Mark Deacon's Marketing Hub: AI Revenue Engine

Canibuild's sales team used to record personalised prospect videos by hand. Each one took 15 to 20 minutes, so reps did them in bursts, when they had spare time. Mark Deacon replaced that routine with a system that scripts, produces and tracks the videos, and he opens his screen to show every step.

Mark is Chief AI Officer at Canibuild. He has spent his career leading sales, marketing and customer success teams, and he does not write code. He built the Marketing Hub, an internal platform where Canibuild's teams serve themselves instead of queuing for engineering.

The outreach video tool is the centrepiece. A rep enters a prospect's website, or imports a list from a CSV or a HubSpot segment. The system scrapes the site, writes a script and produces a video of about a minute. It opens on the prospect's own website, then moves into the Canibuild product and ends on a call to action. Each video features an AI avatar of the account's real rep, with a HeyGen face and an ElevenLabs voice. Mark said reps supplied short recordings to set these up, and a personalised landing page goes out with the video.

Mark was direct about the results. By his account, conversion is roughly on par with videos reps record themselves. The gain is volume: a handful a month before, and potentially a thousand now, at about $4 a video. Video watches trigger Slack alerts and HubSpot tasks; demo bookings create deals, so reps do not need to live in the Marketing Hub.

The build-versus-buy split is useful. Mark said Canibuild's tools split roughly 50/50. It buys anything customer-facing that needs near-perfect uptime, such as its 11x AI SDR. It builds internal tools where a day of downtime is an inconvenience, not a crisis.

He also showed an early version of a newsletter builder. It reads the engineering team's Jira roadmap and industry news, scores what matters for a chosen segment, and publishes through HubSpot. Mark noted that it still needs a person to pick articles and images. Automatic segment-by-segment sending is the next step.

The second half widens out. Every Canibuild tool starts as a flow tested in the terminal, then gets an interface so the team can run it without waiting on Mark. Staff build dashboards and apps in VS Code using shared skills. Those skills apply templates, scan for leaked API keys, push to a central GitHub and register each tool on a master dashboard, so nothing disappears when its builder leaves. Mark described his role as enablement. He wants the people with