Testing out a new idea: stats for Slack

Good documentation is the key for team productivity and there are plenty of systems that you can use as an internal wiki (GDocs, Confluence, Notion, etc). We've also been working on one and, while doing our research, we realized that creating documentation may not be the hardest task of all. Before writing anything, how do you even know what needs to be documented?

Since we're working closely with Slack, and trying to extract something valuable from Slack logs, we decided to do a little experiment with one of our customers. We took logs of one of their high-traffic channels, ran some of our NLP tools to process them, uploaded everything into a Google Sheet and did some basic analysis. The results were quite promising, and now we're trying to figure out if this kind of stats is something that a lot of teams would love to have.

Here are some questions we were able to answer with our stats:

• How much traffic is on the channel
• How often do people ask questions
• Who asks
• Who answers
• What exact questions
• On what topics
• Which questions re-occur
• Which questions get resolved
• How long does it take to get an answer

Of course, have the row-level data, which can then be sliced and diced on any of these dimensions and then used to create the right content, which actually fulfills knowledge gaps and serves everyone in the team.

Right now we have everything in scripts & excel sheets, and we'd want to run the analysis with a few more customers before building any custom UI for it. We've created a PH Ship page so if you think this kind of data would be helpful for you, please feel free to signup for a beta: https://www.producthunt.com/upcoming/onebar-insights

Also, looking for any feedback here :)
Thanks!