11–20 of 22 posts
You never know. Are you ready for success ?
This story looks like that.
This article comes across as being really fake. You can clearly tell that the goal is to to drive additional traffic to their v1.0001 instead of actually diving into what they did wrong. Were they really investigating an entire new DB and user interface in the few days after launch? If your initial design is so far off that it requires a complete rewrite on day 1 of launch, then you have serious problems. That is not…
Let's not jump the guns too soon. Analytic products are notoriously hard from scaling perspective. UI, APIs, Infra that works crisply for 1x data, starts to become sluggish at 10x and really breaks down at 100x.
Startups solve the 100x scale problem when they get there (sensibly so). In this case, they got there way too quickly thanks to HN traffic.
This article comes across as being really fake. You can clearly tell that the goal is to to drive additional traffic to their v1.0001 instead of actually diving into what they did wrong. Were they really investigating an entire new DB and user interface in the few days after launch? If your initial design is so far off that it requires a complete rewrite on day 1 of launch, then you have serious problems. That is not…
This article comes across as being really fake. You can clearly tell that the goal is to to drive additional traffic to their v1.0001 instead of actually diving into what they did wrong. Were they really investigating an entire new DB and user interface in the few days after launch? If your initial design is so far off that it requires a complete rewrite on day 1 of launch, then you have serious problems. That is not…
This article comes across as being really fake. You can clearly tell that the goal is to to drive additional traffic to their v1.0001 instead of actually diving into what they did wrong. Were they really investigating an entire new DB and user interface in the few days after launch? If your initial design is so far off that it requires a complete rewrite on day 1 of launch, then you have serious problems. That is not…
> That is an architectural failure. Let's not jump the guns too soon. Analytic products are notoriously hard from scaling perspective. UI, APIs, Infra that works crisply for 1x data, starts to become sluggish at 10x and really breaks down at 100x. Startups solve the 100x scale problem when they get there (sensibly so). In this case, they got there way too quickly thanks to HN traffic.
This article comes across as being really fake. You can clearly tell that the goal is to to drive additional traffic to their v1.0001 instead of actually diving into what they did wrong. Were they really investigating an entire new DB and user interface in the few days after launch? If your initial design is so far off that it requires a complete rewrite on day 1 of launch, then you have serious problems. That is not…
And... So it was a failure... So they redid the work.
You can trigger events with JavaScript and choose whether they affect bounce rate, so you can manually trigger an event when the user scrolls down, clicks something, spends a few minutes on the site, etc. So your problems with the bounce rate metrics are just not true.
Also I saw you mention it doesn't track returning users, that's not true either. I can actually see insights into how many users return month after month, and it'll tell me what my activity is per channel and if one channel outperformed others, so it's pretty powerful in this regard for a free platform.
I skimmed it but from just reading those it sounds like you should try to get better familiarity with Google Analytics and talk to users to see what their main pain points with existing platforms are, as well as establish more concrete value propositions. Google Analytics is free after all, I'm not convinced yet to move to a paid platform that tries to address problems I'm not experiencing.
I wanted to try Volument but I noticed that their website wasn't redirecting to https, they had set the HSTS header and forgot about http since they only ever saw https on their browsers. This put me off because I thought, if they got this wrong, who knows what else they got wrong? I emailed them and they replied very soon and fixed the problem within a day, though, so at least response time was excellent.
I looked at your problem page and it's not true that Google Analytics bounce rate is not useful for single-page applications. You can trigger events with JavaScript and choose whether they affect bounce rate, so you can manually trigger an event when the user scrolls down, clicks something, spends a few minutes on the site, etc. So your problems with the bounce rate metrics are just not true. Also I saw you mention i…
GA can do retention reports or "cohort analysis" and show how visitors return in a monthly basis, but there are two critical limitations on it:
1) It doesn't show you which landing pages, target markets, or their combinations are retaining the most.
2) You can only study one metric by the time and not the total retention + conversions each segment generate, which should be the deciding factor
There is no initial interest, nor predictions either. So when doing a new campaign you cannot take any insights from cohort analysis until you wait for enough return visitor data.
We certainly agree that Google Analytics is an awesome tool and it has served our sites really well in the past. It gives tons of general insights for a free service, but isn't designed specifically for conversion optimization. Hence Volument.
Cheers for shipping a product! I recall the post, and as a heavy Google Analytics user the landing page made some very salient points. This post was honest and challenges the fantasies of many hopeful hackers. "Catastrophic Success" is no joke. I can sympathize with the challenges of running a web scale analytics tool, after helping build and run an analytics stack for an ad network. Even with our relatively small gr…
Thank you for the solid feedback!