Delighting the customer by driving better customer experience is the holy grail for all businesses, and Retail is no exception. In today’s ever changing dynamics of consumer buying behavior and various engagement touch points, it is imperative that organizations have a defined strategy and data driven mechanisms to manage the customer data. To build a stable foundation for Omni channel engagement and presence, one needs to address aspects of Customer Master Data Management.

Classically MDM is defined as comprising a set of processes and tools that consistently define and manage the non-transactional data entities of an organization (which may include reference data). MDM has the objective of providing processes for collecting, aggregating, matching, consolidating, quality assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the on-going maintenance and application use of this information.

MDM can help retailers maintain focus on the customer in today’s multi-channel retail environment, and the resulting benefits - customer-centricity with a single, consistent view of each customer; correlating data across channels for more effective engagement and cross-sell/up-sell; tapping into social sentiment to drive customer loyalty and sales; helping increase the speed and number of new product introductions; synchronizing information within the enterprise and with external entities.

As data is being shared and shuttled across more and more systems, would it not make sense to have a centralized philosophy and approach to manage/share all of this data? How many silos have you built? Maybe it is time to break down those silos and consider an MDM approach to your data.
Retailers today are looking for ways to offset increasing competition, pricing pressure and operating costs. As always, the focus is on the customer. One is constantly looking for ways to match the right products with the right customers to create a purchase. But when you are dealing with more than one ‘version of the truth’, it’s difficult to know which choices to make – whether planning your assortment or routing products through your supply chain.

Gathering accurate customer and product information is harder than ever for today’s retailers. The customer’s habits are continuously changing; for e.g. shopping style, shopping pattern, preferred channel for shopping, and other aspects. A single customer might use different channels for different purchase - preferring to browse the store for a new television and shop the Web to order DVDs, for example.

When retailers can deepen their knowledge of the customer across all of today’s proliferating retail channels, they can strengthen customer loyalty, increase share of wallet, minimize operational costs and maximize profits. It sounds so simple – so why is it so hard?

It is not uncommon for a retailer to have a set of systems for retail point-of-sale, another for e-commerce and yet another for the call center, with information entered and stored differently and in different formats in each case. Given this fragmentation, it is no surprise that it is challenging to coordinate marketing, sales and customer service across Web, brick-and-mortar and call center operations.

To overcome this difficulty, retailers need a way to leverage a single ‘golden version’ of customer data and other data by automatically recognizing and resolving data duplicates and conflicts across multiple systems. Creating a holistic view of the customer by relating customer data to other information such as products they own, retail channels they prefer and household relationships that can drive further sales.

MDM is all about creating complete and authoritative business views, including customer views. It is critically important to understand the value of each customer. MDM enables this by tracking key attributes by resolving data conflicts across data sources. If you want to ensure a consistent customer experience or engage in customer segmentation, MDM can be a key enabler by helping improve the quality of data and by synchronizing data across all its sources to eliminate inconsistencies.

Let’s take the example of a multi business operation having multiple loyalty programs. One approach would be to replace all of the existing loyalty programs with a single program for the whole group; but this would have limited the flexibility for each brand to operate independently. Instead, a solution that could help stitch together all the data from various loyalty programs and create a golden view of each customer would be preferred. Equally important is the ability to match existing customer records in all of its loyalty applications, quickly and accurately. With multi-million unique customers who are members of various loyalty programs, this would be almost impossible to achieve through manual matching; but with advanced matching algorithms, automation will avoid the amount of manual intervention required.

Adopting MDM is a journey that will involve assessing ones data sources and consumers, defining the data owners and attributes, capturing the data and de-duplicating the same and finally ensuring that the channel applications leverage the One View of the Customers for better decision making.