DECEMBER 20169launched once or twice a year often just doesn't cut it, especially when you're trying to assess how customers feel about a shopping experience, dealing with your sales associates, or how the store environment feels to them. These characteristics can change over time, vary by region, or change based on who is managing the stores. If you can capture the feedback continuously and make some operational changes based on the feedback on daily basis, you should be able to see positive changes in customer satisfaction or customer experience levels over time.Ask Why: Capture enough detail that you can take action. It's not enough to have your customers simply rate you on satisfaction by giving you a score out of five. If they give you a low score, you know that there's a problem, but you don't know why. Give them room to explain why in a comment box, especially if this is a web survey. You may be able to look for groups of keywords that keep popping up in the text, such as `no follow-ups' or `long wait-times'. The `why' will provide you with information that makes the response actionable.Quantity Counts: Capture enough responses in order to detect significant differences between categories. You need a statistically-valid sample size to be able to attribute your findings to the entire population. Statisticians will tell you that you need 389 responses in a specific category to have a 10 percent margin of error in your results. Businesses can get by with a 10 percent error margin; and healthcare typically needs five percent, or 1,568 responses. So say for example, you're measuring customer satisfaction at the store level. In order to say that Store A had a significantly better customer satisfaction score Capturing feedback continuously and making operational changes based on the feedback on daily basis will result in improved levels of customer satisfaction and experiencethan Store B, you need 389 responses to be able to draw this conclusion, with 90 pecent accuracy. If you have less than 389 responses for a single category, say store, or gender, or first-time shoppers, you can't draw any reliable conclusions from your findings because the margin of error will be too large. This even becomes more critical if you're trying to find statistically significant differences with more granular information; say males aged 18-24 who shop at the store during the month of May. Your sample size for 18-24 year old males per store during May needs to be at least 389 in order for you to be able to compare this group reliably. Many people who survey don't realize this. So make sure you use methods that provide you enough feedback!So, you can see that by following these three basic rules, you can collect a solid base of customer experience feedback from which you can make informed decisions with confidence. Anything less, and your assumptions may come back to haunt you. Jaakko Mannisto
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