Customer satisfaction measurement with Datagame

Customer satisfaction measurement with Datagame

Customer satisfaction measurement is about understanding your customers better. What do they like and not like about your brand or product? What are your strengths and weaknesses as a brand? How do you compare to your competitors (and what do your customers think about them)? How loyal are my customers? Will they continue to use your brand or product, or switch as soon as something new and shiny comes along?

Customer satisfaction surveys

One core component of a customer satisfaction measurement program is the customer satisfaction survey. In a customer satisfaction survey, the goal is to find out what is important to your customers and how you are performing in those areas. This can be done in a variety of ways, but there are some standard question types that are frequently used:

  • A list of statements, such as “This product was a good value for the price,” with a rating scale of “Strongly Agree” to “Strongly Disagree.” Each statement is about a different aspect of the product, service, or brand. For data quality purposes, vary the desired response. You don’t want the “good” answer to always be “Strongly Agree.” For example, a fast food restaurant might follow the value question with “My wait in line was too long.” In this case, the desired response is “Strongly Disagree.” This requires respondents to read each statement and makes it easier to identify straightline behaviors.
  • Paired questions that first ask respondents how important different features are for their decision making. Then, they are asked how satisfied they were with performance in those areas. For example, a restaurant may be interested in customer satisfaction with Food quality, Price, Cleanliness, Speed of service, and Friendliness of service. The survey would first ask respondents to rate the importance of each of these features. In a follow-up question, the survey would ask respondents to rate how satisfied they were with each these features on this visit.

Brand loyalty and health

An important aspect of customer satisfaction is understanding how you compare to your competitors. Brand health is measured in a number of ways, including relative rankings. A key component of customer satisfaction is returning customers. Are they likely to return, and what are they telling others about your brand or product?

Net Promoter Score (NPS) attempts to measure how likely someone is to recommend your brand or product to others. It features an 11-point scale from 0 to 10. Respondents that answer with a 9 or 10 are “promoters”; they recommend your product to others and will likely be repeat customers. Those that answer with a 6 or lower are considered “detractors”; they not only aren’t recommending you to others but may actually be providing negative feedback to their peers.

Using Datagame for customer satisfaction measurement

You can use Datagame to gamify your customer satisfaction measurement and brand health studies. These examples re-implement the above approaches as card-based games. Sign up for a free Datagame account and try these examples out.

Agreement statements

Do you have a lot of statements that you need respondents to indicate their level of agreement? In this case, you often find that they strongly agree with several statements. What are your biggest strengths and weaknesses? How do you differentiate from several statements with similar scores?

Consider using a MaxDiff Rankifier game to sort this out for you. Instead of asking how much they agree with each statement, ask which statements they agree with the most and which they agree with the least. This will allow your results to stratify themselves and highlight your strengths, as well as where you need to improve.

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Paired questions

The Prefer! preference test game is a great way to collect data on two dimensions at the same time. Respondents select the most important factors, and then rate each factor on their satisfaction level. The results show a rank order of what factors are most important and a satisfaction rating for each factor. The raw data export includes individualized data for each respondent. Analyze the data to find insights, or cluster responses by similar rank order to create segments.

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Brand health and Net Promoter Score

Use a Prefer game to both rank brand strength and the Net Promoter Score for your competitors. This allows you to compare where you stand to your competitors with a relative rank order. Follow-up each choice with the Net Promoter question to see how your brand compares with your competitors. The resulting data shows a rank order of brands and the Net Promoter score for each brand. With the individual respondent data from the raw data export file, it is easy to calculate the Net Promoter Score for each brand.

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