Category: Analytics

2022 Thomvest SaaS Benchmarks — Part II: Output & Operationalization

2022 Thomvest SaaS Benchmarks — Part II: Output & Operationalization

Our 2022 Private Company SaaS Benchmarks & How to Operationalize Them

By Alex Rohrbach

In this two-part series, we examine private company SaaS benchmarks. Part I explains why we created our benchmark and what we learned from other benchmarks. Part II presents our 2022 SaaS benchmarks and describes ways to operationalize them.

We calculated our benchmarks using a “trimmed mean” of the seven published SaaS benchmarks. A trimmed mean helps to eliminate the influence of outliers that would unfairly skew the results. At each revenue range, we took the mean after excluding top and bottom outliers. We used a non-trimmed mean when four or fewer datasets were available.

We chose metrics that were:

  1. Simple — Less is more. Metrics should reveal significant problems, not necessarily diagnose root causes.
  2. Interest aligned — Metrics should matter for operators and investors. Otherwise, benchmarks can create misalignment and distraction that detracts from performance.
  3. Clear — Metrics (and their underlying drivers) should be well understood and hard to manipulate.
  4. Evidence-based — Metrics should be supported by evidence, not gut feelings or traditions.

Let’s explore a few of these metrics in more detail. We include definitions at the bottom of this article.

Annual Recurring Revenue (ARR) Growth

As companies grew, growth slowed. A vast gulf emerged between median and top quartile growth performance. Lagging growth performance may not (necessarily) be a problem if other metrics outperform. For example, the Rule of 40 (see below) balances growth and EBITDA margin.

We saw a wide range of ARR growth across (Read more...)

June makes product analytics more accessible

Meet June, a new startup that wants to make it easier to create analytics dashboards and generate reports even if you’re not a product analytics expert. June is built on top of your Segment data. Like many no-code startups, it uses templates and a graphical interface so that non-technical profiles can start using it.

“What we do today is instant analytics and that’s why we’re building it on top of Segment,” co-founder and CEO Enzo Avigo told me. “It lets you access data much more quickly.”

Segment acts as the data collection and data repository for your analytics. After that, you can start playing with your data in June. Eventually, June plans to diversify its data sources.

“Our long-term vision is to become the Airtable of analytics,” Avigo said.

If you’re familiar with Airtable, June may look familiar. The company has built a template library to help you get started. For instance, June helps you track user retention, active users, your acquisition funnel, engagement, feature usage, etc.

Image Credits: June

Once you pick a template, you can start building a report by matching data sources with templates. June automatically generates charts, sorts your user base into cohorts and shows you important metrics. You can create goals so that you receive alerts in Slack whenever something good or bad is happening.

Advanced users can also use June so that everyone in the team is using the same tool. They can create custom SQL queries and build a template based (Read more...)