11–20 of 213 posts
Since Heap captures everything from day 1, all analysis is automatically retroactive. There's no need to wait days for data to accumulate.
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Dumb question but how does this work? Since Heap captures everything from day 1, all analysis is automatically retroactive. There's no need to wait days for data to accumulate. So it studies my server's web logs? I'm confused about what this means.
Dumb question but how does this work? Since Heap captures everything from day 1, all analysis is automatically retroactive. There's no need to wait days for data to accumulate. So it studies my server's web logs? I'm confused about what this means.
Looks very cool––what kind of performance hit is introduced by logging every event?
It's essentially imperceptible. We measured it, and our client-side script introduces a 0.1% CPU overhead.
How does it affect network performance? If I click a link and it takes me to another page, how do you track that?
Dumb question but how does this work? Since Heap captures everything from day 1, all analysis is automatically retroactive. There's no need to wait days for data to accumulate. So it studies my server's web logs? I'm confused about what this means.
Yes! I've been doing this for awhile. If you feed the data into a Bayesian classifier, you can figure out what kind of user you're dealing with, too.
This seems really interesting, but starting at 250 users per month seems high. I notice the price/active user starts at a penny and falls 60% as the users climb to over 500,000. Would it be possible to create a price option for even smaller companies, demo sites, etc, at a higher rate? Say, what if the owner of a small blog wanted to use this to do really fine grained analysis of users actions but they average 250 hi…