Case Study
Why a Mid-Market PE Firm Chose Crustdata Over ZoomInfo and Apollo for Portfolio-Wide GTM Data
Company
A Mid-Market Private Equity Firm
use case
Portfolio GTM Transformation
company overview
A mid-market private equity firm with 8 B2B portfolio companies spanning SaaS, professional services, and industrial technology. The firm's operating team manages GTM strategy and performance benchmarking across the portfolio.
scale
8 B2B portfolio companies
The firm's operating partner needed to grow revenue across 8 B2B portfolio companies without proportionally increasing sales headcount. Three problems stood in the way: inconsistent data quality that made cross-portfolio benchmarking impossible, out-of-date vendor data that degraded outreach effectiveness, and an outbound model that required more reps to generate more pipeline.
Each portfolio company had inherited a different data stack post-acquisition. One relied on ZoomInfo, another on Apollo, and a third ran outbound from manually researched spreadsheets.
Coverage, freshness, and data definitions varied across every company. The operating partner could not compare pipeline quality or conversion rates because the underlying prospect data came from different sources with different update cadences.
TAM sizing exercises produced incompatible results. When one portco estimated its addressable market using ZoomInfo's company database and another used Apollo's, the numbers reflected vendor coverage gaps as much as actual market differences.
Replicating a successful outbound playbook from one portco to the next was unreliable. A targeting strategy that worked with one vendor's filters and data coverage often broke when applied to a different vendor's dataset at another portco.
The legacy vendors that portfolio companies relied on refreshed their data in batch cycles, typically monthly or quarterly.
Reps across the portfolio regularly reached out to contacts who had changed roles or left their companies entirely. Bounce rates on email sequences were high, and connect rates on cold calls were low.
Company records lagged behind real market movements. Funding rounds, acquisitions, and leadership changes appeared in vendor databases weeks after they happened, well past the window when an outreach message referencing them would feel timely.
Sales managers had no way to distinguish between a targeting problem and a data freshness problem. When outbound campaigns underperformed, the default response was to increase volume rather than question whether the underlying records were up to date.
Without a way to prioritize which accounts and contacts deserved attention right now, every portco's outbound motion ran on volume.
Growing pipeline meant hiring more SDRs. The cost of each incremental pipeline dollar increased linearly with headcount, which worked against the PE firm's goal of improving operating margins across the portfolio.
Reps spent significant time on manual research to compensate for data gaps. Before reaching out, they checked company websites, social profiles, and news to verify that a prospect was still relevant. This research time cut directly into selling time.
The operating partner had no lever to pull besides headcount. Without signal-based outreach triggers, there was no mechanism to help existing reps focus on higher-probability opportunities.
The operating partner deployed Crustdata's APIs across all 8 portfolio companies, replacing the patchwork of legacy vendors and manual research.
Every portco now enriches company records through the Company Enrichment API, which returns 250+ live datapoints per company from 15+ sources. People records go through the People Enrichment API, returning 90+ datapoints per profile. The data definitions, coverage, and freshness are identical across the portfolio.
TAM sizing and pipeline benchmarking now use the same underlying dataset. The operating partner compares conversion rates, account coverage, and pipeline velocity across portcos knowing the data foundation is consistent.
When a successful outbound playbook emerges at one portco, the filters, targeting logic, and enrichment fields transfer directly to the next. The playbook is portable because the data layer is the same everywhere.
"For the first time, I can sit down with sales leaders from three different portcos and we're looking at the same data definitions, the same enrichment fields, the same filters. The conversation shifts from 'why are your numbers different' to 'why is your conversion rate higher.'" - Operating Partner
Portfolio sales teams replaced bulk purchased lists with self-service search through Crustdata's discovery APIs.
The Company Search API gives reps access to 95+ filters covering company size, geography, industry, funding stage, growth signals, and web presence. Reps build account lists that match their specific ICP instead of working through a vendor's pre-packaged segments.
The People Search API searches across 1B+ professional profiles with 60+ filters including title, seniority, function, skills, tenure, and verified business email. Reps find the right contacts at target accounts without toggling between multiple tools or resorting to manual profile research.
The time reps previously spent on manual list building and contact verification now goes directly into outreach and conversations. Each portco's sales team covers more accounts with the same headcount.
The Watcher API introduced signal-driven outreach across the portfolio, replacing the high-volume cold model.
Portfolio companies set up automated monitors for job changes, funding events, and hiring spikes at target accounts. When a tracked signal fires, the Watcher API pushes a webhook notification to the portco's CRM or engagement tool.
Reps now reach out when something relevant has just happened at the account rather than following an arbitrary cadence. A funding announcement, a new VP hire, or a rapid headcount increase gives reps a reason to open a conversation that feels timely.
The operating partner uses the same signal categories across portcos to benchmark which triggers drive the highest conversion rates. This creates a feedback loop where signal effectiveness at one portco informs outreach strategy at others.
Successful outbound motions at one portco now replicate to others within weeks, because the data infrastructure no longer requires separate tool evaluation and migration at each company.
Newly acquired companies ramp their outbound operations faster because the data infrastructure is ready to deploy from the start. The operating partner no longer evaluates each portco's existing data vendors before building a GTM plan.
The firm treats Crustdata as part of its standard post-acquisition GTM toolkit. Every new portfolio addition reaches full outbound capacity sooner, which shortens the gap between closing an acquisition and seeing revenue growth.
Existing sales teams across the portfolio cover more ground because they spend time on outreach instead of manual research and data verification. Revenue per rep increased as reps focused on signal-qualified opportunities rather than cold volume.
The shift from volume-based to signal-based outbound reduced the number of SDRs needed to maintain pipeline targets. For the PE firm, this translates directly to lower operating costs and improved margins at the portco level.
The operating partner can now grow portfolio revenue by improving rep productivity rather than approving new headcount requisitions. The cost of incremental pipeline no longer scales linearly with headcount.
Each portfolio company individually replaced its legacy data vendor subscription with Crustdata. The per-company cost decreased while data coverage, freshness, and signal depth increased.
Across 8 companies, the cumulative reduction in per-portco data spend represents a material improvement to the firm's portfolio-level operating costs.
Beyond direct subscription savings, the elimination of overlapping point solutions at each portco, where separate tools previously handled enrichment, list building, and intent signals, further reduces the total cost of the GTM data stack.