Customer card sort before Help Center IA lock
Test your support categories with real customers before freezing the Help Center structure, because the internal taxonomy is usually worse than the team thinks.
Why this can grow a startup
Help-center structure breaks when the team groups content by org chart, feature ownership, or internal jargon instead of the way customers think. A simple card-sort exercise exposes where labels, buckets, and hierarchy feel natural to the reader. That gives the support surface a better navigation model before the archive gets too large to reorganize cheaply.
Source-backed example
Intercom recommends inviting customers to do a card-sorting exercise to test whether the Help Center structure feels intuitive.
Source-reported evidence
Source: Intercom Help · Browse Intercom Help tactics
Intercom explicitly recommends customer card sorting to test Help Center structure.
Attributed to the cited source; GrowthDex has not independently verified it. Use this as context, not as a forecast, benchmark, or recommended target.
Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.
Source discovered: May 28, 2026
When to use it
Use this when Support, Research, Documentation is relevant to ux research, help center, information architecture and you can run a bounded test with a low budget.
When not to use it
Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.
How to do it
- Choose one target segment and define the exact next action this tactic should prompt.
- Adapt the tactic to Support and Research, using evidence from Intercom Help as context—not as a promised result.
- Record a baseline for: Users who resolve the issue and complete the next useful action. Set a guardrail that would make you pause the test.
- Run a narrow pilot and choose a test window that fits the normal decision or use cycle; do not scale before you have observed the full cycle.
- Compare the signal with its baseline. Scale only if the intended action improves without crossing the guardrail; otherwise revise one variable or stop and record what you learned.
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