AI vs non-AI activation benchmark
Measure AI feature usage against the core product path and by customer segment so the team sees whether the AI is helping the right users or merely attracting the wrong curiosity.
Why this can grow a startup
AI usage can look encouraging while still hiding a product mistake. A team may see a lot of interaction and assume the feature is working, when the real pattern is that non-ICP users are playing with it more than the buyers the product actually needs. Benchmarking AI usage against the normal activation path and across segments forces a harder question: is the AI improving the product's real job or only creating extra attention around itself? That view helps teams tune positioning, onboarding, and roadmap bets before they build too much around vanity engagement.
Source-backed example
PostHog found marketers and product managers used Max AI more often than product engineers, which pushed the team to rethink who the assistant was actually serving.
Source-reported evidence
Source: PostHog Newsletter · Browse PostHog Newsletter tactics
PostHog compares Max AI usage by customer type and against normal feature usage instead of reading raw AI engagement in isolation.
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 26, 2026
When to use it
Use this when Analytics, Activation, Positioning is relevant to ai products, analytics, segmentation 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 Analytics and Activation, using evidence from PostHog Newsletter 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
Did you launch this experiment?
Report a launch to help us understand which growth ideas founders put into practice.
Apply this with an operator
Choose product surfaces that compound distribution without hiding weak activation or retention.
SOURCE HUB
More tactics from PostHog Newsletter
Explore related GrowthDex examples and evidence connected to PostHog Newsletter.
Open PostHog Newsletter source hub