This data is crucial to determining who is using your product, how they're using, and where users are bailing out. A very simple use case is when you're tracking users that hit your landing page, then hit your pricing page, then leave. If that's too big a percentage of your users, then it might signal that your pricing is off. If it's in response to a certain campaign, then it might be a signal that ad campaign isn't level-setting correctly.

This data tends to be uber-private, and would never be shared outside of the company, but it's also information that could be pieced together from server logs natively anyway (though with significantly more effort). Basically speaking, almost every company collects this data already, this just makes it more actionable.

It's also perhaps worth noting that following an individual user around the site is low value -- what you want to see are aggregates and percentages. Of all the users that make it to a funnel, how many complete? Of those that do complete, what's different about them vs. the others.

For a company the size of AirBNB to track each user individually is prohibitive, but being able to isolate those metrics down into measurable factors is huge.

If your startup wants to do something like this, it's worth noting that you could very easily semi-anonymize the data by attaching tokens to the users instead of tracking by username or email address. You'd still get the same traceability, but perhaps be slightly more able to be comfortable with doing it.