Heap

Problem: The team can see which variation wins on the primary conversion, but they lack visibility into how each experiment impacts deeper product engagement and feature adoption inside the app. Solution: With Convert + Heap, every event is enriched with experiment and variation properties. Marketers can segment Heap funnels and usage reports by test exposure to see how each variant changes in-app behavior. Outcome: Teams move beyond surface-level conversion lifts to identify variations that improve long-term engagement and product stickiness, leading to more durable revenue gains and better product decisions.

Problem: Marketing optimizes landing pages for sign-ups, but can’t easily see if higher sign-up rates from a winning variant translate into better activation, retention, or revenue later in the customer journey. Solution: Convert automatically passes experiment and variation data into Heap for all visitors. Growth teams build Heap funnels from landing page visit to activation, usage, and purchase, segmented by variation. Outcome: They discover which variants attract high-quality users who activate and convert, not just sign up. This prevents false positives and aligns optimization with true business outcomes instead of vanity metrics.

Problem: Product and marketing run overlapping experiments across the site, but it’s hard to untangle which test actually influenced behavior when users are exposed to several experiments at once. Solution: The integration tracks multiple simultaneous Convert experiments and variations as properties on Heap events. Analysts can filter and segment by any combination of experiments inside Heap reports. Outcome: Teams confidently scale their testing program, avoid misattribution, and understand interaction effects between tests, leading to cleaner insights and safer, faster experimentation across the product.

Problem: Onboarding flows span modals, tooltips, and in-app tours that don’t map cleanly to standard page views, making it difficult to evaluate how experiments affect completion and time-to-value. Solution: Using the custom event option, teams fire Heap events that include Convert experiment and variation data at key onboarding milestones. Heap funnels then show completion and drop-off by variation. Outcome: Product managers pinpoint which onboarding variants reduce friction and accelerate activation. They ship flows that shorten time-to-value and increase the percentage of new users who reach key aha moments.

Problem: Even when a variation wins on short-term metrics, the team doesn’t know whether those users become high-LTV customers or churn quickly, limiting their ability to prioritize experiments by long-term value. Solution: Convert experiment and variation data flows into Heap, where analysts build cohorts of users by test exposure and track their long-term behavior, retention, and revenue events over time. Outcome: The business identifies experiments that create more valuable customer cohorts, not just quick wins. This shifts prioritization toward tests that improve lifetime value and informs pricing, packaging, and UX strategy.

Problem: Every new experiment requires engineers to add custom tags and properties for analytics, slowing down test launches and creating inconsistent tracking across the stack. Solution: Once the Convert–Heap integration is enabled, all Heap events automatically include experiment and variation context. Custom events can be added via a simple JavaScript snippet without backend work. Outcome: Marketing and product teams launch and analyze tests faster, with consistent tracking and fewer implementation errors. Engineering is freed from repetitive tagging tasks and experimentation velocity increases.