Because clickstream data is so readily available, we can easily measure/quantify users’ behaviors on websites, apps, etc. So is there any point in conducting surveys to get inside user’s heads, to measure their attitudes and preferences? After all, the best predictor of behavior is past behavior, not self-reported attitudes.
Surveys can nonetheless answer questions about our users that clickstream data cannot. Here are some scenarios:
You have a site where you provide online technical support to customers of a product. Using Google analytics, you notice that users have been spending more time on your site per visit, conducting more consecutive searches on your site, and viewed more results pageviews per search. So are users having a better or worse experience on your site?
- You could reason that users are having a better experience – they may find your site useful or engaging for technical support, and want to spend more time exploring the site.
- But they could instead be having a worse experience – they are not able to find the information they need, no matter how many searches and results pages they go through.
- Conducting a tracking study in which we regularly survey users by asking them “Were you able to resolve your technical issue or question?” and “Overall, how satisfied or dissatisfied are you with the support website?” helps us answer the question of whether users are having a better or worse experience on your site.
Surveys can reveal insights or problems through the use of open-ended questions. By asking questions like “What was the reason for your visit?” or “What feedback do you have about our site?”, you’re getting at the Voice of Customer telling you what’s working and what isn’t, and whether they are visiting your site for the reasons you expect. Looking at numbers in digital analytics won’t give you this type of insight. Also, using surveys to get at Voice of Customer is cheaper and faster than any other qualitative methods like usability lab studies, ethnographic field studies, etc.
In addition, attitudinal metrics provided by survey data tells us how loyal our users are likely to be in the face of competition. Let’s say we have a website or product in which we clearly dominate the market (think YouTube or Microsoft Office). Usage is no doubt very high, but high usage does not necessarily mean users are satisfied with our site or product. There may simply be no better alternative. The danger is that your site or product may become vulnerable to a rising competitor. By looking at not just behavioral measures (as indicated in clickstream data) but also attitudinal measures ( as provided in survey data), you get a better indicator of customer loyalty.