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The Value of Old Surveys

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The most valuable customer-satisfaction surveys you have may be the ones you haven't looked at it in a few years. They are not valuable so much for what you learnt then as for what you have learnt since then. Since you conducted that survey, some customers have stopped buying from you, others have decreased how much they buy, and some have significantly increased what they purchase.

Wouldn't it be great if you could use a new version of that survey to predict loyalty behavior?

You can, provided that you collected survey responses by account rather than anonymously. You'll need access to detailed customer records. For B2B research, you should be able to request information from your CRM (Customer Relationship Management) system. For B2C research, e-commerce sites and mail-order operations have detailed sales transaction databases that you can mine; for retail, your best source of information is that collected as part of customer loyalty programs. On the consumer side, subscription and service businesses have better records than manufacturers or retailers.

Once you have identified your source of customer information, you want to see how much information you can collect from it. Some possibilities:

• Acquisition
  • Date of first purchase
  • Amount of first purchase
• Expansion/Contraction
  • Amount spent since the date of the old survey you are analyzing
  • Amount spent in same time period prior to the survey
  • The percentage change in spending for the two periods
• Retention
  • Whether or not they are still an active customer
    • Easy to define for subscriptions and annual services
    • Hard to define for retail (perhaps defining it as customers who have made a purchase in the past six months)
• Recommendation
  • Referrals - others who have become customers because of their recommendation [sometimes possible for B2B research, depending on the CRM data]

Supplement these suggestions with other financial information or customer-loyalty data relevant to your industry.

With this information at hand, merge it into your survey data. You can now conduct a correlation analysis to see what survey answers are predictive of increased or decreased customer loyalty. For instance, one of our customers was able to do a linkage analysis that identified how much additional revenue for licenses and maintenance renewals would result from increasing the Customer Loyalty Index by one rating point. For one of our clients, we found that of a dozen attributes measured in a transactional survey it was "Timeliness of Customer Service" that had the highest correlation to customer retention.

Once you have identified the key drivers for customer loyalty, you can move tactically and strategically to act on this information. Tactically, you can modify the survey to focus on the key drivers and de-emphasize or eliminate some of the other questions; you can set up survey triggers so that any low or medium ratings on the questions that drive loyalty are immediately escalated to a customer service representative or manager. Strategically, you can determine what investments are needed to improve the key drivers on an organizational basis.

You see, an old survey can teach you new tricks.