Buyout firms keep hitting the same RevOps problem after every acquisition: sales and marketing at the newly acquired company operate in silos, running unfocused campaigns with no shared data. A new ZoomInfo case study shows what closing that gap looks like in measurable time, not strategy decks.
What happened
Tide Rock Holdings, an unlevered buyout firm that acquires cash-flow-positive B2B companies, used ZoomInfo’s sales and marketing platforms to unify go-to-market operations at Interconnect Solutions Company (ISC), a maker of custom interconnect components for aerospace, medical, and industrial customers. Before the rollout, ISC’s sales and marketing teams worked from separate systems and ran what the case study calls “spray and pray” campaigns with no shared visibility into prospect engagement. Eric Shumway, SVP of Sales and Business Development at ISC, said the company is now “capturing high-quality leads in less than 48 hours from launching a campaign,” down from a process that previously took months.
Why it matters
The lesson generalizes well beyond one manufacturer. Newly acquired B2B companies routinely inherit disconnected sales and marketing stacks, and the fix ZoomInfo documents here, a single verified data layer both teams work from, is a RevOps decision as much as a tooling purchase. The 48-hour benchmark is a useful yardstick for whether a go-to-market unification project is actually working.
The original insight
What stands out is who is telling this story: a private equity operator, not a marketing department, citing lead-capture speed as evidence of value creation. That signals sales-and-marketing data alignment is becoming a standard item on the operating playbook buyout firms apply across acquired companies, because it is now fast enough to show results inside a single deal-hold cycle.
This follows a pattern already visible in how revenue intelligence platforms are proving ROI through partnerships rather than abstract data-coverage claims, and how sales intelligence vendors are increasingly measured on hard revenue outcomes instead of dataset size.
Source: ZoomInfo
