JayOh gave PE-backed Vault Verify a working RevOps function instead of a new full-time hire: shared definitions, a marketing–sales SLA, an intake process, Salesforce training and automated data cleaning. Lead processing got 30% faster, Lead-to-MQL conversion improved 45% and data errors dropped 90%.
Vault Verify needed RevOps outcomes (clean handoffs, trustworthy data, a team that could use Salesforce) without adding a full-time head. The issues were the ones most PE-backed teams inherit.
Marketing and sales used terms differently, so stage definitions and reports didn’t line up.
There was no agreed marketing–sales SLA defining when a lead transfers, what information moves with it and how it’s recorded.
Issues, tasks and projects needing RevOps support had no intake process, so they were slow to resolve.
Data uploads, cleaning and deduplication were manual, and the team needed structured Salesforce training.
7 workstreams, in the order they matter. Each one closes a specific gap from the problem list above.
StackOne reference for consistent terminology across marketing, sales and leadership.
A documented SLA and a Marketing → Sales process flowchart that set exactly how and when leads move.
Common objectives and KPIs so every team worked toward company goals, not just their own.
A single way for stakeholders to submit issues, tasks and projects needing RevOps support.
Recurring training that raised Salesforce proficiency and day-to-day productivity.
Insycle implemented to automate data cleaning, upload hygiene and deduplication.
Defined when and how a lead transfers, what information goes with it and how the handoff is recorded in Salesforce.
JayOh operated as the company’s RevOps function. It ran as an embedded engagement rather than a fixed-length project, so there’s no single end date to quote.
Definitions Dictionary, shared KPIs and the marketing–sales process flowchart.
Marketing ↔ Sales SLA, lead-handoff rules and the RevOps intake process go live.
Insycle automates data cleaning, uploads and deduplication.
Recurring Salesforce end-user training locks in adoption.
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 |
|---|---|---|---|
| Lead processing time | No SLA | 30% faster | Lead acquisition to qualification |
| Lead → MQL conversion | Unstructured handoff | +45% | From SLA-based handoff protocols |
| Sales cycle efficiency | — | +25% | From the Marketing → Sales process flowchart |
| RevOps issue resolution speed | No intake process | +50% | From the new intake process |
| Data errors | Manual cleaning | −90% | Insycle-automated cleaning and dedupe |
| Dedicated RevOps FTE added | Planned | 0 | Need for a dedicated hire negated |
The operator lessons we’d apply to any team facing the same problem.
A Definitions Dictionary sounds small. It is what made the SLA, the KPIs and the reports agree with each other.
Defining exactly how leads hand off drove a 45% Lead-to-MQL improvement without changing lead volume.
An intake process made RevOps support 50% faster because work stopped arriving through hallway requests.
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.
