Wishlist activity ROI calculator

Is the wishlist activity worth its cost?

Estimate what a booth, festival, ad campaign, creator sponsorship, or other activity needs to return before you commit the budget.

Cost per wishlist
What you paid to generate each measured wishlist.
Wishlist value
Expected developer receipts from one added wishlist.
ROI
(Developer receipts − activity cost) ÷ activity cost.

Editable assumptions

Model the activity

Name the booth, campaign, event, or promotion.
Include the full incremental cost: space, travel, build, ads, fees, and contractors.
Use incremental wishlists attributable to the activity, not all wishlists added during the period.
Use the price you expect buyers to pay after launch discounts.
The share of these wishlists you expect to become purchases in the period being assessed.
The share of player spend you expect to receive after the store fee and other deductions.

Estimated return

Convention booth

Below break-even
Return on investment-96.5%
Profit / loss-$1,930
Developer receipts$70From 10.0 expected purchases
Cost per wishlist$20.00Activity cost ÷ added wishlists
Value per wishlist$0.70Price × conversion × developer share
Player spend$100Before the developer revenue share

Break-even test

What would this activity need to achieve?

Wishlists needed2,858At the current price, conversion, and share
Purchases needed286To recover the activity cost
Conversion needed285.7%With only the wishlists entered above

Even 100% conversion would not recover this cost from the attributed wishlists alone. The activity would need more wishlists, a higher realized price, or value beyond direct wishlist-attributed sales.

Use the result carefully

A financial lens, not the whole event story.

This model counts only sales attributed to the wishlists entered. Booths and campaigns may also create press, followers, playtesters, community relationships, publisher conversations, content, or learning. Count those separately rather than hiding them inside an optimistic conversion rate.

Conversion varies by game, wishlist quality, price, discount, launch timing, and measurement window. Run conservative and optimistic cases before making the decision.