A Sample Decision Tree

A basic customer experience management strategy in action:

IO Customer Experience Management Decision Tree 

The Logic

Step 1

At the start of every interaction a random decision is made about whether any recommendation will be made to this customer (Box 1).  Neutral (‘Do Nothing’) interactions are essential as control groups to allow proper measurement of the uplift of specific actions.  

Step 2

The  next step in the process is to choose between three options:  If the customer data is less than 50% complete (Box 2) then gathering information is the priority; if the attrition risk is less than a given threshold (60% in this case), the best offer will be made; otherwise, a proactive service action will be taken.  

For the customers who receive a cross-sell/up sell recommendation, an ROI calculation determines the best offer.  But for 40% of customers, a new offer is tested to determine uplift potential.   (Box 3)

Step 3

For customers who receive a service action (Box 4), the model looks at whether the customer is better serviced through a different channel, whether the customer should be moved to a new product or offered an appointment with a customer relationship manager for portfolio management services.

Customer experience management decision tree strategies like this can be deployed at different levels of sophistication depending on a company’s modeling capabilities and level of integration.  Typically, the strategy itself is wrapped within the Interaction Optimizer delivery rules to ensure the best available action –and to continuously test alternatives.

Interaction Optimizer deploys this kind of strategy through one channel or across all channels with any changes propagated instantly to every touch point.

“Don’t bury logic in channel applications.  The decisioning engine is the brain, the channel application is the delivery mechanism.”
Suresh Vittal, “Interaction Management” Webinar
Forrester Research, Inc. October 2006
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