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Heavyweight hobbyist board games. Games and hobbies. United States. 90 days.
How a boutique board game publisher got its new releases recommended by AI
Boutique tabletop publisher. Engines monitored:
The challenge
Enthusiasts asking "deep euro-style strategy board games for exactly 2 players with low luck and high engine building" were only given 15-year-old classic games. The publisher's new releases were completely overlooked.
What the audit found
Every engagement starts with a baseline across a fixed set of buyer prompts.
- Core gamer mechanics (worker placement, resource drafting), BoardGameGeek complexity ratings (for example 3.65 out of 5) and true two-player rule variations were missing from machine-readable listings.
What we did, stage by stage
Using the EASY framework: Entity, Answers, Sources, Yield.
Entity
Structured mechanics, player counts, playtimes and complexity ratings into schema; updated Amazon backend catalog classifications.
Answers
Created a dedicated Board Game Mechanics and Weight Selector featuring downloadable, plain-text rulebooks and two-player balance guides.
Sources
Earned dedicated playthrough reviews from prominent tabletop channels; participated transparently in hobbyist board game discussions (r/boardgames).
Yield
Monitored 30 complex gamer-intent queries weekly; tracked holiday board game shopping recommendations leading up to Q4.
Results after 90 days
Baseline measured before any changes, against the same prompt set, engines and locations.
| Metric | Baseline | After 90 days |
|---|---|---|
| Strategy tabletop recommendation share | 4% | 34% |
| Complex strategy recommendation prompts won | 2 of 30 | 15 of 30 |
| Monthly attributed Amazon and direct web sales | $3,100 | $21,500 |
| Mechanics, weight and player count fact accuracy | 33% | 97% |
What worked, and what did not
General toy catalog marketing failed to move the needle. Precise game mechanic terminology, BGG weight parity and machine-readable rulebook files earned reliable engine citations.
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