Executive Summary

Solo app makers and micro‑SaaS publishers (roughly 1.5M potential publishers) struggle to stitch together app store analytics, ad network attribution, and backend events to measure ROAS and LTV across channels. They face rising ad CPCs and limited bandwidth—decisions that used to be made with analyst teams now fall to individuals who need clear, actionable attribution and cohort metrics. A pragmatic product would be a lightweight dashboard that ingests App Store/Google Play APIs, major ad network attribution (including SKAdNetwork and server‑to‑server events), and popular managed backends, normalizes events, and surfaces LTV, cohort ROAS, anomaly alerts and prescriptive next steps. Built as a low‑cost SaaS with opinionated defaults and an annual pricing target aligned to the market estimate ($2.0K ACV used to arrive at a $3.0B market), the MVP could focus on 10–15 common integrations and automated AI‑driven insights to reduce the need for manual analysis. Key challenges will be fragmentation of APIs, privacy constraints (SKAdNetwork/ATT), and building trust around sensitive revenue data—technical but solvable problems if prioritized. Timing is favorable: rising ad costs make optimization urgent, open APIs and managed backends lower integration cost, and affordable AI enables automated anomaly detection and prescriptive recommendations that solo devs value. To stand out in a medium‑competition landscape you must focus on clear, opinionated UX for non‑analysts, privacy‑first attribution, a narrow vertical go‑to‑market, and tight integrations with 3–4 popular stacks—if you can execute this in 6–9 months the opportunity is attractive but not trivial.

Market Opportunity

Dashboard that consolidates app analytics and ad attribution for solo devs targets a $3.0B = 1.5M app & micro-SaaS publishers × $2.0K ACV total addressable market with medium saturation and a year-over-year growth rate of 12% YoY — mobile analytics and app economy growth (sources: Sensor Tower, App Annie trend reports).

Key trends driving demand: Ad CPC increases — rising ad costs force smaller publishers to optimize ROAS and LTV, creating demand for better attribution.; Open APIs and managed backends — accessible APIs from app stores and managed backends like Supabase make integrations easier and cheaper.; AI-driven insights — affordable AI models enable automated anomaly detection and prescriptive recommendations that previously required analyst teams.; Indie dev ecosystem growth — active communities and maker culture accelerate word-of-mouth distribution for niche dev tools..

Key competitors include AppsFlyer, Amplitude, Looker Studio / DIY pipelines (Google Data Studio).

Sign in to access

Dashboard that consolidates app analytics and ad attribution for solo devs

Executive Summary

Market Validation

Market Opportunity

More in Data & Analytics

Automated reporting for data/ML pipelines that generates model-aware operational reports

Stop full-table scans on lakehouses with spatial + time indexing

SaaS founders can't explain churn — automated root‑cause analysis & recovery

SEC JS-pagination blocks comment scraping — build headless crawler + NLP index

Restore Excel & human-in-loop workflows for modern BI/AI pipelines

Measure real process bottlenecks first — then automate with robots