Events and Webinars

You've heard about Meta Conversions API. Maybe you've even set it up. But here's what a low match rate is actually costing you: Meta can't find more of your best customers, your campaigns optimize on incomplete data, and your ad budget works harder than it needs to for weaker results. The fix usually isn't just the connection. It's knowing which events to send when and which data to attach. In this live session, Meta walks through why strong signals change campaign outcomes. Then Jared from Matix Flows gets into the strategy: which events to send, when in the funnel, and how to structure them for the best results via Zapier.

Sales, Marketing, and Customer Success each carry a different version of the customer.

Sales hears one version in calls. Marketing sees another in campaign performance. Customer Success learns what happens after the deal closes. Those signals live in different tools, decay at different speeds, and rarely make it back into the persona deck everyone is supposed to use.

AI should make your marketing better. Without shared context, it becomes a slop hose.

Your team can produce more content, campaigns, outbound, and enablement than ever. But when the context beneath that work is stale or fragmented, AI produces generic output faster.

Zapier's marketing team is building a different model by building five buyer personas from account patterns and de-identified sales calls (Databricks and Gong), then put them to work pressure-testing copy, campaigns, and outreach before it ships. These aren't imaginary AI characters or static profiles with a chatbot attached. They're evidence-backed representations shaped by sales conversations, campaign performance, customer behavior, and what the team learns next.

Join Lindsay Rothlisberger, Joe Stych, and Ryan Anderson for a candid look at how Zapier built these personas, keeps them current, and puts them to work across GTM.

This session is for senior Marketing, RevOps, Sales Ops, and GTM Innovation leaders who want AI grounded in a shared, current understanding of the customer.

Save your seat. Recording shared with registrants.

A rubric can define AI fluency. It cannot make employees fluent.

Publishing an AI fluency framework is progress because it creates expectations and a shared language. But then employees return to tools, outdated training, crowded priorities, and managers who are wondering what “good” looks like.

The framework may be right. The employee experience around it is incomplete.

Zapier took a different path. Broad AI adoption came before the first formal rubric. The company then used the rubric to give shared language to behavior employees had already started practicing—and connected that language to hiring, onboarding, performance standards, Golden Paths, peer learning, and manager expectations.

Join Colin Monaghan, Zapier's Director of Learning & Development, and Ryan Anderson for an open-playbook look at how Zapier made AI fluency part of the job. They'll share what worked, what didn’t, what the organization had to provide before raising the bar, and how Zapier looks for changed work instead of tool usage alone.

This session is for AI transformation, Talent, People, Learning and Development, HR Operations, and IT leaders responsible for turning company-wide AI expectations into daily behavior.

Save your seat. Recording shared with registrants.