How Conviva Is Turning Sales Calls Into Search-Optimized Content

Conviva is the digital intelligence platform that analyzes user behavioral patterns and agent conversations to continuously make your AI agent smarter.

Their marketing team is now one of the first to build with AirOps Quill: connecting the dots between what prospects are actually asking on sales calls and the content the field team needs to answer those questions at scale.

For a company sitting on thousands of hours of conversation data, the opportunity isn't just content production. It's turning real buyer signals into a repeatable content engine that drives growth in both traditional and AI search. These are early days, and Ari is building the system from the ground up.

The signal was in the sales calls all along

Every sales call contains buyer intent: the objections, the questions, the topics prospects care about most. For most marketing teams, that signal stays locked in call recordings or scattered across notes. Turning it into content meant listening to calls, pulling out themes manually, cross-referencing search data, and then briefing writers.

"Quill solves for complexity," said Ari Moskowitz, Content Marketing Director at Conviva. "I don't get lost in prompts and steps. Once I decide on what I want to build, a Playbook shows each step clearly no matter how sophisticated or specific. I can iterate without getting bogged down in processes."

Before Quill, Ari was stitching together Grids, Slack threads, and Claude MCP connections to do pieces of this work. It worked, but the process was manual and fragmented.

A Playbook that mines Gong transcripts and produces sales-ready content

Ari built a Playbook that pulls entire transcripts from Gong, mines them for objections and questions that match high-value search terms, and produces blog posts and ebooks that sales can use directly with prospects before and after calls.

Quill runs the mining and drafting autonomously, but checks in with Ari before content ships: surfacing the draft, the source transcripts, and the search terms it mapped to, so the team stays in control of what goes out.

The content isn't generic thought leadership. It's built from real conversations with real buyers, mapped to the search terms those buyers are using. The result: content that serves both organic visibility and direct sales enablement in the same motion.

"Before Quill, we created Grids using the MCP connection on Claude," Ari said. "Now, we build Playbooks and adapt on the fly."

The program is just launching, so results are ahead of it. But the shift in how Ari spends time is already clear.

From manual assembly to quality control and ideas

The Playbook automates the work Ari was previously doing by hand across multiple tools and threads. That freed up something more valuable than hours.

"Playbooks automate the work I'm currently doing manually across Grids and Slack threads," Ari said. "I now focus on quality control and iteration. And thinking of my next big idea."

That's the pattern across Quill's early builders: Quill becomes a core part of how the team operates, handling execution and connecting activity to the growth metrics that matter, while the human drives strategy and the quality bar.

For a content marketing director at a company with Conviva's scale of conversation data, the pipeline of ideas is the asset. Quill is what makes it possible to act on them.

Ready for an AI agent that actually moves your metrics? Meet Quill.