Conjoint Analysis: B2B Customer Service Strategy

In this case study Sawtooth Technologies researched the values for service attributes in the channel (brokers, agents and distributors) and with end-customers.

 

Situation

A major U.S. provider of commercial insurance wanted to increase profits by enhancing customer service. The client sought to understand the impact of:

• Customer service on policy purchase and renewal
• Various aspects of customer service on the overall value of customer service

 

Research Steps

1. Developed two different two-stage conjoint interviews: one for end-user customers and one for the channel.
   • Stage One allowed respondents to express their trade-offs at a “micro” level between customer service attributes (speed of policy issuance, speed of inquiry resolution, point of contact, etc.).
   • Stage Two assessed respondents’ preferences for different insurance concepts, each composed of “macro”-level attributes such as price, financial rating, coverage and exclusions, etc.
      
2. Calculated two sets of utilities—one at micro level and one at macro level—for each interviewee.
    
3. Built a two-stage simulation model for each population to predict acceptance of the client’s products. The model used three sets of information to generate results:
   • Respondent perceptions were used to specify the client’s current service level.
   • The micro-level specifications service features were coupled with the micro-level utilities to generate a predicted level of customer service performance.
   • The predicted level of customer service performance was combined with the macro-level product specifications and the macro-level utilities to estimate the overall acceptance of the client’s products.
      
4. Used the two-stage models to test different product and service configurations:
   • Altered customer service features and predicted the impact on customer service.
   • Simulated changes to the overall level of customer service and observed the predicted changes in purchase and renewal acceptance.
   • Tested alternative product scenarios and assessed which product features offered the greatest leverage to the client.

 

Research Results

Through the use of these simulations, the client gained a rich understanding of the impact of:

• Customer service on policy purchase/renewal.
• Customer service components in driving perceptions of quality.
• Product features in driving policy purchase and renewal.

 

Outcome

The information was used to reposition the client’s customer service offerings in a way that customers valued and that differentiated them from the competition.

 

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