Salesforce

Problem: Marketing runs dozens of A/B tests, but success is judged on clicks and form fills. Leadership still can’t see which experiments create qualified pipeline or closed-won revenue in Salesforce. Solution: Convert sends experiment and variation exposure as custom events into Bizible, which syncs to Salesforce. Every lead and contact record shows which tests they saw, enabling experiment-level attribution in standard Salesforce reports. Outcome: Teams finally connect tests to opportunities, pipeline, and revenue. Budget and roadmap decisions shift from vanity metrics to Salesforce-backed business impact, increasing confidence in experimentation investment.

Problem: Pricing page tests often boost trial signups or demo requests, but it’s unclear which variation actually leads to higher ACV, faster sales cycles, or better win rates in Salesforce. Solution: Convert tracks which pricing variation each visitor sees and streams that data to Bizible and Salesforce. Revenue teams segment opportunities and deals by experiment and variation in Salesforce dashboards. Outcome: Companies identify the pricing experiences that generate larger deals and healthier margins, not just more leads. Pricing tests are prioritized and iterated based on real revenue lift, improving monetization strategy.

Problem: Sales complains about lead quality while marketing celebrates higher conversion rates. No one can pinpoint which on-site experiences are sending sales-ready leads versus tire kickers. Solution: Convert + Bizible tag each lead in Salesforce with the experiments and variations they interacted with. RevOps builds Salesforce reports that correlate exposure to specific tests with MQL→SQL conversion and opportunity creation. Outcome: Sales and marketing rally around a shared Salesforce view of which experiences produce high-intent, high-converting leads. Marketing scales winning journeys and cuts low-quality variants, improving funnel efficiency.

Problem: ABM teams want to tailor site experiences for target accounts, but personalization decisions are made in isolation from Salesforce insights about account value, stage, or industry. Solution: Convert personalizations run on-site while Bizible passes experiment exposure into Salesforce. Teams analyze which variations resonate with high-value segments and opportunity stages, then refine Convert targeting rules using those learnings. Outcome: High-value accounts see experiences proven to work for their segment. Engagement, opportunity progression, and win rates improve, and ABM programs become measurably more effective in Salesforce reports.

Problem: Experiment backlogs are prioritized by intuition or top-of-funnel metrics. It’s hard to know whether to focus on hero banners, forms, or product pages without revenue-based evidence. Solution: With Convert experiment data flowing into Bizible and Salesforce, marketers compare the revenue impact of past tests across different parts of the funnel. Roadmaps are built using Salesforce dashboards that rank experiments by pipeline and ARR influence. Outcome: Teams double down on experiment types and pages that consistently move revenue, not just clicks. Testing velocity stays high, but effort is concentrated where Salesforce shows the biggest financial upside.

Problem: Executives struggle to see the ROI of experimentation programs. Reporting lives in separate tools, and tying tests to revenue requires manual, error-prone spreadsheets. Solution: Convert experiment and variation data is centralized in Bizible and surfaced in Salesforce. RevOps builds executive dashboards that show pipeline, revenue, and win rates by experiment, variation, and channel. Outcome: Leadership gets a single Salesforce view of experimentation performance. Funding, headcount, and strategic bets are justified with clear ROI, elevating experimentation from a tactical activity to a core growth lever.