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SaaS

Simple Analytics: a privacy constraint became the product

An Amsterdam analytics business reached a founder-reported $100k ARR milestone without personal tracking. The lesson is a clear constraint, not a generic dashboard.

Founder
Adriaan van Rossum and Iron Brands
Launched
n/a
Model
Freemium analytics subscriptions

Published · 2 min read · 2 sources

Key takeaways

  • Adriaan van Rossum started the product in September 2018; Iron Brands joined as co-founder in 2022.
  • A March 2021 founder post reported reaching $100k ARR.
  • The company now describes itself as independent, profitable and self-funded; these are company claims.

What it is

Simple Analytics provides pageview, referrer, campaign and event reporting without cookies or personal data. Its company page positions privacy as the product’s design constraint, not an optional dashboard setting (Company page).

Timeline

  • September 2018: Adriaan van Rossum started Simple Analytics as a solo project after becoming frustrated with tracking-heavy analytics tools (Company page).
  • 8 March 2021: a founder post reported reaching $100k ARR while rebuilding the data architecture to enable filtering and broader APIs (Milestone post).
  • 2022: Iron Brands joined as co-founder to lead marketing and growth (Company page).
  • Checked 7 November 2026: the company page described a three-person team, self-funding and profitability. Its “31k+ users” figure does not identify how many are paying customers (Company page).

Why it worked

  • An explicit exclusion makes the offer legible. The company promises useful website analytics without individual tracking. Buyers can understand the tradeoff before trying it (Company page).
  • Customer requests guided infrastructure. The founder described filtering as a frequently requested feature that was awkward under the original database design, motivating the new structure (Milestone post).
  • The API made the data reusable. The milestone post names customer uses including Nomad List calculating advertising prices from analytics data. This is the vendor’s account, not a separate customer interview (Milestone post).

What to learn

  1. Differentiate by removing a behavior customers dislike, not only by adding features.
  2. Use a familiar database to test demand, then revisit architecture when a concrete customer request exposes its limits.
  3. Pair engineering with a distinct distribution owner. Compare the privacy positioning in Plausible.

Risks and what didn't work

  • The original PostgreSQL-plus-aggregate-tables approach made new filtering work more cumbersome, according to the founder. Fast prototyping created a later architecture cost (Milestone post).
  • The historical $100k ARR is a milestone, not today’s revenue. Profitability and user totals on the company page are self-reported (Milestone post, Company page).
  • Our inference: privacy limits can be a strength for one buyer and insufficient for another who needs individual attribution. Validate the required job before assuming a simpler dashboard fits everyone.

FAQ

Short answers drawn from the sections above.

What is Simple Analytics?

Simple Analytics provides pageview, referrer, campaign and event reporting without cookies or personal data. Its company page positions privacy as the product’s design constraint, not an optional dashboard setting (Company page).

Why did Simple Analytics work?

  • An explicit exclusion makes the offer legible. The company promises useful website analytics without individual tracking. Buyers can understand the tradeoff before trying it (Company page).
  • Customer requests guided infrastructure. The founder described filtering as a frequently requested feature that was awkward under the original database design, motivating the new structure (Milestone post).
  • The API made the data reusable. The milestone post names customer uses including Nomad List calculating advertising prices from analytics data. This is the vendor’s account, not a separate customer interview (Milestone post).

What can indie builders learn from Simple Analytics?

  1. Differentiate by removing a behavior customers dislike, not only by adding features.
  2. Use a familiar database to test demand, then revisit architecture when a concrete customer request exposes its limits.
  3. Pair engineering with a distinct distribution owner. Compare the privacy positioning in Plausible.

What didn't work for Simple Analytics, and what are the risks?

  • The original PostgreSQL-plus-aggregate-tables approach made new filtering work more cumbersome, according to the founder. Fast prototyping created a later architecture cost (Milestone post).
  • The historical $100k ARR is a milestone, not today’s revenue. Profitability and user totals on the company page are self-reported (Milestone post, Company page).
  • Our inference: privacy limits can be a strength for one buyer and insufficient for another who needs individual attribution. Validate the required job before assuming a simpler dashboard fits everyone.

Sources

Every link cited above, in order of first use.

  1. 1.Company page (simpleanalytics.com)
  2. 2.Milestone post (simpleanalytics.com)

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