Should verbatim analysis drive customer survey processes?

Traditionally, verbatim analysis techniques and tools are applied in post survey analyses of customer feedback.  But, with the increasing prevalence of very brief transactional surveys and social media channels generally, I'm wondering if the process should be reversed.  i.e. Analyze verbatim comments to understand where deeper dive kinds of surveys should be deployed.

I'm seeing an increasing number of companies these days that use a very simple transactional Net Promoter or CSAT survey process. Typically, these firms are asking a single question: "How likely are you to recommend [company] to your family and friends?", accompanied by a comment box. Or, "Rate your satisfaction with [company]", accompanied by a comment box. It seems to me that there are advantages to this kind of process including:

• Higher response rates
• Really simple and fast implementation of the survey process itself
• Low cost 

It would also seem that there are some disadvantages to this type of process, including, among others:

• Figuring out who should do follow up on received feedback.  
• Figuring out how to appropriately follow up on received feedback.
• The challenge of analyzing feedback from surveys where no questions exist about key aspects of the company's offerings (examples being product / service quality or value vs. competition).

For companies early in their existence, simple easy and low cost are important characteristics for a customer feedback program. But, as they grow, understanding the drivers of loyalty or satisfaction become more important in successfully operating the business. This leads to growing companies using more and more manual resources for feedback analysis, which of course costs money. The way it works: At first, one person is assigned to read, categorize and action issues identified in comments in surveys. When comment volume gets more significant they expand to a team of people. And, so on.  

Once multiple people begin analyzing verbatims individually, interpretation issues begin to creep into the analyses.  The more people categorizing text the more interpretation issues there will be. Automated text analysis tools are a good next step for customer feedback evaluation when teams of people begin getting involved. They reduce labor costs while improving the quality of the analyses. 

Even automated and consistent text analytics isn't sufficient to fully understand the voice of the customer (VOC). Additional quantitative data is also necessary. So, some level of follow-up survey process needs to be implemented. In fact, potentially several separate follow surveys might be used depending on what the verbatim feedback is indicating. For instance, if product or service issues are highlighted by people responding to the survey, a follow up survey asking a few more questions (less than 10 ideally) should be sent in order to better understand what those issues might be.

A number of companies I talk with these days have this scenario where they're receiving lots of multi-channel verbatim feedback, beyond that contained in their transactional surveys. Twitter feeds, customer service chats, feedback forms on the websites, etc., all offer text analysis opportunities and will provide indicators for follow up, deeper dive surveys. Companies should look to Text Analysis tools to standardize their verbatim feedback analyses. But, they also should look for ways to use the verbatim analysis results to drive follow up surveys that lead to a higher level of VOC insight.

Transactional feedback is a key element to any company's customer experience strategy.  But, understanding the customer experience is more involved and requires more information about customers than simple transactional surveys can provide. Combining them with text analytics and targeted follow up surveys can provide that richer set of insights.

- Stewart Nash
QuestBack USA
Etuma USA
LinkedIn: www.linkedin.com/in/stewartnash