Roistat

Problem: CRO and marketing teams run tests in Convert and campaigns in Roistat, but performance lives in separate tools, making it hard to see which experiments truly move revenue and leads. Solution: Install both tracking codes and send Convert experiment and variation names into Roistat as custom events. Every visit in Roistat is automatically enriched with testing context from Convert. Outcome: Teams get a single source of truth for test performance. They can see which variations lift key KPIs across channels, align on winners faster, and prioritize experiments that drive real business outcomes.

Problem: Winning variations are chosen on on-site metrics like CTR or form submits, but marketers can’t reliably tie those wins to downstream revenue and LTV tracked in Roistat. Solution: Use the integration to pass Convert variation names into Roistat and include them in attribution and revenue reports. Each sale or lead is tagged with the experiment and variation a user saw. Outcome: Marketers see which variations generate higher revenue per visit, not just more clicks. Budget and roadmap decisions are based on profit impact, improving ROAS and experimentation ROI.

Problem: Channels like contextual ads, SEO, and paid social perform differently under each test variation, but this nuance is lost when A/B test data isn’t visible in Roistat’s channel reports. Solution: Send Convert experiment and variation data as custom events to Roistat and segment performance by traffic source, campaign, and variation in one dashboard. Outcome: Teams discover which combinations of channel + variation drive the best conversion rates and revenue. They can tailor landing experiences per channel and reallocate spend to the highest-performing pairings.

Problem: CRO teams suspect certain audiences respond differently to variations, but can’t easily slice experiment results by device, region, or campaign cohorts inside Convert alone. Solution: With Convert data in Roistat, analysts build segments using Roistat’s rich visitor attributes—device, geo, campaign, UTM tags—and overlay experiment and variation names on top. Outcome: They uncover segment-specific winners (e.g., mobile users in certain regions) and design targeted experiences. This leads to more precise personalization and higher conversion lifts per audience.

Problem: Analysts spend hours exporting CSVs from Convert and Roistat, then merging them in spreadsheets just to build basic experiment performance reports for stakeholders. Solution: The integration automatically streams experiment and variation names into Roistat, where they become standard fields in dashboards and reports—no exports or manual joins needed. Outcome: Reporting cycles shrink from days to minutes. Teams can monitor experiments in near real time, share consistent dashboards, and redirect analyst time from data cleanup to insight generation.

Problem: Experiment ideas are prioritized on intuition or isolated on-site metrics, disconnected from broader marketing goals like CAC, payback period, or channel profitability tracked in Roistat. Solution: By viewing Convert experiments directly in Roistat, product marketers and growth teams evaluate tests against full-funnel metrics and attribution models used for campaign planning. Outcome: Experiment roadmaps become tightly aligned with marketing strategy. Teams prioritize tests that improve acquisition efficiency and revenue, creating a continuous optimization loop across site and media.