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How to Integrate Preference Data Into Your Analytics Strategy?

The popularity of using online customer survey has grown strongly in the past few years. Companies send out their surveys every once in a while, and collect the data from their customers. However, it’s not unusual that this data is left untouched or luckier, it is analysed but the insight will go straight to archives. Does that sound familiar to you? If so, don’t worry because you are not alone.


Many firms out there still treat survey data differently from their customer usage data while in fact, both of them are essential and should be used at the same time to help you understand customers. Here are three questions that companies can use to make the most out of survey data in their analytics strategy:

First, which product usage patterns correlate with low net promoter scores (NPS)? NPS has become highly popular in customer surveys nowadays with its classic question: “How likely are you going to recommend our product/service to your friends and colleagues?” It is an easy to use and great tool for management, however, when tackling preference data separately, it’s likely that companies only look at the charts over time and are aware of customer loyalty. Truth be told, the NPS is not specific enough as it doesn’t identify the reasons customers are Detractors.

What if we look at the usage data and find out which features of the app are correlated with low NPS. It’s possible that most users with low NPSs will interact with the app in the same particular ways. Hence, combining both kinds of data might help you know where and what to improve. What’s more, at that point, you could surely tailor a marketing campaign towards those low-NPS users and turn them into promoters. 

Second, are customers loyal to your company because there isn’t any alternative? Many companies are often overjoyed with great insights from usage data that they ignore the NPS. Well, how can you be dissatisfied when the retention rate is very high, which means people keep using your product over time? Don’t be that silly and do a double check! Low NPSs should draw some of your attention.

What if someone tells you the customers still use your product because they can’t find any alternative at that moment? They might not enjoy the app but have only one option. As soon as better service appears in the market, those “loyal” customers will jump ship and abandon you. Remember Yahoo and Google Search, or Myspace and Facebook. Who is the winner now? Thus, make sure to use both usage and survey data to improve the customer experience before you see them walk out of the door. 

Third, which features can bring in more influencer customers? Each product usually has its own core audience who can bring numerous values to your brand. Needless to say, they are the ones who constantly use the product and will be more likely to tell their friends about it. You will get ‘free’ marketing if you have more of them, right? But the problem is How? Now is time to look at both analytics and survey data. Once you integrate your survey into the usage data, you can find features which are correlated with high NPSs. Want to have more highly satisfied and loyal users, you know where to shift your development focus to, right?

Those are only 3 fundamental questions which might help companies use their usage and preference data more efficiently. Of course, there are many more ways to do it. The more questions you ask yourself, the more solutions you can find. If you have done it before, feel free to share with us @InlinemarketFin. Or if you want to learn more about our process of integrating surveys into analytics strategy, don’t hesitate to have a chat with our Data Science team.

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