<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>elliott34</author><text>I have a lot of experience with this problem. The simplest way is via data munging in python&amp;#x2F; pandas etc by finding what percent users convert&amp;#x2F;churn after doing an event N times within the first X days, and all the permutations thereof, using statistical tests around the change point. A more clever way is to use bayesian change point analysis.&lt;p&gt;The tricky thing is that these insights wind up being kind of obvious from the first analysis. You will find things like &amp;quot;users who use the software more are more likely convert.&amp;quot; Other times these types of analysis will confirm what you already know. The  tricky thing is making sure you have the right tagging&amp;#x2F;events and place to make sure you&amp;#x27;re getting at the right level of detail to get something worthwhile. It&amp;#x27;s very a much a garbage in garbage out type of thing.</text><parent_chain><item><author>gingerlime</author><text>Finding the famous &amp;quot;Aha moment&amp;quot;.&lt;p&gt;You probably heard the story on how facebook realized that once someone adds at least 7 friends, then they reach this &amp;quot;Aha moment&amp;quot;, and from that point on, they&amp;#x27;re converted to longer-term users. And how afterwards Facebook optimized their onboarding experience to help new users find and add more friends...&lt;p&gt;That&amp;#x27;s the problem I&amp;#x27;m facing with our startup. We have tons of data. We track events, conversions, page views, bounces, you name it. But we&amp;#x27;re still not sure what&amp;#x27;s our &amp;quot;Aha moment&amp;quot;. A tool or service that would ingest our analytics (or do its own) and find a strong causal relationship between actions and conversions would be really amazing (ideally, without requiring a $gazilion+ enterprise license)</text></item></parent_chain></comment><story><title>Ask HN: What is a problem you face at work?</title><text>Hi guys,&lt;p&gt;I&amp;#x27;m Cory. I run http:&amp;#x2F;&amp;#x2F;oppsdaily.com, a daily email for software devs who want to solve the problems people face at work.&lt;p&gt;The email consists of a super brief interview about a problem you have at work, and the software you wished you had (that you would buy), that could solve the problem.&lt;p&gt;Each day I receive a handful responses from developers who want to learn more, and I connect them to the interviewee.&lt;p&gt;I really want to source some of those interviews from this amazing community.&lt;p&gt;If you are facing a problem that you&amp;#x27;d like to share, please contact me! - cory@oppsdaily.com&lt;p&gt;I&amp;#x27;d love to feature you in one of my interviews.&lt;p&gt;EDIT:&lt;p&gt;If you&amp;#x27;re not comfortable being featured in an email, but you would like to share in this thread for the benefit of the HN community, please do! :)</text></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>AznHisoka</author><text>I personally have had this problem and tried looking for that insight hidden among our big data.&lt;p&gt;but we discovered looking for patterns in quantiative data was a waste of time. Instead what we are focusing on is more qualitative data: interviewing customers, interviewing people who cancelled, and finding the &amp;quot;jobs to be done&amp;quot; of your prospective customers. then mapping that to your product features.&lt;p&gt;once you truly understand your customer needs, knowing what to fix&amp;#x2F;improve is rather trivial.</text><parent_chain><item><author>gingerlime</author><text>Finding the famous &amp;quot;Aha moment&amp;quot;.&lt;p&gt;You probably heard the story on how facebook realized that once someone adds at least 7 friends, then they reach this &amp;quot;Aha moment&amp;quot;, and from that point on, they&amp;#x27;re converted to longer-term users. And how afterwards Facebook optimized their onboarding experience to help new users find and add more friends...&lt;p&gt;That&amp;#x27;s the problem I&amp;#x27;m facing with our startup. We have tons of data. We track events, conversions, page views, bounces, you name it. But we&amp;#x27;re still not sure what&amp;#x27;s our &amp;quot;Aha moment&amp;quot;. A tool or service that would ingest our analytics (or do its own) and find a strong causal relationship between actions and conversions would be really amazing (ideally, without requiring a $gazilion+ enterprise license)</text></item></parent_chain></comment><story><title>Ask HN: What is a problem you face at work?</title><text>Hi guys,&lt;p&gt;I&amp;#x27;m Cory. I run http:&amp;#x2F;&amp;#x2F;oppsdaily.com, a daily email for software devs who want to solve the problems people face at work.&lt;p&gt;The email consists of a super brief interview about a problem you have at work, and the software you wished you had (that you would buy), that could solve the problem.&lt;p&gt;Each day I receive a handful responses from developers who want to learn more, and I connect them to the interviewee.&lt;p&gt;I really want to source some of those interviews from this amazing community.&lt;p&gt;If you are facing a problem that you&amp;#x27;d like to share, please contact me! - cory@oppsdaily.com&lt;p&gt;I&amp;#x27;d love to feature you in one of my interviews.&lt;p&gt;EDIT:&lt;p&gt;If you&amp;#x27;re not comfortable being featured in an email, but you would like to share in this thread for the benefit of the HN community, please do! :)</text></story>