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EDM and Customer Centricity

Suresh Vittal over at Forrester wrote a nice little piece this week - "Eight Marketing Technologies That Enable Customer Centricity" (subscription or purchase required). He does a nice job of discussing some of the challenges and identifying technology both for "infrastructure" and "execution". While predictive analytics make an appearance in his infrastructure list, business rules show up in a couple of places and testing/optimization come up I think he misses the role of customer-centric decisioning as a way to link infrastructure and execution. An enterprise decision management or EDM-centric view of this might divide the technologies into three:

  • Infrastructure to collect, organize and enhance customer data
  • A decision backbone or hub
  • Execution technologies to deliver decisions in multiple channels

How would this different from Surresh's paper? Well:

  1. Infrastructure would include technologies for enhancing customer data using third party data sources (demographics for instance)
  2. Execution would involve providing context to and getting responses from the decision backbone (context matters but the decision backbone would be responsible for the "Best Next Action" )
  3. The decision backbone would use EDM to calculate the right decisions for each customer at each point in their lifecycle, connecting them as necessary. To do this it would use
  4. Predictive analytics to model customer behavior, purchase patterns etc
  5. Business rules to control frequency, enforce policies and regulations, allow customers to personalize the interactions and so on
  6. Adaptive control to try out different approaches for some customers to see which work and which do not so as to constantly improve the decision-making

Because the decision backbone is distinct the customer treatment decisions are managed as a corporate asset, they can easily be delivered through the mix of channels and systems most companies have. For instance the billing system could use it to put a compelling offer at the end of the statement.

At InterACT recently, a customer of ours, Best Buy, gave a great presentation on this and we have had other great examples of the improvement in return from being customer-centric in offer-making where personalized offers based on rules and predictive analytics showed up to a 2000% improvement in results! Colleagues of mine also work with the likes of Unica on combined approaches, check out this white paper on Customer Decision Engines and this presentation on From data to decision: Transforming Marketing Data to Enable Decision Management.

We tend to talk about 6 principles of customer-centricity and the table shows how those principles are supported by EDM.



Choose Which Customers to Focus On

Analytics can identify not only the current high-value customers, but also the future high-value customers, as well as those prospects that are likely to respond to an offer or other action.

Clear, Insightful Customer Segmentation

The integration of analytics, including those for segmenting customers, and powerful analytic techniques and technologies from Fair Isaac’s R&D labs ensure that the most effective customer segmentation is applied to all decisions.

Winning Value Proposition for Each Segment

The use of decision models and optimization ensures that the most compelling value propositions are identified quickly, tested scientifically and deployed easily.

Deep Alignment Across the Enterprise

Customer treatment decisions can only be aligned across the enterprise if an infrastructure for sharing, managing and deploying decisions across the enterprise exists. EDM delivers such an enterprise decisioning backbone.

Define and Track Key Segment Performance Metrics

Integration with reporting and performance management, combined with effective logging of actions, rules fired and analytics, ensures that the performance of segments can be tracked and measured.

Process for Continuous Learning and Improvement

The adaptive control approach and the integration of adaptive analytics and champion/challenger allows for continuous learning and improvement in all EDM applications across the lifecycle.

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