RevenueCat vs Holistics
Side-by-side trajectory, velocity, and editorial themes.
Stretching from subscription infrastructure into hybrid subs+ads revenue tracking, with paywalls getting smarter.
RevenueCat is broadening from subscription-only to subscription-plus-ads with in-app ad revenue tracking now in public beta — apps using AdMob or AppLovin can send ad events through the SDK and see ad and sub revenue side by side. Paywalls have gained meaningful logic depth (Paywall Rules to show/hide components by intro-offer eligibility or custom variables) and the iOS/Android fallback paywall now auto-styles using the app icon's dominant color. Operational tooling has caught up: archived offerings/products/entitlements, OAuth token visibility and revocation, predicted-LTV winners in Experiments.
The product is moving from 'subscription billing infra' to 'mobile monetization platform.' Ad revenue tracking is the headline because it changes who RevenueCat is for — every freemium app with mixed monetization, not just sub-driven apps. Paywall Rules suggest the company is going deeper on the merchandising layer rather than ceding it to MMP-adjacent tools. The Experiments-side LTV predictions and locale-aware paywalls signal continued investment in the optimization story.
Expect the in-app ad revenue beta to GA with deeper SDK support for more ad networks, more sophisticated Paywall Rules conditions (likely user-segment and behavioral triggers), and tighter Experiments + ad-revenue correlation as customers compare hybrid monetization mixes.
Holistics turns the BI dashboard into a conversational AI surface, on customer-owned models.
Holistics is well into a BI-meets-AI productization phase, layering conversational analytics on top of its existing modeling and dashboard core. Recent releases mix consumer-grade dashboard polish (auto-run filters, K/M/B number formatting, percentile calculations) with deeper AI plumbing: bring-your-own Claude and Gemini keys, per-user AI access controls, and now an Ask AI that asks clarifying questions back. The GitHub App integration also signals enterprise-readiness work alongside the AI push.
The product is being repositioned from a self-service BI tool to an AI-mediated analytics workspace where natural-language exploration is the headline interaction. Crucially, the team is pushing AI as an infrastructure layer customers can own — BYO LLM keys, granular access policies — rather than locking customers into a vendor-managed model. The dashboard improvements look incremental, but read as ground prep for AI agents to consume and manipulate dashboards more reliably.
Expect the next quarter to bring agentic dashboard editing — Ask AI not just answering but proposing dashboards and saving them — plus expanded BYO LLM coverage (likely Azure OpenAI or open-weights via OpenRouter) to widen procurement options for enterprise buyers.
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