What do you have? An ERP, a CRM, a CDP, a loyalty system, a webshop? Chances are if you are in a business that has been around for some time, you may have literally dozens of systems (including spreadsheets) that contain customer data.

When your data repositories are siloed and fragmented, held in different systems with a variety of purposes in mind, it is difficult to converge on a single understanding of who and what the customer is and consequently, it is even tougher to work on an optimized customer experience across all the systems and repositories that your business may have.

So where does all this tie into customer data management you might ask? That answer may lie in your understanding of what customer data management really is. Vendors will tell you that their technology stack is customer data management. That might be true, but it might not be true for your organization. Ultimately, customer data management isn’t exclusively about technology, it is also about business practices (think processes); roles and responsibilities (of people), and of course a bit of technology to help control, evaluate, track and distribute whatever it is that your team(s) are working on.

Compare the differences.

Focusing on the people

Your business may be in the luxurious position of having a data office and a chief data officer (CDO). More likely it has a Head of the DMO (Data Management Organization). Whichever it is, doesn’t really matter that much. Either way, if you have people with job titles that contain the word “data” and they’re not lowly data analysts, then your organization is likely well-placed maturity-wise. It is likely clear who is in charge of the data and accountable for resolving issues.

If you don’t have this kind of structure then the fundamental question is going to be, who is responsible and accountable for the management of the customer data entity. This could be the role of people in Sales, Marketing, Service, or Support; but ideally, it isn’t IT.

Setting standards

There are a number of solid industry standards that your organization could consider in relation to customer data management. The Data Management Association (DAMA) International defines data management as a domain aspecific term as the “planning, oversight, and control over management (sic) of data and the use of data and data-related sources.” That’s a broad expectation for the objective of managing data assets.

Master data management (MDM) is a sub-discipline and requires some very specific data governance activities namely: agreement on people that will be accountable for the mastered data, agreement on the processes and policies that will be implemented and applied, and agreement on the tools and technologies that will be applicable.

One should also not be confused by the subtle but important differentiation between governance and management.

Governance establishes policies and procedures while management enacts those policies and procedures to compile and use the data, ultimately in service of the business needs. So while your business may have a governance policy, does it have a way to execute that policy with a management approach? It could be manual, but it could just easily be automated or semi-automated.

Putting the gears in place

There’s a view that breaking down the silos or at least overcoming the limitation of silos is the first hurdle to address in any organization.

You may be lucky, if your organization is small enough, this could be a deftly meted-out edict from the Chief Executive Officer but the real question is going to be how do you follow through on that intent in a meaningful and productive way?

There is a school of thought that suggests that you should try to corral all the business functions (sales, marketing, service, support, accounting, eCommerce) and make sure that they are all aligned, but that may be impractical or unnecessary.

What’s more important is knowing that those divisions exist and knowing what they have and understanding what the commonalities are for each of them. A well-implemented and well-considered approach to Customer data governance doesn’t have to hamper, hinder or detract from the way that they currently gather and manage their customer data but what it can do, is it can help make their process and data capture activities a wider audience.

Compliance serves as an important aspect of the end to end process of customer data management and this is not easily achieved if there isn’t a clearly designated boundary in relation to who owns which parts of the data puzzle. Further, if you don’t actually have a centrally managed repository of customer information how on earth do you service things like Data Subject Access Requests? With a CMDM, Pretectum believes it is much easier.

If you’re curious about the implementation approach then you’re recommended to have a read of a Pretectum piece on this very topic – getting started…

Why bother?

The “why bother” question, is very important to respond to, and I’ll try to do that here In the general schema of things you might wonder why the marketing team would need to know every shipping address a customer ever used. You might also question why they need to know whether the customer is a pre-pay or postpay customer? The key may lie in the convergence of these two pieces of data accompanied by perhaps the volume of business that the customer generates for the business. Consider that piece of insight as to the CLV.

An effective marketing campaign, for example, is one that has the highest likely yield or return in response to very targeted and specific measures and objectives. Customers may live in one place and take delivery in another. They may even live in one place, take delivery in another and yet shop in a completely different place (in-store pickup).

Customers who prepay might yield a greater or lesser margin for the business as compared to postpay and you may in fact have a campaign that is looking for prepayers based on where they live rather than where they shop. The power of analytics for customers is only improved when you have as much data as you need, easily accessible and unified to those that need it most.

Identity at the core of customer engagement

We’re not talking creep intrusive stuff here, though understandably that might be of concern to some. What we’re considering here is the fact that a collection of anonymous events, wherever they come from, is much less useful than an activity that paints a useful picture of the interests and tastes of known customers.

The alternative is clear, every sale made, a deal brokered or engagement had, is either serendipitous or is part of a larger and more elaborate deliberate business plan.

You want to remove the luck and chance elements and start putting a little more predictability into your deliberate behaviour and shaping the potential customers and markets that need to underpin your business growth plans.

Data, and Customer data, in particular, is often considered in the context of how it might inform digital transformation or how much of a burden it represents in terms of privacy or compliance. Those are all good reasons to consider it, but data for insights which can help to guide business growth plans, reduce organizational friction and elevate the personalization of the customer experience should actually be front and centre to why customer data needs more of your focused attention.

Pretectum thinks that centralized customer data management, the kind provided by a CMDM like that offered in the cloud by Pretectum, is one of the best ways to wrap all those diverse requirements up and package them for the general use of your employees and the technologies that they use, support and deploy.

A deliberate Customer Experience

To improve the customer experience, your business needs to be able to recognize the individual and spot their omnichannel interactions with your brand. You need to use identifiers, traits and potentially a slew of other aspects of the customer profile to do this. All of that requires data.

An incomplete customer profile limits your ability to categorically identify the customer when limited data is on offer. An inconsistent or downright wrong profile attribute from any given source can make a truly unified understanding of the omnichannel customer well-nigh impossible.

Industry analysts, Gartner, suggest that your customer data management processes and infrastructure must be flexible and adaptable. Flexibility lies in the ability to take the single dimension of customer and facet it according to the needs of use. Can you do that with what you have today?

Pretectum feels that the rigidity of CRM and ERP, which are largely for transaction processing, make this difficult.

For CDPs, there are overlaps but the greatest challenge is likely found in the fact that CDPs are generally targeted at a narrow group of organizational users for whom the capabilities of the CDP are either too prescriptive or don’t cover enough divergence in terms of alignment with the individual business user’s need.

This is where CMDM may serve as a better hub and datastore with connectivity to all and any systems you might have through a variety of integration methods.

Contact us to learn more about how CMDM may be a great addition to your data management landscape.