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Handshake: The Pitch Deck That Told Kerry Haring Everything Wrong With B2B Messaging

Kerry Haring had spent nearly 15 years in HR tech when she joined Handshake in summer 2024. She knew the buyer. She knew the space. She assumed the messaging would need refinement, not surgery.

Then she pulled up the pitch deck.

It opened with what Handshake does. Who they are. What the product is. Slide after slide building the case for Handshake before the buyer’s world had appeared anywhere on screen. Kerry had seen this before, but seeing it laid out in front of her clarified the actual problem.

“Most of the people on the other side of that call don’t care 100%,” she said. “They just want to know, what pain are you going to solve for me and why should I go after your solution versus somebody else’s?”

The pitch deck wasn’t broken. It was answering the wrong question first.

The Assumption Buried Inside Most B2B Messaging

In a recent episode of Unicorn Marketers, Kerry walked through how she rebuilt Handshake’s B2B messaging from scratch — and what she found when she stopped assuming she already knew the buyer.

The failure mode looks like this: teams build a product, then reverse-engineer the pain it must be solving. The buyer reads the resulting messaging and feels nothing, because nobody has proven they understand what the buyer is actually dealing with.

“A lot of the times people make assumptions about pain,” Kerry said, “so they’ll say or there’ll be internal, I think triggers that will get into customers pain. So like we built this solution so people must want it type situation versus really taking time to understand what are those drivers and what makes people make a decision.”

Her first move was not a messaging workshop. It was discovery. She spent time with the account team, listened to sales calls, and reviewed closed won and loss reasons.

One insight changed the entire frame. Internship programs — which most companies treat as summer staffing logistics — function as primary long-term leadership pipelines in certain industries. The companies Handshake sells to weren’t filling temporary roles. They were sourcing future leaders. Once Kerry understood that, the messaging problem became clear: Handshake had been talking to a strategic decision like it was an operational one.

The Sequenced Validation Loop

With a clearer picture of the buyer, Kerry built a validation process to check messaging before it shipped. She runs it in a specific order, and the sequence matters.

Sales and GTM teams go first. They talk to hundreds of buyers regularly and carry an instinctive read on what lands. Bringing them in early also generates field ownership. “If they’re brought in, they feel heard they’re going to use it more, most likely,” Kerry said. Field adoption of messaging is a distribution problem, and involvement is the mechanism for solving it — not training decks sent after the fact.

From there: A/B software testing, live Gong call review, website testing. Each layer adds signal. Skipping straight to formal testing without the sales gut-check loses the fastest read and the buy-in that comes with it.

When AI Language Backfires on Conversion

The most counterintuitive decision Kerry made was driven directly by data.

In B2B tech, AI has become the default headline claim. Kerry tested whether that assumption held with Handshake’s actual buyer. It didn’t.

“A lot of them are scared of AI,” she said. “They don’t know how to use it, when to use it. They’re worried about, you know, legality and safety and all those things.”

The HR persona Handshake sells into isn’t operating in the same AI-forward context as the teams building the messaging. For that buyer, “AI-powered” doesn’t signal sophistication — it signals risk. Kerry ran explicit message testing on AI-forward language and found it created friction at the top of the funnel. She removed direct AI claims from top-of-funnel messaging based on test results.

Building a Source of Truth That Gets Used

Consistent messaging across a large organization degrades fast. Marketing, sales, exec comms, and demand gen all touch the messaging. Without a single resource people actually use, even the best work erodes.

Kerry’s solution was an internal AI chatbot named Barb. The distinction in how Barb was trained is what makes her useful. Most teams load internal AI tools with documentation. Kerry trained Barb on three things: core messaging docs, feedback she has given other PMMs, and actual copy the team has written alongside how it was applied in context.

“She’s also trained on the feedback that I’ve given, you know, other product marketers, the copy that we’ve written for different areas and like how we applied it,” Kerry said.

That third layer is what separates a tool that produces generic output from one that produces on-brand decisions. Every person in Handshake’s marketing organization uses Barb daily. One resource to update. One place where the messaging lives.

The Discipline Behind Narrative Strategy

Kerry structures all of Handshake’s content, executive posts, events, and paid activity around five market narratives she wants to land this year — each built around something the market needs to understand differently about the early talent space.

The discipline she applies to updating those narratives is deliberate. Web copy can and should be tested continuously. Strategic narratives require stability to be measurable. “The more you change them, I think the less you’ll understand which message actually landed,” she said.

The principle: match your update frequency to the surface and the story you’re trying to land. Treating all messaging as equally testable means you’ll never know what actually moved perception.