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Sucker for Love: First Date

Akabaka · 2022 · $9.99 · Indie · deal grade B

Measured on 2026-09-26 02:45 UTC, 10 days ago. The whole catalog is re-measured daily; a game that just launched can move fast between passes.

  • Estimated net residual revenue: $575 to $863 per month
  • Opportunity: $935 per month at x1.30 dormancy
  • Estimated lifetime owners: 107.0k
  • 98% positive across 3023 reviews · 11.5 reviews/month

Why it's flagged

  • Developer active, last post 5 months ago
  • Studio active elsewhere (3 titles tracked), so this one may welcome a partner
  • Store page localized in only 2 language(s)
  • Last discounted 3 months ago, 7 sales in the last 12 months

Analyst notes (AI-assisted)

Note written 2026-09-05; the live figures above take precedence over any numbers in it.

A 2022 indie visual novel where players seduce eldritch horror entities through ritual-building mechanics, shipping with strong art direction and voice acting.

Sucker for Love occupies a viable niche at the intersection of visual novel and light puzzle mechanics with remarkable attach rate: nearly all who buy complete it, leaving solid four-figure monthly residuals despite a mid-sized owner base. The community is unusually devoted (see review tone) and the sequel's existence validates the IP. This is a quiet earner suitable for a publisher looking to fold an established franchise into a catalog management agreement, or for a developer seeking to acquire dormant back-catalog titles that require minimal servicing. Most realistic play: publishing.

  • Risk: Niche romantic/horror hybrid with limited mainstream appeal and no seasonal or event-driven sales cycle to drive retention.
  • Risk: Missing basic UX features (achievements, remappable controls, keyboard navigation) noted by players; technical debt may limit porting or live-ops potential.
  • Risk: Median session is under 6 hours; post-completion residuals depend entirely on new player acquisition, which has flattened since launch.

This case as Markdown · Estimates carry ±30-50% error per title.