The acronym MDM stands for Master Data Management.
The realm of customer marketing is at the heart of Equancy’s expertise and is related in multiple ways to customer data issues and in particular to master data. Indeed, customer data is essential for implementing relationship marketing and for offering the customer a unified experience, especially in an omni-channel environment. So, how can you reconcile the digital customer with the physical customer in the store, what are the rules for integrating customer data from a central system with that gathered from a retail network? How can we achieve a 360° vision of the customer in an increasingly digital world with multiple interaction points, identifiers which vary depending on the channel and physical points of sale that may be competitive with each other (franchises, for example), and which, in fact, do not share customer data with rival sales points.
The role of MDM
MDM for customer data is a repository of master data. At the heart of a customer information system, it interfaces with data sources via ETL (Extract, Transform and Load) solutions, which as the name suggests, extracts data, transforms it into the required format and uploads it to the MDM system.
So, the MDM system is a sort of database of customers?
Unlike a database, the MDM system does not stock a complete set of customer data but only the “master” data, i.e. data that is important to the company’s core business. We often talk about the GOLDEN RECORD. For a MDM system set up to deal with marketing issues, the scope of master data includes customer identity data (last name, first name, client identification), contact data (addresses and other means of contact) and opt-in and subscription emails. Other data may be added: purchasing data, a segment, an indicator of customer value, customer engagement scores vis-à-vis the brand… depending on the company’s customer issues and the role assigned to MDM.
Furthermore, the MDM system provides a range of important services such as identification, real-time data queries, and configurable rules for integrating data regarding sources and data redistribution …
Amongst these functions, identification or recognition, is of paramount importance: it makes it possible to identify a customer, who is already registered in the system thanks to multiple recognition criteria (name, email, telephone, contract number,…), and if the customer is not known, the MDM will assign a unique identifier throughout all systems. It identifies relationships between individuals, creating notions of households, groups of individuals endowed with specific privileges for example …
Examples of different identifiers which could be used at various customer contact points
|Customer interaction channel||Infosys tools||Customer query identifier|
|Call centre||Customer care solution||Name + Post code|
|Store check-outs||Check-out tool||Client N° / Name + Post code|
|Website||CMS||Email + Password|
|Social networks||Facebook Connect / G+ connect||Social network ID|
The functions of data distribution, sharing and visibility are crucial for companies using an external distribution network, as the MDM system defines the data which are visible to each actor (agent, distributor, sales point) regarding business constraints or data ownership. The MDM system can send alerts to selected contacts when customer data is updated (for example if customer services changes a postal address, the agent can receive a notification).
Data quality processing
The MDM system is nearly always supported by a data quality management module, the purpose of which is to automatically clean and correct data. For postal addresses for instance, we speak about standardization and validation.
The data quality module also manages the strategic functions of deduplication and record merging, which are essential for maintaining the quality of the base. It can also call upon external solutions for enriching and processing data.
The processes of deduplication and record merging cannot be entirely automated and may sometimes require manual processing, this is the role of the data steward, a veritable guardian of data and data quality, he or she manages data quality issues left unresolved by the cleaning rules/the automated merges, monitors the data quality scores and analyses rejected items. The data steward normally works in an operational department but the position is really at the crossroads between business teams and the ISD.
The data steward handles requests from corporate departments which don’t have the same level of rights over the data as he or she does; indeed at the various stages of customer interaction, not all users have the right to modify or to create customer data: creation, modification, deleting, consulting, and record merging.
Who is MDM for? How to go about it?
We can observe that MDM systems for customer data mostly concern big corporations facing B2C issues, in sectors as diverse as insurance, banking, automotive or retail…
In general, companies for whom the customer represents their core business (retail for example) have an ERP which integrates the management functions of MDM.
In terms of technical choices, while some companies opt to develop solutions in-house, this can often be a long and complex process; there are also off-the-peg solutions available. Some of our clients particularly those in the specialized retail sector, are seriously examining this issue.
Those who have already taken the plunge, recommend step-by-step implementation, with a limited scope of data at the outset, which can be enlarged as the project progresses. The key success factor for this type of large-scale project is to deliver rapid solutions in an ever-changing context.