The Best Web Analytics Tool

https://satchel.com/web-analytics/

This is primarily a comparison between Heap, Amplitude, and Mixpanel. Appears to be an eminently fair comparison, and ends up recommending Heap for early-stage startups.

Highlights / Quotes

Every YC batch, Michael Seibel gives a talk about building product. He’ll ask: “How many of you are using Google Analytics as your primary source of metrics?” But it’s a trick question. When the majority of the audience eventually raises their hands, he’ll fake a sigh and tell everyone that they’re doing it wrong, and that they should instead by relying on an event-based analytics tool.

Without using an event-based analytics tool, which tracks the interactions your users have with your product, you won’t know how your users are using your product. This is arguably just as important as actually building out the product. There are a lot of event-based analytics tools out there, but we think that if you’re an early-stage startup, Heap makes the best tradeoffs.

Google Analytics by itself is insufficient to figure out how your users are using your product, although it is useful to complement an event-based analytics tool.

We found that defining events in code while having auto-track as a safety net is a near-ideal setup for an early stage startup.

Google Analytics uses a pageview-driven paradigm, a holdover from what was important in the early 2000s. Its focus on pageviews helps answer questions such as how many users came to your website, what pages they visited, and how they found your website. Unfortunately, it isn’t able to help you figure out which specific actions a user performed on any given page of your website.

If event-based analytics are so important for early-stage startups, one might rightly wonder why so many YC startups, whose founders are quite sharp in aggregate, rely primarily on Google Analytics?

It turns out that this is a rather illuminating question. The main contributor to this phenomenon is easy to understand and empathize with. Startups are busy and overworked, and analytics are often ostensibly seen as orthogonal to the priorities of understanding their users and building product. Therefore, event-based analytics often fall to the wayside as they typically require engineering time and discipline to maintain. If you forget to update an event, or don’t have time to implement analytics for a new feature, then you can’t get any benefit out of it at all.

We think that Heap is the best analytics tool for a typical early-stage startup. Out of the event-based analytics tools that we tested, we found Heap to be the best-suited for products with rapidly-changing feature sets, despite it lacking some of the extensibility and more advanced analysis capabilities of its competitors. We think that this tradeoff is best suited for early-stage startups.

We found that often founders who use an analytics tool with auto-tracking functionality tend to rely entirely on events being automatically captured without programmatically defining any events. After extensive testing for ourselves, as well as our own historical experiences with analytics tools, we don’t think this is the best way to use these tools. Instead, we think the ideal approach is to rely primarily on programmatically-defined events and use auto-tracked events as a backup.

relying solely on auto-track functionality has two primary upsides and two primary downsides

  • upsides: error tolerance, non-technical user friendliness
  • downsides: event definition disorder, lack of focus

The nice thing about Heap’s pricing is that once you move onto a paid plan, it generally costs less than both Mixpanel and Amplitude for an equivalent amount of users.

we discovered that while Amplitude’s ease of use was a major factor for their satisfaction, Amplitude’s pricing model was what convinced a lot of founders to initially sign up.

One benefit on this front is that Mixpanel is the only event-based analytics tool with a mobile app. This may seem redundant, but we found it to make dashboards, KPIs and common analysis much more accessible within our team, as it promoted checking metrics on a more routine cadence for team members who otherwise wouldn’t.

The general consensus is that Segment is a well-loved product with a well-disliked pricing

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