Analytics tools are either too expensive for low-traffic side projects relative to total infra spend or lack essential features like data export, per-user attribution, bot protection, and usable filters, forcing wasted engineering time and lock-in.
Existing analytics tools for side projects are either overly complex/expensive or lack key features like per-user attribution, data export, bot protection, and usable filters, leading to high costs and frustration for low-traffic users.
So,.. I Decided to Build My Own Analytics, This Is How It Went
So,.. I Decided to Build My Own Analytics, This Is How It Went
So,.. I Decided to Build My Own Analytics, This Is How It Went
"The funniest part is spending a month engineering a system to save $14/month"
commentThe funniest part is spending a month engineering a system to save $14/month and somehow still feeling satisfied afterward because the existing tools annoyed you enough
Solo builders running low-traffic personal websites and micro-SaaS projects who want basic visitor insights without enterprise complexity or cost.
Multiple repeated complaints around cost for low traffic, lack of export, poor attribution, no bot protection, and terrible filters across indie communities.
Ultra-affordable for <10k monthly visitors with export freedom and bot protection that Plausible and DataFast lack, while staying far simpler than PostHog.
Lightweight web analytics platform purpose-built for indie side projects with affordable pricing, full data export, per-user attribution, bot protection, and simple filters.
Users explicitly reject $40-500/year tools when infra is only $150 total and complain about spending a month to save $14; $9/mo is trivial compared to their engineering time value.
“Get reliable side-project analytics without paying enterprise prices or building your own.”
Lightweight web analytics platform purpose-built for indie side projects with affordable pricing, full data export, per-user attribution, bot protection, and simple filters.
Launch on Indie Hackers, r/SideProject, Product Hunt, and X indie dev communities with free tier for initial traction.
Indie users may demand more advanced features quickly after basic launch, stretching MVP scope.
Delivering reliable bot filtering without false positives on low-traffic sites is technically tricky.
Users accustomed to Google Analytics may not switch even with better UX for their use case.
Frequent exports on paid tier could raise storage/egress costs unexpectedly.
Run an Investment Memo to get a structured Go / No-Go verdict, competitor landscape, unit economics, and a 90-day validation roadmap for this opportunity.
Generate an investment memoThis idea scores in the upper-middle range of opportunities surfaced by MonetScope, with a validation sub-score of 8/10 against 4 independently sourced evidence signals. A "promising" rating usually indicates a real pain has been detected and discussed in the open, but the pipeline did not find enough signal to flag it as urgent or high-frequency. These opportunities can still produce excellent businesses — they often correspond to "boring" problems that established players have ignored — but the founder should expect a longer customer-development cycle to confirm willingness to pay.
It sits at the intersection of "ai-powered", "analytics", "data-management", which makes it relevant to a specific subset of founders rather than a generic horizontal opportunity. SaaS opportunities at this stage tend to win on the strength of their initial wedge — a single workflow that the target user runs every week, where the existing solution is either spreadsheets, a clunky incumbent feature, or a manual process they hate. The build cost is moderate; the distribution cost is everything. The MonetScope pipeline surfaces this category alongside other saas signals, which is why it appears here rather than in a generic "trending ideas" feed.
Scores are derived from real forum discussions across Reddit, Hacker News and X, weighted by evidence volume and signal quality. How scoring works
MonetScope does not generate ideas from a language model's imagination. Every opportunity on this site is anchored to specific source posts and comments from real public discussions — typically on Reddit, Hacker News, or X — where actual users describe the pain in their own words. The AI's role is structuring, scoring, and grouping those signals into a navigable opportunity, not inventing the problem.
MonetScope's spider pipeline runs continuously and surfaces opportunities as new evidence accumulates. The "Updated" date in the header reflects the most recent re-scoring of this specific opportunity. Most saas opportunities visible in the public catalog draw from discussions in the last 30-60 days; older signals are de-prioritized because user pain shifts faster than most founders assume.
Overall score is a composite across six dimensions — pain, urgency, willingness to pay, market size, defensibility, and execution ease — designed to give a single number for triage. Validation score is narrower: it asks "how cleanly does the same signal repeat across independent sources?" An opportunity can score high on overall but lower on validation when one or two large discussions dominate the evidence; conversely, validation can be high on a smaller-overall idea where the signal is consistent but the addressable market is modest.
