Fern search scope by product before cross-doc noise
Scope docs search to the reader's current product or version before one broad index starts answering the wrong product's questions.
Why this can grow a startup
Multi-product docs often become less trustworthy as they grow because search pulls in adjacent but irrelevant answers. Fern's search configuration is unusually direct about that failure mode. It gives teams a softer ranking boost or a stricter default filter tied to the current product or version. That matters because the reader is usually not searching for everything your company ships. They are searching for the answer that fits the page they are already on.
Source-backed example
Fern's `settings.search` options can prioritize the current product in ranking or filter results to the current product by default while still allowing users to broaden the search later.
Source-reported evidence
Source: Fern Docs: Search configuration
Fern documents two current-context search modes: `prioritize-current-product` and `default-filter-by-current-product`.
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.
When to use it
Use this when API docs, Conversion, Developer Tools is relevant to docs search, product fit, versioning 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 API docs and Conversion, using evidence from Fern Docs: Search configuration as context—not as a promised result.
- Record a baseline for: Target users who complete the tactic’s intended next 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.
Compare a stack for your situation
Compare source-backed tactics against your product, stage, budget and channel strengths, then choose one experiment to test.
Explore the context
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Apply this with an operator
Turn isolated search tactics into a crawlable visibility system tied to demand and proof.