Selling into higher education means selling to a campus, not a single decision-maker. Enrollment, advancement, athletics, alumni engagement, IT, and student success leaders can all shape a deal, but most B2B databases don’t reflect how those buying committees actually work.

Gravyty, an AI-powered engagement and fundraising platform for higher education, needed a better way to identify the right stakeholders, understand institutional priorities, and turn that context into pipeline.

Amanda Laffan, ABM Manager at Gravyty, was brought on to build the company’s account-based marketing motion from the ground up, including account scoring, expansion campaigns, competitive displacement, buying committee mapping, and sales alignment. The strategy was clear. The data was the blocker.

The challenge: higher-ed data Gravyty couldn’t trust

After several company mergers, Gravyty had a large database, but not an accurate one. Its lead generation platform underperformed in higher education, and Gravyty’s own AEs, many with years of higher-ed sales experience, confirmed the gaps.

Amanda tested alternatives. One major provider’s contact lists failed manual LinkedIn validation. In some cases, Gravyty’s existing CRM data was more accurate. AI enrichment through ChatGPT guessed at email addresses, creating bounces and data-quality issues in HubSpot. The team even resorted to manually searching campus directories.

“Every hour AEs spend hunting for contacts is an hour they’re not spending generating pipeline,” Amanda said.

From RFP intelligence to account intelligence

Gravyty was already using Starbridge for RFP intelligence when their CSM mentioned it could also support account enrichment and contact discovery. Amanda was skeptical after months of vendors overpromising, so she compared Starbridge contacts side by side against the tools Gravyty was already using.

The difference was clear.

In an expansion campaign targeting new departments within existing higher-ed customers, Starbridge increased buying committee coverage from an average of 10 contacts per institution to more than 23. It also revealed that nearly 40% of target accounts had no relevant contacts in the departments Gravyty wanted to reach.

Starbridge filled those gaps, turning previously unworkable accounts into viable targets.

“Starbridge didn’t just give us more contacts,” Amanda said. “It helped us identify the right people, understand the buying committee, and execute a campaign that would have been difficult to run using our existing data alone.”

From persona-based targeting to signal-based outreach

The bigger shift came from buying signals.

Many higher-ed board, trustee, cabinet, and committee meetings are public, and those conversations often reveal exactly which challenges institutions are trying to solve. Starbridge surfaces those signals so Gravyty can build outreach around real institutional priorities instead of relying only on job titles, personas, or org-chart assumptions.

Gravyty now uses Starbridge to surface insights around specific institutional challenges, giving BDRs context before every conversation. As one Gravyty BDR put it: “When I get a prospect on the phone, I actually know what I’m talking about.”

The results: 20% more demos booked

With Starbridge, Gravyty saw a 20% increase in demos booked compared to traditional outreach methods.

The impact went beyond better contact data. Starbridge helped Gravyty move from asking, “Who should we contact?” to “Why would this institution care right now?”

“The biggest impact wasn’t that Starbridge gave us more contacts,” Amanda said. “It gave us more context, and context is what turned outreach into conversations and conversations into meetings.”

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