Dmitriy Pavlov

Actually, we're launching something very similar to NPS tool, but this is much deeper.

This is essentially we're trying to upend traditional market research by leveraging a new state of the art kind of deep learning natural language processing.

And by doing that, we're actually able to generate things that are more predictive than surveys.

Really, we're able to understand customers on a level that traditional market research hasn't been able to.

Good point.

Yeah, we're definitely pulling.

So this is unobtrusive research.

This is a way of asking users without really bothering users.

What we found actually, and I know you've interviewed lots of folks that have approached this space in terms of customer feedback, market research, lots of times.

And

All of the approaches are really good.

And what we found is a lot of users and customers are actually trying to communicate with the brand almost every day across lots of different channels.

And a lot of the firms we're working with have hundreds of thousands of customers calling in, sending support tickets, support emails every month.

So they're trying to do is trying to understand what are the issues to their customers, but they're also buying a bunch of research that tells them that does surveys that conducts other market research companies conduct surveys, et cetera.

That is a push type of survey.

So there's push and pull going on.

So what we realized is all of that data is valuable.

What we do is we collect all of that data that has been surveyed data, that is submitted organic user data.

We actually integrated with our system to create this.

Essentially, there's a strengths, weaknesses, opportunities, and threats that are relevant.