PlayDirective
Validation demo · simulated data

AI Product Analyst

The analyst layer explains only what PlayDirective's deterministic decision layer can support. Root-cause ideas are explicitly labeled as hypotheses, not facts.

Grounded mode
Executive summary

Fix mobile onboarding before you scale growth.

The strongest supported issue is a material mobile-versus-desktop retention gap. The current evidence justifies investigation and an onboarding experiment; it does not prove a specific UX defect caused the decline.

Priority 01
High confidence

Investigate mobile onboarding friction

Evidence

Mobile D1 retention is 8.7% versus 17.9% on desktop.

Why it matters

This is the strongest supported signal because the segment divergence is large and directly tied to the first-session experience.

Next action

Compare the first-session funnel by device and test a shorter mobile onboarding flow.

Priority 02
Medium confidence

Convert traffic growth into monetization

Evidence

DAU is growing materially faster than daily revenue.

Why it matters

Traffic growth without proportional revenue growth suggests a monetization efficiency issue worth investigating before scaling acquisition.

Next action

Inspect payer conversion and offer timing before increasing acquisition spend further.

Causality guardrail

Candidate causes such as onboarding friction or offer timing are hypotheses. The analyst may recommend how to validate them, but it must not present them as proven causes unless the underlying decision bundle explicitly permits a causal claim.

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