may have failed during the first year of the COVID-19 but the final tally may be higher than thought given the subsequent waves of the Delta and Omicron variants.

Business failures often stem from misalignment between the unique resources and capabilities of the organization and the demands of the new business environment and data can be one of the greatest resources that help inform your business.

COVID-19 certainly introduced a number of aspects to the way businesses work, that changed a lot of the face-to-face personal experience for retailers but it also changed things for the bespoke and custom apparel sector. The pandemic did a pretty good job at slowly killing consumer purchasing habits and behavioral patterns in particular until there is barely anything left to even be cremated!

The global pandemic has greatly impacted businesses in all industry segments in all geographies and has forced us to rethink how we work, travel, communicate and shop. This change in old habits has affected businesses, both big and small. Very few escaped unscathed in some way.

Before the covid-19 pandemic, local businesses had regular operating hours, the notion of walk-ups into a physical store to purchase items would have been considered commonplace.

When the pandemic hit, our physical movement became restricted, safety became a priority, walk-ups instead became queue ups. Consumers started accelerating their migration to the virtual world, increasing their digital adoption, instead of going to the store physically, they would go to the store online.

E-commerce continued to experience strong growth, rising to about 30% year on year. Shopping for more basic needs like food, sanitary, nose masks, and other products related to the pandemic went on the rise, and purchasing less and less from travel sites and agencies, car insurance, and outdoor entertainment. The automobile industry remained strong, perhaps in part because of changes in disposable income and a refocus on the personal asset base.

Surveys found that consumers in several regions shifted more to value-based purchasing, which prioritizes obtaining maximum value for the consumer for the money spent.  eCommerce facilitated shopping around too.

In short, consumers started settling for new patterns of behavior in response to the multiple waves of the pandemic, something we can likely expect to persist. As a result of these rapid, yet continuous and unpredictable changes, customer data that businesses held in their various systems became less accurate and potentially more inconsistent as customers’ behavior continued to change. The result? Ultimately if your business is using data to make decisions the customer experience may be poorer if the understanding of the customer hasn’t changed with the changed context.

Fear and risk of infection will fade over time, but when exactly that will be, we cannot be sure. In the meantime, as consumers potentially ease back into their old ways, habits, behavior, purchasing patterns, your business should remain aggressively resolved to support the current and present environment, the old and the new. All of that is going require you to have the best possible customer data in order to successfully satisfy your customer’s needs in a sustained way. You could continue to just play easy if you have been resting on your laurels waiting for better days, but that’s a risky proposition in the longer term.

It’s been a long rough ride for business in general but some have weathered the storm because they have adapted or already had a robust customer data profile in place ahead of the pandemic. You’d agree, that now more than ever, your business needs to obsess about their customer data management because your business is planning to stick around. Surviving in the game depends on that data.

So far, businesses that have adopted customer data management, have been able to meet customers’ expectations to the maximum extent possible and they’re in a better position to retain such ones even during the post-pandemic era.

Now, is the time to secure your customer’s confidence and loyalty, and what better way to achieve that if not by your customer data management. Pretectum believes it has the perfect customer data management solution to support your business in the journey. Using a hub and spoke approach to data management means that your existing systems can remain intact but leverage a central source of truth to drive improved insights and decisions.

Publish Date: February 22, 2022 3:54 AM


Here is an outline of some facets of a robust data governance program that you might want to consider as part of your overarching approach to customer master data management.

Start with goals and strategy

Put aside the data for now and think more holistically about your business objectives. A good business strategy that understands its dependence and relationship with data helps your business to understand what data you need to have and for what purposes. This in turn will inform your data strategy.

Answer these fundamental questions to guide your strategy:

  • What is the problem you are trying to solve with data?
  • What kind of data do you need, where and when?
  • What is the data literacy of your organization and do you need to improve it?
  • What is your data worth? Justify this proposition with CLV or other measures.
  • How do you exchange, collate, disseminate and control the data you have?

A considered and well-formulated data strategy has a strong vision, clear goals, well-defined success metrics, and compelling business rationale.

Roles and responsibilities

All successful data governance and data management programs including those that only consider Master Data Management as a first step, have to be implemented by people. These could be stakeholders from the business, members of IT, a specialized group of people that form a data management organization (DMO) or they could be external consultants or service providers.

Answer these fundamental questions to guide your organizational definition:

  • Will you have dedicated people for data management or will this be an integral part of the role of existing peoples’ day jobs?
  • Have you committed to your initiative being a business led initiative as opposed to a technology and It led one?
  • Do all the participants in the process understand their roles and responsibilities with respect to proper and appropriate activities and decisions around the data?
  • Do you have assigned data owners?
  • Do you have a decided escalation or triage process for contentious issues?
  • Do subscribe to the concept of “Data Stewardship” ?

Recognizing that part of the responsibilities of people undertaking data stewardship is the creation and handling of the Data Management Body of Knowledge (DMBoK); defining, evaluating, and resolving data quality assessment; documenting policies and procedures ultimately help with transitioning to a more evolved state of organizational data governance.

Defining and measuring success

There is an old adage, often attributed to W Edwards Deming, statistician, and QC expert, that “you can’t manage what you can’t measure”. The same is true of your data management program. If you have not defined measures and are not evaluating those measures, are you in fact managing your data?

Very little data enjoy a static existence, more often than not, data evolves and changes according to the needs and usage of the business. Setting up monitoring of data is therefore one of the key tasks for the teams responsible for data management.

These are the common measures you might expect to see

  • Assessment of Accuracy
  • Evaluation of Relevance
  • Completeness checks
  • Consistency checks
  • Rights and permissions

What you use to perform these assessments and checks is less important than ensuring that they are undertaken regularly and consistently and reported on.

Remediation plans can only be put in place and be executed upon if you are performing these checks.

Data quality measures can include different things such as information like the number of completeness checks, root cause analysis, recurrence relative significance of certain types of issues encountered. Your metrics may vary when compared with other organizations but in some instances, there are standard measures for industry sectors and your peers. What’s crucial is to establish key metrics for assessing data quality and follow through on leveraging them.

Communication and education

A well-implemented data governance program avoids being labeled as bureaucratic and instead demonstrates effective management and use of data through a comprehensive and elaborate communication program.

This means that those people with the assigned responsibilities of data governance need to bring strong communication skills to the table when dealing with people and process issues. Since data governance is often accompanied by business process change or digital transformation, many of the communication approaches will be common.

If this is a new initiative for the business there are a couple of critical communication touchpoints that might be beneficial.

  • Develop a timeline and a schedule for your communication activities and channels.
  • Introuce others to the initiative by way of an executive sponsor in town hall, internal newsletters or communiques.
  • Make use of social media and print media on noticeboards, corporate screensavers and email banners.
  • Clearly articulate business expectations in terms of outcomes – why are we doing this and what expected benefits will we or our customers all enjoy
  • We talked about roles and responsibilities already but reiterate these so everyone understands especially those not a part of the team.
  • Avoid buzzword bingo and jargon in conveying the message and building organizational understanding.
  • Communicate on a regular basis.

The more others understand what you are doing and why you are doing it, the greater the likelihood of success.

Fitting MDM into the big picture

Master data management encompasses the processes, standards, and tools that are used to support the creation and management of master data.

MDM is a cornerstone to data management and data governance. At its core, MDM is the maintenance of the relationships between the master file and all other masters and transactions with the Masterfile for the customer in particular being a key point of reference.

A well-implemented and maintained MDM practice avoids duplicates, redundancy, and inconsistencies.

The long game

Things that are worth doing, often take time, and the same is perfectly true about data governance and the implementation of master data management as part of a more broadly focused data management program. It isn’t something you do once, and then you’re done.

Over time your organization will determine that the true value of data is often hidden in how it is used in ways that were perhaps less obvious at the outset.

Fast-evolving data and data needs mean that the job of data governance never really ends and so your business will need to keep pace with these changes both in terms of how the data itself is managed and in how teams think about the data.

The Pretectum C-MDM is a flexible and adaptable complementary technology to any data governance program with a special focus on customer master data management that can be of benefit to you in your data governance initiative.

Publish Date: January 4, 2022 11:00 PM

Call Centres and Customer Data Management

The COVID-19 pandemic has proven to be a make or break experience for call centres.

Not only was there an increase in calls but there was also a significant increase in the rate of difficult calls and the need to escalate them. That’s at least according to a 2020 study by Harvard Business Review. Difficult calls increased by 50% overall.

Customer service employees, therefore, had to deal with more calls and more complexity in the calls and were further challenged with having to go into under-manned call centres due to social distancing measures or were having to work from home too.

NBC and Telemundo survey respondents suggested that work conditions had worsened during the pandemic and more than half of callers were unable to resolve their issues.

Several issues were identified in an article as particularly problematic

  • Protracted Call Wait Times
  • Continued WFH circumstances
  • Call centre agent recruitment and retention
  • Low customer satisfaction


There is no single bullet that will solve all of these issues but it can certainly be argued that data probably represents one of the key aspects of how call centres engage with customers that could help.

Companies that rely on call centres for customer interaction have the opportunity to consider how they deal with customer master data in particular and how that can be aligned and integrated with call centre operations.

In the current era, a call centre that can’t identify, queue and prioritize a customer based on CLI is missing a trick in prioritizing higher-value or even known customers. To do that of course requires the orchestration of integration of the CLI with the CRM or CIC software and in all likelihood a customer MDM (Master Data Management) system like the Pretectum C-MDM. Of course, there is always the risk that the number from which the caller is dialling is unknown or blocked but surely when the number is known or identified, there is value in leveraging that information in queue management.

WFH (Work from Home) is quite possibly the new normal. We’ve seen the progressive transition to telework wax and wane over the past quarter-century as networking and telecommunications infrastructure has improved but these days most people who would be office-bound or work in a call centre; likely have fairly good broadband access where they live and even the costs of teleworking equipment now make this a much more affordable option than it was in the past. Call centre heavy business will have their eye on the ball here and be looking to enhance and improve the ability of their staff to work from home and the technology and infrastructure shouldn’t be a hindrance in achieving this.

Recruitment and staff attrition is a thorny subject because some individuals thrive on the social interaction associated with actually working in an office and might not cope as well in WFH from home circumstances. However, if your business has coordinated the elements of WFH and yet allow hybrid working approaches say where those who really want to divorce home life from work life can, then it becomes possible for staff to still achieve their top line work objectives and still have a work-life balance that they feel is acceptable. Give them access to the right levels of data that give them the feeling that they are empowered to actually help customers, and retention becomes less of an issue because staff are likely to appreciate the ability to work where they want in the circumstances that they prefer.

Finally, if you manage to orchestrate the best implementation approach for call queuing; provide staff with all the necessary customer data via your MDM integration with CIC and CRM that helps them be the best that they can be, in their jobs and then augment their lifestyle with the ability to work where and how they prefer it is likely that preferred existing and new customers won’t have to wait so long to have their calls answered; will be responded to by staff with some existing knowledge and insight about the customer and are likely to help solve issues faster and with improved success rates.

Publish Date: December 8, 2021 2:38 AM

The importance of customer data

The significance of the underlying data of our daily lives seems never more important than it is today. The rebranding of Facebook as a new entity called "Meta" seems to bear this out. In some sort of second-life like realm, we may well be represented beyond the simplicity of the online presence that we have today. The future is likely to be wholly immersive, and possibly quite possibly dystopian.

One can only imagine what the likes of George Orwell, Aldous Huxley and HG Wells would make of it all. It's hard to imagine ten years ago what we have and leverage today in trying to maintain a digital relationship with our customers.

There's a call for us to unsubscribe from social media, grade our social media in terms of privacy and social responsibility and to uninstall Google Chrome and while this is all very well, the reality is that if you're on the buy-sell side of consumer data this is not a good situation at all. The battening down of hatches by Apple, Facebook and Google ecosystems ahead of the 3rd party cookie crumble  doesn't bode well for the future good understanding of the customer without marrying one's strategy to one or all three of these behemoths.

Interestingly, it also doesn't matter if you are selling to other businesses or Joe Public. All the data essential for companies to shape customized experiences and offering which you had hoped would set the stage for innovation have now been put in jeopardy as a result of privacy concerns. If the individual you want to promote your business or products to, doesn't buy into your holding and handling of their data then it will be a rocky road ahead.

Taking aim

The number one objective in the future, and even today, is going to be ensuring that the data assets that you have are in the best possible shape and that they are appropriately yours and suitably managed for optimized targeting.

With tightened marketing budgets, there will be the expectation that you should sweat the existing data assets more, and spend even less on advertising. A mentality of "make the most" of what you already have.

As a consequence, businesses are focusing all their energy on their data. Data that is harvested from existing activities, should be tweaked and adjusted and then reexamined to derive insights for the next round of activity.

There are many tools available to help with this, but at the core of it all lies the need to consider the mastery of the customer record itself. Whether that mastery is done inhouse, outsourced or crowdsourced shouldn't really be much of a concern. What should be of concern is how current that data is and whether it has enough attributes to be useful.

Returning to that constrained marketing budget, you only want to likely target people who are interested in what you have to offer, but how will you optimally do that?

Playing to an audience

Through the elaboration of personas it is possible for every business to understand their optimal customer both as a consumer, user and buyer of their goods or services. While this is typically a product and product marketing function it could also be a pure marketing focus depending on the nature of the business. Understanding what the Jobs to be Done are and understanding who the products and services are targeted at will help you in segmenting the people whose data you have and understanding feature form and function that aligns with their needs, expectations and pocket-book.

The most appropriate data in your systems of record will allow you to hone and refine your message and help to ensure that you are focused on exactly the right audience. It shouldn't be underestimated how many businesses waste precious marketing dollars on targeting people who have little interest in what they have on offer.

A brave new world

Huxley described how science and efficiency could neutralize emotions and individuality, where there are no lasting relationships. This is all exactly the opposite of what our businesses need. We want to use the science (of data) and leverage the most efficient ways to actually elicit emotion and target individualistic messages to form long lasting relationships.

Centralized master data management like that offered by SaaS and PaaS solutions like the Pretectum Customer MDM (C-MDM) suggest ways to gather data and new metrics to track B2C and even B2B relationships in a world of innovation around customer data. Technologies like these provide more ways to track and report key data to find a clear path to focus all business efforts on the right prospects and customers.

The main obstacle will be balancing customer privacy with the businesses need to know. Companies will need to avoid being intrusive and holding unconsented data. While a lot of this might be considered marketing issues, the reality is that everyone in the company is responsible for all the data . If you gather less data or show customers exactly what you contain in your systems as 'their' data then customers may decide to choose you for that transparency. The tradeoff may be that you have fewer records to work with, but only time will tell.

Where does your business stand on the right level of customer data to hold, and what is the quality of the data that you currently maintain and want to maintain?

My thanks to Uli Lokshin for his review of my piece and suggestions.

Publish Date: November 8, 2021 6:42 AM

Digital transformation depends on effective customer data management

There has been an incredible amount of technological change that impacts our everyday lives. The advent of the internet, social media, mobile and more, have changed how customers interact with brands, hence the need for change from brands.

It is the need for that change, that drives effective digital transformation.  

Digital transformation can mean different things for different organizations. It can mean launching e-commerce or a mobile app. For some, it could be about improving the web experience.

Whether you’re already an online business that needs a transformation initiative to engage markets that have not been targeted or an offline brand that realizes that a negative digital brand experience can be damaging for customer experience, loyalty, and reputation, you’ll be considering some kind of digital transformation, even if you don’t refer to it as such.

One of the many goals of digital transformation is to create insights and data points that will improve the customer experience with the intent of increasing sales, loyalty, and brand advocacy. A defined data strategy works to connect all your data, online and offline and defines the steps needed for advanced digital transformation. 

You’ll need to keep in mind, though, that tools or platforms don’t automatically make for an effective digital data strategy.

Some 70% of all initaitives do not attain their intended goals, close to $900 billion has been witnessed in potential wastage as a result of initiative failures. So it’s not enough to simply say you’re going to implement a digital transformation. To yield results, you need a holistic transformation approach to identifying where the right digital tech is needed, fed with the right unified accessible data, accompanied by a clear data strategy. How could you possibly achieve this?

This is where customer data management could make a grand entrance. 

Customer Data Management, Benefits 

It is said, data is fuel for digital transformation initiatives. Superior customer data management, in particular, ensures the supply of that data fuel is enabled and activated. If your customer data is consistent, well managed, and directed to the right place, at scale and in real-time you have a better chance at achieving an all-around improved view of each customer. 

  • A single source of truth– Your organization likely has several different systems that store different data. Without effective customer data management across these tools, you’ll be required to enter data manually, which oftentimes leads to data capture inconsistency. A customer name might be entered in a system in the format “CAMERON LEE” and in another system as “LEE CAMERON” – which one is correct? This kind of transposition inconsistency and possible errors, can lead to a lot of wasted time and a potentially poor customer experience, as you might end up sending multiple marketing emails to slightly different names, yet ultimately the same person. It is therefore important to converge on a single system model or a single source of truth where each customer data is managed centrally and shared or accessed by the surrounding systems. This ensures consistent, enriched, and up-to-date data information, no matter what system the customer data appears in. 
  • 360-degree view of each customer– Customer data management can help build a 360-degree view of key business information about the customer to allow you to take full advantage of your organization’s data, for better business outcomes that include; 
  • A compliant digital customer management strategy
  • Optimized and correctly calculated lifetime customer value
  • An improved and customized customer experience 
  • Improved customer onboarding and retention management

If you adopt customer master data management, your business is likely to do better, statistically, it has been found that digitally mature firms are 26% more profitable than their peers, they generate 9% more revenue, and achieve 12% higher market valuations than other large firms in their industries.

Getting ahead in terms of improving your relationship with your customers and dominating the markets in which you operate requires effective customer master data management. Having the pole position at the start of the race allows you to get ahead of competitors. With an ever-evolving digital world, you don’t want to delay your execution plans until later, the time has never been riper to evaluate what a Customer MDM can do for your business today!

Publish Date: October 28, 2021 6:28 AM

Customer Master Data Management in the Cloud

There’s nothing particularly exotic about cloud-based applications and the same is true of master data management solutions in the cloud.

The growth of cloud services, cloud data, and cloud usage continues unabated. We should expect, that as long as good internet connectivity infrastructure is available there will be a continued support for cloud based systems and in fact cloud based solution adoption should grow.

More and more organizations are adopting cloud computing infrastructure to afford greater business agility and get access to the best available technology of the time. The adoption of cloud infrastructure like CRM in the cloud not only holds the promise of improved business efficiency but also the benefits of improved economic value and ROI.

In most cases, cloud solutions are well architected, unencumbered by legacy technology problems and present themselves as having a lower cost of ownership and wide accessibility to business stakeholders.

Businesses have been slow on the uptake of cloud-based MDM though with Gartner estimating that only 6% of all the companies that they talk to, have cloud-based MDM solutions in use.

Cloud-based Customer MDM presents itself in the shape of software as a service (SaaS).

This means that organizations do not have to incur the cost of the hardware and the software associated with it and have no application or hardware maintenance to pay.They pay one fee according to the size of the usage profile that they have, either in terms of records, users or both.

The organizational and financial cost of provisioning on-premise and captive hardware is sometimes prohibitive enough for organizations to effectively ditch capital expenditure on a system and instead invest capital budgets elsewhere in the business. They might instead choose a "pay as you g(r)o(w)" model which a SaaS application will support.

One of the reasons Gartner’s observation of 6% of adoption may be so low, could be tied to the fact that there is remains some anxiety around the security of cloud-based systems and a reluctance to store sensitive proprietary data outside the company’s firewall.

Platforms like the Amazon Web Services (AWS), Microsoft Azure and the Google Cloud Platform are deployed with the best resources available and a high degree of automation and monitoring.

Security is a top priority for these infrastructure providers in order to provide top tier companies and organizations across the globe, with the right level of secure and robust compute to meet their diverse needs.

Data hacking is regrettably a continuous threat but since the mid-2010’s on-premise system attacks due to inadequate software maintenance and control regimens have highly outnumbered the incidents of cloud attacks.

The cloud attacks themselves have had nothing to do with cloud security vulnerabilities, they have largely been as a result of poorly implemented data controls or internal bad players, so basically inside jobs.

Numerous customer relationship management (CRM), Enterprise resource planning (ERP), customer data platforms (CDP) and marketing automation (MA) solutions are cloud-based. Most notably Salesforce CRM and NetSuite ERP are exclusively available as cloud solutions.

Cloud based MDM (Master Data Management) solutions are also available and these include well known solutions from Informatica, IBM, Oracle and SAP as well as newcomers like Pretectum C-MDM for customer master data management.

Cloud-based SaaS applications like the Pretectum C-MDM deliver new functionality on an almost continuous basis and for major changes, you can decide when to upgrade and avail your business of new functionality.

Upgrades are seamless and generally invisible to clients until they are actually completed.

Legacy versions are typically only supported for a limited time after the general availability of new functionality and enhancements to reduce the costs of operations support.

Your organization should therefore be prepared to move with upgrades as they become available to ensure that you are making use of the newest version of your customer MDM. Updated technology or newer infrastructure is available for use via the cloud in a completely transparent way.

In considering a cloud provider, remember that not all cloud providers offer cloud hosting outside the US.

This is important when considering Customer MDM particularly in the context of Europe’s General Data Protection Regulation (GDPR).

Also, consider that US safe harbor agreements are problematic with the storage and transferral of EU citizen data outside Europe.

If you are using on premise systems that contain Personally Identifiable Information (PII) data then you may need to always store that data on-premise in the country of origin, this may represent an IT burden to your organization.



Publish Date: October 5, 2021 3:10 AM

Making the most out of customer data

To run a customer marketing campaign or undertake any customer analytics, you might consider a variety of customer-related data at your disposal.

There are several types of customer data that you might consider but what we will focus on here is how you can consider the incorporation of aggregates into your customer master to help influence and inform your decisions and actions as a business.


Transactions are easily understood. They occur every time there is a value exchange between your business and the customers. Every additional transaction deepens the relationship that your business has with the customer and likely also influences if they will be a customer again. While you may have a particular interest in the tastes and preferences of the customer.

At the aggregate level, it is useful to know how many times the customer has transacted with you, the average value of each interaction and the frequency between transactions.

By having these attributes tied to the individual customer master you can calculate the lifetime value of that customer, perhaps infer something about their preferences and how they might respond to certain events or promotions. Your CDP or eCommerce platform may have this information but would this be of value to other areas of your business?

Service and Support

If you sell products that are often associated with a service element then, this is an aspect of that can likely also be easily understood.

Every time the customer engages with a representative of your organization around a service or support elements associated with the goods and services you provide can inform your business about the levels of the relationship that exists between the customer and your business and its goods and services. Some sort of survey assessment at the conclusion of every interaction can also tell you whether this customer is net promoter or detractor of your business.

This information could be useful in your next engagement or outreach event associated with that customer. Insight into contacts, can help to convey a closer understanding and form a stronger bond between your business and the customer. Consider how you could incorporate survey, support ticket, warranty and other aggregated information into the customer master

Social media

Your CDP platform likely contains some understanding of the social media aspects of your customers but it is likely that there is nothing on the CRM or ERP system.

If you collect social media data you may be able to see which platform is the most popular among your customer base.

You could consider this in influencing your marketing campaigns and also decide what type of social media platforms and posts perform best and what time of day. Using social media information can influence what you create and publish for maximum reach.

Social media is a critical avenue for certain types of brands, and is now less of an area of exploration and testing, and more a necessary line item within the marketing plans for brands.

Your Customer MDM should be configurable to take the aggregations from these other sources and incorporate them into your Customer master ready for syndication to whoever needs the data

Publish Date: August 30, 2021 5:36 AM

Maximizing CRM & ERP Customer Master data Value

Most companies have customer master data somewhere in their systems. The challenges with the customer data is that many companies find it difficult to maintain that customer data and ensure that everyone that needs access to the customer data, in fact has access to it.

Access to a version that is the latest and greatest form. It is suggested, in various pieces of research, that as little as 20% of business user time gets to be spent on actually using the data. The remaining time, according to HBR, is spent seeking out and preparing the data.

Data is central to how we run our businesses today and customer data is often slap bang in the center. Global market intelligence firm International Data Corporation (IDC) projects spending on general data and analytics to reach $274.3 billion by 2022, you can assume a large chunk of that will be on working on customer data.

Customer data, wherever it is found, is also often contaminated with additional data that is not necessarily pertinent or current. The best solution to having exactly what you need, is the implementation of customer master data management (C-MDM).

Having a C-MDM creates a common definition and a single view of what a customer is, by centralizing data and creating governance, compliance and security.

With the infinite number of possible data combinations and the average number of systems that may be involved (an average of around a dozen or more), any C-MDM project can be unnerving. Getting started can be made easier.

Here’s some steps to make your customer master data management initiative a success.

Organizational Master Data Maturity

Any master data management project’s starting point depends on where the business falls in the enterprise data management maturity model.

Every company is at a different stage and very few are start from scratch or have only one source for the ‘customer’.

Here are some clues to organizational master data maturity

  • Business Divisions are focused on products, services or functions, so they don’t share customer data with others even if there is overlap or benefits

  • Companies may have great customer data, but have inadequate control and governance over that data, so data gets duplicated and potentially goes stale.

  • Non-organic growth activities result in acquisitions of data from elsewhere but this data may be misaligned, inadequate or simply not integrated

  • Meteoric business growth leads to systems not being able to adjust in alignment with the needs of the business, resulting in data proliferation and islands of information.

So, what are the choices available to you, to remediate these kinds of problem?

Research and Identification

Identify who should be the custodians of the Customer Master and which pieces they should be responsible for. This will inform you on the controls and processes you have around customer record creation and maintenance.

Identify who uses the customer master and for what purpose. They could be using the data to engage in outbound customer marketing, billing, service or almost anything

Take an inventory of all the customer data repositories that people are curating or maintaining or using. This will inform you on your data control and proliferation changes and also hopefully give you a statistical count on how many raw records you have.

Define the ideal customer master

Create one or more common definitions of what a customer is and what a customer should look like (we recommend you start with just one). Consider then, the different lenses through which different business units, view and leverage the customer record.

Looking at the consumer customer record, consider that even a consumer may have many different pieces of contact data, emails, phones and actual addresses, some of which are for specific purposes. Home, work, delivery etc.

The idea is to identify data attributes that will be common to the majority of your customers and constitute the customer data point definition – this will become your customer master data model.

Get rid of the duplicates and bad data

After you have a master data model, you’ll want to ensure that your data is accurate and free of duplicates. If you have customer information in multiple systems, the chances are good that you will have duplicate customers with different information. You need to correct inaccuracies and converge on a unified view of the customer record. You will also need to clean up those records and report regularly on the effectiveness of your efforts!

Access and Control

Some sort of governance program will help you control your master data model and in particular the adjustments that will occur to it over time. You’ll also need controls baked into the model and the capture and maintenance processes to keep your data clean and accurate. Good governance ensures that customer data can be trusted and it provides accountability as you strive to keep it up to date and limit the control of and access to the data.

Some final thoughts...

Consider a C-MDM that helps you define your participants in the master data curation process, the solution allows you to define one or more models for what you consider the ideal customer master and then it further allows you to establish controls and measures around what the data should actually be. Look for a C-MDM that goes a step further, one that also allows you to physically build up your repository of customer records and syndicate them to whichever systems or users need the data in a hub and spoke approach using APIs and integrations.

The goal of any C-MDM is to create a single place for all your customer information, a single data source that you can use to inform your business decisions and systems. If you consider the workings of customer relationship management (CRM) systems, ERP’s and CDP’s, the value of a C-MDM is clear. It is not a transactional system, it is a master repository with controls.

Many companies think that their shiny new CRM, ERP or CDP will solve all their customer master data issues but without a solid understanding of customer data and a strategy for how it will be managed. When you move to those new systems you can often compound the problem rather than solving it by creating yet another system with its own data repository and governance rules.

Publish Date: August 25, 2021 11:39 AM

Digital Transformation and the finance function

Calls for digitalisation has been going on for some time now, across all industries, from government agencies through to the latest vaccination certifications as a result of the COVID-19 pandemic. There is an erroneous belief though that everyone is prepared to embrace all that digitalization has to offer.

Regrettably, one of the last miles of resistance may be the finance function. While other areas of the business are focused on new technologies to drive better insights that support their business – is the same true for the more conservative finance function?

IDC research suggests that only about half of the “best-run” midsize organizations have a finance function that appropriately understands how significant data quality and data, in general, is, in order to be timely, accurate and useful. Constellation research from 2018 suggests that “DX” projects are often led by the CIO in 60% of small and midsize companies, not by Finance despite Finance often being the final decision-maker.

Finance leaders in business appear to know that cool technologies like AI and ML can help in breaking traditional organizational data silos, that they can support information sharing and improve overall operational efficiency as well as reduce errors in handoffs and accelerate decision management all to the benefit of the customer but do their teams know?

The finance operations disposition seems to be one of “Why change what isn’t broken?” This perspective drives to the heart of the fundamental problem of data ownership and responsibility. The finance function is typically viewed as an operational overhead and not a strategic or competitive advantage or fuel for organization growth. While the business as a whole, favour the benefits associated with fast and easy access to real-time data to respond to a changing business landscape, those clinging to their monstrously complex, macro and formula laden spreadmarts.

For many, shared spreadsheets still remain the most ubiquitous method of fast and easy data distribution between departments despite all the inherent risks with using them as sources of record.

There is a valid argument on both sides of the fence. The short-term view is that the environment is so volatile and ever-changing, that heavy reliance on protracted big-bang projects will end with a half baked solution that will simply add more friction to analysis, insights and reporting. Big transformation projects are risky often with a poorly understood return on investment. Another argument is that finding the right technology to meet SMB needs is hard. 

The flipside of the argument is that the ever-growing pile of electronic spreadsheets makes data management impossible. They’re disconnected from the original sources, get out of data and are easily manipulated in such a way that they can present entirely the wrong picture. In addition to the logistical nightmare, there is the potentially unnecessary reliance on IT support for critical business insights, slow and inefficient processes, and poor decision-making outcomes.

Adoption of technological advances, especially in the SMB and particularly by their finance teams must be the way to deliver timely actions, improve decision-making accuracy, and provide fully informed insights. It only takes a few innovations to deliver benefits that will speak for themselves.

Those innovations, once operationalised will help the finance function get ahead of the audit and compliance anxieties that often plague finance. A recent Forbes piece, suggests that having a DX strategy places your business in a much stronger position and show more resilience than those without one.

Deliver these without detracting from overall business efficiency, data quality and keep up with organizational and business growth and the resistance to adopt and embrace a new way of working will dissipate.

Publish Date: August 15, 2021 10:23 PM

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