Baidu Analytics (Baidu Tongji)

Problem: The ecommerce team runs homepage A/B tests in Convert but can’t clearly see which variation drives higher revenue and order value inside their existing Baidu Analytics ecommerce reports. Solution: They map a Baidu Analytics Custom Dimension to Convert’s experiment and variation data. Every Baidu Analytics hit now carries the visitor’s experiment and variation, visible in standard ecommerce and revenue reports. Outcome: Revenue, AOV, and conversion rate can be broken down by variation directly in Baidu Analytics. The team quickly identifies the winning homepage, quantifies uplift in local currency, and scales the best-performing experience with confidence.

Problem: Marketing has dozens of Baidu Analytics goals configured for sign-ups, downloads, and lead forms. Re-creating these goals in Convert for every experiment is error-prone and slows down testing velocity. Solution: They activate the Baidu Analytics integration in Convert and assign a Custom Dimension slot. Experiment and variation data flows into Baidu, where existing goals are simply segmented by that dimension—no duplicate setup. Outcome: All current goals become instantly usable for A/B test evaluation. The team saves hours of configuration per test, reduces tracking discrepancies, and can launch more experiments without sacrificing measurement quality.

Problem: Traffic from Baidu search lands on multiple page variants, but the product team can’t see how each variant affects drop-off in their existing Baidu Analytics funnels. Solution: Convert assigns visitors to landing page variations and passes experiment and variation names into a Baidu Custom Dimension. Funnels in Baidu Analytics are then segmented by variation to expose step-by-step behavior. Outcome: The team pinpoints which landing page variant reduces abandonment at each funnel step. They prioritize the highest-performing variant for Baidu search traffic, improving conversion rates from organic and paid Baidu campaigns.

Problem: Leadership wants a single Baidu Analytics dashboard showing how ongoing experiments affect key KPIs, but test data lives separately from their main analytics views. Solution: With the integration enabled, Convert sends experiment and variation data into a dedicated Baidu Custom Dimension. Analysts use this dimension to build custom Baidu dashboards and reports centered on test performance. Outcome: Executives see real-time experiment impact on traffic, engagement, and revenue in the dashboards they already use. Experimentation becomes more transparent, and data-backed decisions gain faster buy-in across the organization.

Problem: CRO specialists want to understand how different variations affect micro-behaviors—scroll depth, page views, and content engagement—but can’t easily slice Baidu Analytics data by experiment. Solution: Convert automatically appends experiment and variation identifiers to Baidu Analytics hits via the mapped Custom Dimension. Marketers then create Baidu segments filtered by specific experiments and variations. Outcome: They uncover nuanced behavior differences between variations, such as deeper engagement or more product views. These insights inform better hypotheses, more targeted follow-up tests, and a richer understanding of user intent.

Problem: A global retailer operates multiple localized Chinese storefronts tracked in Baidu Analytics, but struggles to tie localized UX tests in Convert to Baidu’s multi-store ecommerce metrics. Solution: They enable the Convert–Baidu integration across all storefronts, mapping a shared Custom Dimension for experiments. Each store’s Baidu ecommerce reports can now be filtered by experiment and variation. Outcome: The retailer compares test impact on revenue and conversion across different Chinese sites in one analytics environment. They standardize on winning patterns, accelerate localization decisions, and grow revenue in Baidu-centric markets.