Knowing your customer, and now every individual customer, is core to taking key decisions and developing strategies and improving products, etc. to directly or indirectly improve your top line or bottom line.
In traditional Analytics, customers were segmented on various vectors and combinations like loyalty, usage, average revenue, life time value, visit frequency, etc. and strategies and offerings were rolled out at a segment, or in more mature cases, at micro-segment levels. This was perhaps effective till such time channels and business models started to evolve and change with Digital Strategies and Transformations coming into play in an enterprise.
While a key part of Customer Experience Management is about understanding the Customer Impacting processes and Interaction levels based on the Industry specific customer life cycle and touch points (a top-down approach), knowing every individual customer has become an imperative now (bottom-up approach) and not just knowing the customer from a demographic, geographic, transactional, survey based or web based enterprise level characteristics and behavior, but including the digital behavior and influence on social platforms, mobile applications, forums, blogs, etc.
Hence the combination of the Top-Down and Bottom-Up would enable an optimal Personalization, Business Efficiency and Innovative Business Model led Customer Experience Enrichment.
Therefore, while Social MDM for Social CRM was about mashing up Enterprise Data with Customer Social Data, Digital Master Data Management is going far beyond Social MDM, which was limited to analysis of Social Networks and Social Behavior, to include all Digital Platforms and Properties to get a rich and diverse understanding of the customer including their behavior, preferences, dislikes, network, etc. which helps not only in enhancing the customer experience but also providing newer avenues for revenue generation via better cross-sell / up-sell or for new profitable customer acquisition, growth and retention, etc.
The challenges of knowing the customer outside the enterprise includes, but is not limited to : Incomplete Information such as Demographic details missing, Contact Details (email, phone, etc.) missing; Multiple or Duplicate Identities including multiple profiles, emails, etc. or common profiles used by multiple users; Incorrect Information in the form or Fake or Aspirational or Astroturfing profiles, unintended typographical errors, etc.
To add to the above, data will now come to you from Web Forms, Log Files including Clickstream data, Voice and Video Interactions, Images, Emails, Mobile Applications over and above your other Digital Properties and Public Social Platforms. In all of this identifying the variables that define the uniqueness of the customer and even help in house-holding, etc. are critical.
A robust Structured + Unstructured Data Analytics coupled with a Natural Language Processing (NLP) capabilities empowering a Multi-Structured MDM would enable the solution to be automated to a large extent as a real-time or near real-time integration with the CRM, Campaign Management and all other Customer Intelligence dependent systems for democratizing actionable insights internally to all key stakeholders and even allowing the organization to monetize this new enriched customer insights in a secure regulatory compliant manner (like aggregated insights at a geographical/location or age or income or spending segments as an example) ,if needed, as an additional revenue stream in their specific industry.
While Real-time, Multi-domain MDMs are essential, the key is to ensure that you harness the rich customer data that is being made available to you due to data sources emerging as an outcome of a Digital Strategy and Transformation.
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