Have any of these things ever happened to you?
1) You know that your company regularly conducts a customer survey, but you have no clue what the results are.
2) You are the lucky recipient of a ‘data dump’ (reports, spreadsheets, emails) with no explanation of what it means or how to use it.
3) You are compensated or measured based on a metric with no idea of how you can help improve the score.
Most companies are good at collecting data from customers. In fact, it’s common practice to have a customer feedback program in place. However, for some companies, dealing with the results is when things begin to get fuzzy. What are our customers trying to tell us? And how do we take that information and use it to effectively improve the customer experience?
To benefit from analysis, a successful customer feedback program must first include the collection of credible data:
- Are we targeting the right customers?
- Are we collecting actionable data that reflects the customer experience?
- Are we surveying customers at an appropriate time?
With these as a foundation, you can begin the process of analyzing and operationalizing the data.
Analysis for Action
When designing your analysis plan, consider the following: 1) Who will be using the data; and 2) What is the best method of distribution? You should be able to analyze and report results in a way that is useful and meaningful at all levels of the organization (executive, management, and front line employees).
For example, executives often like to see the key insights in dashboards, presentations, or emails, with access to additional information if they want to dig deeper. A service area manager may want to have access (either online, or in reports) to all of the data for his survey results, broken out by key segments and linked to operational metrics, so that he or she can use the results to drive improvements in people, tools and/or processes.
Next, consider how you will extract the drivers of satisfaction and loyalty from your data. A good analytical plan should include the use of objective and subjective survey results. Some examples of objective survey data include: overall satisfaction and loyalty questions, functional area, transaction or agent rating questions. Subjective data can be collected using verbatim questions and customer follow-up/root cause analysis. Using this customer feedback data, driver results can either be inferred (e.g. correlation, regression, factor analysis) or direct (e.g. comment analysis, text analytics, root-cause customer interviews). How you approach your analysis depends on your audience, company culture, survey content and the overall goals and objectives of the program.
You are now ready for action planning and execution. A survey governance model (policies and people who direct how the survey program is designed, administered and utilized) is a solid step toward business transformation. Survey results can be collected and analysis done, but it takes sponsorship, cooperation and coordination across the organization to be truly effective. Executives need to see the financial benefits of improving the customer experience and make it a part of the company DNA. Cross-functional management teams can bring the organization together to prioritize and develop action plans. Front-line employees should understand company goals and the part that they play in becoming champions for the customers. And don’t forget to communicate your goals, insights and successes, both internally and externally.
Whether your business is Fortune 500 or a Mom-and-Pop store, business-to-business or business-to-customer, local or global – all companies should strive to understand the customer experience and continuously plan for improvements. True success means that you are driving to business outcomes and not just a metric. Collect the feedback data and then do something with it. Your customers will thank you!

That is the premise of a new paper now available from 

