It is a problem, depending on the context, it’s a big problem actually. So for the analytics per se it can be mitigated by just collecting more data.

It doesn’t tell you exactly what for person X or person Y what’s their key pain point are, but it can analyze for all customers or certain segments, what’s their key criteria to act on are. For customers or visitors, if they don’t write much, you need to collect more data.

One way of collecting more data is to collect more data at one person. There are so-called active listening approaches. What the active listening does in the NPS survey is, it takes the customer text feedback sends it to the deep learning tech service platform in real time, categorizes it in real time. The based on rules the bot reacted. If it’s category is friendliness, it says: “Hey, I’m a bot. I understood, you’re not satisfied with friendliness. Did I get it right? It would be great if you can explain in more detail”.

This probing, which is adaptive, has proven to be very effective, because the response really feels okay. Customers feel “This is not an preprogramed bot here, but they feel understood me somehow, or they feel the bot didn’t get me, which has even the same effect. Customer feel: Oh, he didn’t get me. I need really to explain better. So this, has proven to get double of feedback and also improve the predictive power by another 50%.