The Outbuzz AI Example
Real funnel, real numbers: measured end to end at one of the agencies this system was built for, from first LinkedIn touch to signed contract.
No ICP, so I built one from the client's own wins
There was no predefined targeting, no messaging playbook, no list to start from. Instead of guessing, I looked at the client's historical wins: every strong project was connected to conferences. That became the buying signal, not a demographic assumption.
Every channel pointed at the same storefront.
This wasn't a generic outbound campaign. Paid, organic, community, and 1:1 outreach all funneled attention into one thing: an AI storefront that turns a prospect's own website into a personalized OOH plan in 60 seconds.
AI personalized the offer, not just the message
The interesting part wasn't using AI to write messages. It was using AI to turn company research into a tangible, company-specific OOH campaign concept, in clearly separated stages.
Four touches, timed around the event
Every message was built around event timing, not a generic pitch. The LinkedIn message's job was to create enough curiosity to open the proposal, not to explain OOH.
What I'd take to the next campaign
The ICP came from the client's own data, not from a "who buys OOH" assumption. Strong outbound starts with finding the observable signal that tells you why this account might care now.
The 27% positive reply rate came from prospects receiving something specific and useful, their own campaign concept, not a generic "let's explore OOH" message. The proposal was the conversion mechanism.
Running paid, organic, community, and outbound simultaneously meant prospects often encountered the brand from multiple angles before a cold LinkedIn message arrived: warming the cold.
The same message, sent to the same person, three months before or after the conference would have performed far worse. The event created urgency the pitch didn't have to manufacture.