Many companies blindly attempt to retain customers at all costs. Is this a good practice? 
Are there situations where you should allow customers to walk away?  How much should you spend to retain a customer?  Do the best retention offers translate into increased retention rates and future profitability?

These were the questions posed to Aspen Analytics by a Fortune 100 provider of subscription services.  To answer these questions, it was important to define the client’s most important metrics.  How does the client measure success?  Company profitability?  Number of subscribers?  Number of saved customers?  ROI of the retention program?  Depending on the optimization goal, the approach may differ.  For example, if the goal is number of saved customers, the tactics would be different than maximizing company profitability.  In this case, the client decided to focus on company profitability.

Using a combination of predictive analytics and financial modeling, we developed a multi-step process for calculating the retention cost that should be spent to retain each individual customer. The main factors taken into consideration included: offer costs (discounted service, cash back, etc), success rate of various offers (take rate and tenure following offer acceptance) and projected future profit (profit of products subscribed and projected future tenure).

This methodology was implemented successfully in a call center where an escalating list of three offers were displayed to customer service “save specialists” to present to customers calling to unsubscribe. 

Our approach showed two interesting results:

• The optimal approach for many customers is No Offer.  Customers with little prospect for future profitability should receive “consultation,” but no financial offer.
• The most costly offer does not guarantee the best results in terms of retention or profitability.  In many cases, “consultation” proved more effective than, say, a $50 discount on future service.  This tells us that many customers just want to have a problem solved.  Yet many organizations automatically give the most valuable customers a rich offer without really understanding the customer’s needs.

By implementing our approach, our client is positioned to add millions of dollars to the company’s bottom line annually.  At the same time, the data collected throughout the process can be used to further refine the methodology and provide additional incremental profits to the organization.  This data can also be used in other marketing initiatives across the company.

This case study demonstrates another example of how a small investment in marketing analytics can return an exponential level of profit.  What thoughts do you have on customer retention?  Are all customers created equal?  We’d like to hear your opinion.