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You can now work together in the Visual Editor without accidental overwrites. When teammates edit the same experience, the Visual Editor detects changes and prompts you to Reload or Overwrite & Save. A short safety window helps prevent conflicts, and Change History lets you see who changed what. Overwrite carefully—this replaces the latest saved version. No impact on live traffic. Learn more: https://support.convert.com/hc/en-us/articles/edit-locking-version-conflict-prevention-in-the-visual-editor#overview

Auto-Allocation powered by Multi-Armed Bandits (MAB) lets Convert automatically send more traffic to better-performing variations while your test is running. Instead of fixed splits, MAB adapts in real time—helping you learn faster, reduce wasted traffic, and drive more conversions during the experiment. Works with both Frequentist and Bayesian stats and supports strategies like Thompson Sampling, Epsilon-Greedy, and UCB. Once enabled, traffic allocation is fully automatic, with clear reporting to show how it evolves over time. Learn more: https://support.convert.com/hc/en-us/articles/multi-armed-bandit-mab-auto-allocation-in-convert

You can now combine audience conditions using AND logic, not just OR. This means you can target users who meet multiple conditions at once (e.g. from Google and Yahoo), giving you tighter, more accurate audience definitions. To use this, make sure your project is running on the new tracking script. Learn more: https://support.convert.com/hc/en-us/articles/115000009891-define-audiences-for-your-experience

You can now remove specific data directly from experiment reports, no support ticket needed. Owners and Admins on Pro and Enterprise plans can delete selected event types and date ranges (including specific conversion goals) straight from the report view. This gives you more control when cleaning up test data caused by setup issues, QA traffic, or unexpected events. The flow is simple: choose the date range, select the event types, review the impact, and confirm. Changes may take a few seconds to reflect, and once data is removed, it can’t be restored—so you’re always in control. Learn more in our Help Center: https://support.convert.com/hc/en-us/articles/remove-report-data-feature

We’ve added Average Order Value (AOV) and Average Products Per Order (APPO) to experiment reports to give you deeper insight into order-level performance. AOV (Average Order Value) shows the average revenue per order for the selected date range or segment. It appears as a currency column alongside RPV in the Revenue table, while all RPV statistics (lift, confidence, etc.) continue to work exactly as before. APPO (Average Products Per Order) shows the average number of items per order. It uses the same product count data as APPV, but is calculated per order instead of per visitor. These metrics make it easier to understand whether changes are driving bigger orders, more items per order, or both—not just more visitors converting. Learn more about experiment reports and these metrics: https://support.convert.com/hc/en-us/articles/understanding-report-metrics-in-convert

You can now A/B test pop-ups inside Convert with the same rigor as any experiment so you validate offers, messages, and timing before rollout. Available on Pro & Enterprise plans.