We help mid-market B2B companies translate complex data into actionable, predictable revenue strategies. No fluff, just measurable outcomes.
Trusted by data-driven B2B enterprises
Most B2B companies collect millions of data points but fail to connect them to actual business outcomes. Sound familiar?
You know marketing is driving leads, but you can't accurately trace which campaigns are generating high-LTV enterprise clients.
Customers leave seemingly out of nowhere. Your team is reacting to cancellations instead of proactively saving at-risk accounts.
Executives have 15 different dashboards showing conflicting numbers. Trust in the data is low, leading to decision paralysis.
We don't just build dashboards. We architect a complete data ecosystem that acts as a central source of truth for your sales, marketing, and success teams.
We analyze your current CRM, analytics stack, and data cleanliness to find the leaks in your revenue funnel.
We design a custom data model that aligns with your specific B2B sales cycle and business objectives.
Our engineers build the pipelines, while our consultants train your team on how to actually use the insights.
We don't offer generic advice. We deploy specialized data engineering and advanced analytics to solve specific revenue bottlenecks.
Map multi-touch buyer journeys spanning 6-12 months. Know exactly which touchpoints influence enterprise deals.
Machine learning models that identify high-risk accounts 90 days before they cancel, giving your CS team time to act.
Centralize data from Salesforce, Hubspot, and proprietary apps into a clean, queryable Snowflake or BigQuery environment.
Stop wasting sales time on unqualified prospects. We build dynamic scoring models based on historical closing data.
Custom BI development (Tableau, Looker, PowerBI) that gives the C-suite real-time visibility into company health.
Real outcomes from B2B companies that stopped guessing and started relying on structured data.
The Challenge: The client had a massive dataset of user activity but no way to know which behaviors indicated a user was likely to cancel.
The Outcome: Outcometric built a predictive ML model analyzing usage drops, support ticket tone, and billing history to flag at-risk accounts 60 days out.
The Challenge: Wasting ad spend on unqualified leads due to broken attribution between Google Ads and their archaic CRM.
The Outcome: We engineered a custom data pipeline connecting ad platforms directly to closed-won revenue, allowing them to instantly cut unprofitable campaigns.
Everything you need to know about working with us.
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