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When your monetization metrics look worse than they should, Qyren surfaces a recommendation explaining why and what to try. “Should” is relative to your own trailing history, not to other studios.

What triggers this

Any of:
  • ARPDAU drops more than 20% vs. the 14-day trend, sustained 3+ days.
  • Conversion rate on a specific offer drops below the 10th percentile of your catalog for 7+ days.
  • Payer share (percentage of DAU who paid in the last 7 days) drops more than 15% vs. trend.
  • First-purchase rate (share of new players who make any purchase in their first 3 days) drops more than 20%.

Common patterns we report

Offer fatigue

A specific offer has been in rotation too long. Conversion decays as your repeat-viewer base exhausts. Action: rotate it out for 2–3 weeks, or reprice.

Placement saturation

Too many offers in one placement. Players tune it out. Action: reduce offers per placement; trust personalization to pick the best one.

Price anchor shift

A new cheap offer has made existing offers feel expensive by comparison, even if they’re objectively the same price they were yesterday. Action: either retire the cheap offer or re-tier the premium ones.

Segment mismatch

An offer tagged for whales is being shown to minnows (because of a tagging mistake or an over-broad segment_tag). Action: tighten the tags.

Missing first-purchase offer

No offer under $2.99 exists in your catalog, or the one that does exists is poorly placed. First-purchase rate falls because there’s no low-friction entry point. Action: add or relocate a starter offer.

What the card shows you

  • The metric that triggered it and its current vs. baseline value.
  • A breakdown by segment so you can see who is affected.
  • A list of 2–3 candidate causes, each with enough data to confirm or dismiss.
  • One or two suggested actions, with an expected impact range (e.g. “adding a $1.99 starter offer should lift first-purchase rate from 3.1% to 4.5–6.0% within 14 days”).

What you owe the system

If you take action, mark it in the card. If you don’t, dismiss it. Either way, Qyren learns which suggestions your studio actually uses and tunes future recommendations toward those shapes.