Put Your Revenue Data Where Your Product Data Lives
If your company is using or moving towards outcome-based pricing or usage-based models, you’re facing a familiar challenge: product usage lives in your data warehouse, sales context lives in your CRM, and getting them to work together requires endless data engineering tickets.
The business needs answers now.
- Which accounts are at risk based on usage patterns?
- Which customers are ready for expansion conversations?
- How do we forecast revenue when pricing is tied to outcomes and consumption?
But while product-led and usage-based models become table stakes, many GTM leaders and RevOps teams are still waiting weeks for custom dashboards, stitching together exports in spreadsheets, or making decisions with incomplete data.
That sort of fragmented, delayed process creates blind spots in pipeline, slows down go-to-market execution, and forces lean RevOps teams to chase data instead of driving revenue.
Today, we’re changing that.
We’re excited to announce our native integration with BigQuery, built to give RevOps teams one unified view of product usage and CRM activity – without waiting on data engineering.
Bring Product Data and Sales Context Together in One Platform
Disconnected systems create revenue blind spots: usage signals that could predict churn go unnoticed, expansion opportunities sit dormant in product data, and sales teams operate without visibility into how customers actually use the product.
With this new integration, RevOps teams using Salesforce or HubSpot can now connect AccountAim directly to BigQuery, automatically syncing transactional and product usage data alongside CRM records. With BigQuery as your data warehouse and AccountAim as your revenue intelligence layer, your team gets real-time visibility into the signals that matter for outcome-based pricing, with the ability to surface insights and trigger workflows without writing a single SQL query.
If you’re a lean RevOps team managing consumption-based or outcome-driven pricing models and looking to move faster, forecast smarter, and close more deals, read on to learn how AccountAim turns your BigQuery data into revenue action.
Empower RevOps to Move at the Speed of Business
RevOps teams can’t wait two weeks for a data engineer to pull a usage report. With AccountAim and BigQuery, teams can access product usage, transaction history, and behavioral signals in real time – without technical dependencies.
With this integration, RevOps teams can:
- Sync transactional data, product usage metrics, and behavioral signals from BigQuery into AccountAim
- Combine usage data with Salesforce or HubSpot records to create a complete customer profile
- Build segments and scoring models based on consumption patterns, feature adoption, and engagement
- Trigger automated workflows when usage crosses critical thresholds
- Surface usage insights directly in the tools your sales team already uses
No SQL required. No engineering backlog. No waiting.
Make Outcome-Based Pricing Predictable and Scalable
The shift to outcome-based and consumption pricing is accelerating. Customers want to pay for value delivered, not seats purchased. But if your usage data lives in a warehouse while your revenue forecasts live in Salesforce, you’re flying blind.
AccountAim eliminates that gap by connecting BigQuery’s transactional data with your CRM’s sales context.
With one unified platform, revenue teams get:
- Real-time visibility into consumption trends and usage velocity across accounts
- Early warning signals for churn risk based on declining usage or feature abandonment
- Expansion triggers based on usage thresholds, feature adoption, or transaction volume
- Accurate forecasting that factors in both pipeline and product engagement
With product usage and CRM data unified, your team can price confidently, forecast accurately, and identify revenue opportunities before they slip away.
Build Revenue Motions That Scale With Your Data
Teams choose BigQuery because they’re collecting massive amounts of event data and need a warehouse that can handle it. AccountAim extends that foundation by providing the no-code intelligence layer needed to turn raw data into revenue action:
- Multi-source data unification (product events, billing transactions, support tickets, and more)
- Custom scoring models based on usage intensity, engagement quality, and transaction patterns
- Pre-built workflows for common use cases like usage-based upsells, churn prevention, and expansion identification
- Native syncs back to Salesforce and HubSpot so sales teams see insights where they work
As your data evolves and your go-to-market motion matures, AccountAim adapts with you. We’re making it possible for RevOps teams to iterate on revenue strategies without rebuilding data pipelines.
Track What Matters as Pricing Models Evolve
In an era of outcome-based pricing, tracking usage isn’t optional – it’s the foundation of your revenue model. Customers are paying for results, and your ability to measure, monitor, and act on usage data determines whether you retain and grow those accounts.
AccountAim makes usage tracking simple and actionable:
- Automated usage monitoring tied directly to account health and renewal risk
- Consumption-based signals surfaced in account views, opportunity records, and sales workflows
- Custom alerts when usage patterns indicate risk or opportunity
- Historical usage trends that inform pricing discussions and contract negotiations
With AccountAim and BigQuery, you’re not just tracking usage – you’re turning it into a competitive advantage.
Get More Value From BigQuery and Your CRM
AccountAim and BigQuery together unlock what RevOps teams have been asking for: one connected view of product engagement and sales activity, with the automation and intelligence to act on it – without waiting on data engineering.
If you’re managing outcome-based pricing or usage-driven models and looking for a simpler, faster, and more accurate way to connect product data with revenue execution, we’d love to chat.
Request a demo with our team today and see how RevOps teams are closing the gap between product usage and revenue growth.
