JayOh helped Ramp hire its RevOps team and stand up a modern GTM data stack: Snowflake, dbt and Hightouch feeding enriched data into Salesforce, HubSpot and Outreach. The automated BDR and personalization engine built on top drove 25% of all new-business pipeline while cutting data platform costs 20%.
Ramp was growing faster than its revenue operations. The team needed RevOps leadership, and the data that reps and leadership acted on had to be consistent, fast and pushed into the tools sellers actually use.
Biz Ops, leadership, sales and marketing needed someone to own revenue systems and processes as GTM headcount scaled.
The previous data warehouse struggled with concurrency, causing deadlocks and performance bottlenecks.
Data from Salesforce, HubSpot, Zendesk and Outreach was transformed ad hoc, so the same metric could disagree across reports.
Without enriched, scored data in the CRM and sequencer, sellers spent time on research and data entry instead of selling.
6 workstreams, in the order they matter. Each one closes a specific gap from the problem list above.
StackWorked with Biz Ops, leadership, sales and marketing to define roles, wrote the job descriptions and ran sourcing, interviews and evaluation. Placed a senior RevOps leader plus two supporting hires.
Replaced the bottlenecked warehouse with Snowflake for near-unlimited concurrency, automated scaling and lower maintenance overhead.
Standardized transformations across Salesforce, HubSpot, Zendesk and Outreach data so core metrics were consistent everywhere.
Synced enriched, scored data back into Salesforce, HubSpot and Outreach so reps and marketers acted on the same insight.
Enriched prospect data flowing into the CRM, automated multi-channel sequences, and signal-triggered follow-ups so nothing slipped.
Custom audiences synced to ad platforms, CRM enrichment and automated workflows delivering tailored outreach across marketing and sales.
The work ran in the four phases below. A start-to-finish duration wasn’t recorded in the case study, so we don’t quote one.
Roles scoped with leadership; senior RevOps leader and two supporting hires placed.
Snowflake warehouse and dbt models standardize metrics across source systems.
Hightouch reverse ETL pushes enriched data into Salesforce, HubSpot and Outreach; BDR motion automated.
Personalization engine and synced audiences drive new-business pipeline as GTM headcount grows.
Every figure below comes from JayOh’s documented case study for this engagement. Where the starting value wasn’t recorded as a number, the “Before” column describes the starting state instead.
| Metric | Before | After | How it was measured |
|---|---|---|---|
| Share of new-business pipeline | No automated engine | 25% | From the automated BDR + personalization engine |
| Data platform cost | Baseline | −20% | Budget freed for growth initiatives |
| Data transformation speed | Ad hoc transforms | +33% | Faster insight for sales and leadership |
| Company growth supported | — | 200%+ | With a foundation for 10X GTM employee expansion |
| RevOps team placed | No dedicated leader | 1 senior leader + 2 hires | Strategic leadership plus execution |
The operator lessons we’d apply to any team facing the same problem.
Placing a senior RevOps leader early meant the stack had an owner who kept scaling it after the build.
dbt models ended the ad hoc transformations that made the same metric disagree between Salesforce, HubSpot and Outreach.
Reverse ETL into the CRM and sequencer is what turned a warehouse into 25% of new-business pipeline.
Five signs we saw at this client before the work started. Tick the ones that are true for you; the more you tick, the closer your fix looks like this system.
Rule of thumb: 1–2 signs is a contained fix, 3 is this pattern, 4–5 means the system needs rebuilding rather than patching.
Tick the statements that are true for your team.
Bring your current setup to a 30-minute call. We’ll tell you which parts of this case apply, what we’d build first and what it would take.
We engineer growth systems. JayOh builds the RevOps architecture, GTM execution and data infrastructure that turn messy revenue operations into predictable pipeline for B2B SaaS and PE-backed teams.
