Free-text signup attribution for dark funnel discovery
Add a free-text 'How did you hear about us?' field during signup instead of a dropdown to uncover the untraceable channels driving 30-50% of B2B signups.
Why this can grow a startup
Traditional analytics attributes most dark funnel traffic as 'Direct' or 'Organic,' hiding the real channels that drive trust and buying decisions. A free-text field captures the actual discovery path in the user's own words, revealing channels like private communities, personal recommendations, and podcast mentions that you'd otherwise never invest in. Founders who discover these hidden channels can double down on fueling word-of-mouth instead of over-investing in trackable but lower-trust paid channels.
Source-backed example
Documented by http://Postiv.ai (February 2026) across hundreds of SaaS founders — those who replaced dropdown attribution with a free-text field consistently discovered that 30-50% of signups came from private Slack channels, forwarded newsletters, DM recommendations, and other dark funnel sources invisible to analytics.
Source-reported evidence
Source: postiv.ai · Browse postiv.ai tactics
50% of signups came from private Slack chan
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: March 23, 2026
When to use it
Use this when Communities, Referrals is relevant to 0-100, 100-1K and you can run a bounded test with a free 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 Communities and Referrals, using evidence from postiv.ai as context—not as a promised result.
- Record a baseline for: Share of referred users who reach the activation milestone. 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
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