Automated Testing

Quantitative:

Quantitative data answers what is happening using numbers
(e.g., error counts, completion rates, time on task, crash frequency)

Best Stage: Ongoing Development → Post-Launch

Primary Goal: Repeatedly testing core systems, performance, and regressions at scale

Effort: High (set up) → Low (ongoing)

Overview

Automated testing refers to the use of scripts, bots, or software tools to automatically run and evaluate aspects of a game without human testers. While often used in QA (Quality Assurance), it also has applications in game user research, especially for collecting data at scale, identifying player behavior patterns, and validating hypotheses.

Types of Automated Testing

Telemetry Validation

Automated tests can ensure in-game event tracking (like button presses, deaths, or progression checkpoints)
Bot Playtesting

AI agents or bots simulate player behavior to test difficulty balance, pacing, and navigation. This helps researchers identify pain points or exploits before human testing.
Automated A/B Testing

Scripts randomly assign players to different gameplay variations (e.g., tutorial length, UI layout) and track behavioral differences using analytics.
Regression Testing

Automatically checks that updates or new features haven’t broken previously functional gameplay elements, preserving the player experience over time.
Session Logging & Analysis

Tools can be set to log and analyze thousands of play sessions, surfacing trends like choke points, early quits, or unexpected strategies