Game economy designers tune drop rates, pity thresholds, and currency rates for revenue, but average-case math can hide the experience of unlucky players.

Telltail is a B2B SaaS preview tool that simulates players across the full range of luck, showing revenue impact and sentiment risk side by side before an economy change ships.

Average-case economics don’t show the experience of the unlucky tail.

I looked at job postings, developer discussions, academic research, and public examples of monetization backlash. Together, they pointed to a gap: economy tools focus on expected outcomes, while player reactions can be driven by the extremes.

This research shaped the direction for Telltail. See all six sources

Priya owns the currencies, drop tables, and pity curves for an F2P mobile economy, working from spreadsheets that show the average outcome but not what an unlucky player actually experiences. See Priya’s full profile

Still brainstorming at this point, not building: three ways to surface the unlucky tail, weighed against the research and each other before any UI existed. See all three directions

The core workflow is Home → Create/Open Change → Adjust Parameters → Review Impact → Save or Send for Review. As parameters change, simulated outcomes update live.

Games, Reports, Settings, and Profile complete the product shell but were outside this build.

I prototyped the first dashboard in Figma Make. It gave revenue impact, churn risk, and spend conversion equal visual weight, which didn’t match their actual priority: churn and spend conversion are supporting metrics, not equal ones.

The fix wasn’t more metrics. It was an order: sentiment risk first, then revenue impact, with the supporting metrics beneath it.

The rebuilt workspace pairs the parameters Priya adjusts with outputs ranked by priority, so the sentiment risk score leads instead of competing with revenue and churn. See the full input/output breakdown

The rebuild also moved to a dark theme for legibility. Telltail contrasts the urgency of the games it analyzes with a calmer environment for comparing outcomes and making decisions.

The visual system uses Spline Sans, Spline Sans Mono, a dark monochromatic base, and a green-to-red semantic scale for revenue and risk. The dragon-tail logo references both the product name and the unlucky tail of the distribution.

The main challenge was deciding what deserved attention first. The final hierarchy puts sentiment risk first, followed by revenue impact and supporting metrics, and carries that structure from economy inputs through the resulting dashboard.

The current simulation focuses on whether a player obtains a desired character. A fuller model would account for systems where multiple copies determine functional value, such as Genshin Impact’s Constellation system.

Future versions could model the number of copies needed to reach different power thresholds and how those thresholds affect sentiment risk.