Client work · Career coaching · January–February 2026
A coaching business had an AI chatbot and a new service to test. I built the paid acquisition campaign around it, then used booking results to look beyond the cost of getting someone into a conversation.
Delivered through a partnership with an advanced chatbot technology company. The end client is unnamed.
The business question
The company wanted to supply leads to graduates of its coaching certification program. It needed an initial read on whether paid conversations could lead to booked discovery calls before committing to a larger budget.
The client had already built the AI chatbot. It could ask about a prospect’s needs, qualify their interest and direct suitable prospects to book through Calendly.
The missing piece was an acquisition campaign that put that experience in front of the right people.
My role covered campaign strategy, audience selection, creative testing and performance analysis. I connected advertising decisions to the booking outcome instead of judging the campaign on conversation volume alone.
This case study covers that paid acquisition work, not ownership of the underlying chatbot.
The acquisition path
Meta ads
Creative introduces the coaching conversation and invites a response.
Messenger + client chatbot
The existing chatbot asks questions and routes people according to their interest.
Calendly
A discovery-call booking gives the campaign a downstream outcome to measure.
What the test revealed
The initial audience generated 62 conversations without a recorded booking. After the February 4 audience update, the report recorded five bookings from 152 conversations, even though each conversation cost slightly more.
Before the audience update
From 62 conversations
After the audience update
From 152 conversations
A low cost per conversation wasn’t enough. The useful question was whether those conversations led to the next business step.
Source: campaign performance report covering January 26–February 25, 2026. The audience update was February 4; the report records the campaign as paused February 10. These are small before-and-after samples, not a controlled test of audience targeting alone.
The work behind the test
I designed a Meta Messenger campaign that opened a conversation with the client’s bot. The acquisition path connected the ad, qualification experience and booking step.
I tested creative approaches and adjusted audiences, budgets and campaign structure. The audience update became an important point of comparison because booking behavior changed while click costs stayed similar.
I used AI to help synthesize advertising data and support the review process. I made the decisions about which audiences and creative to change, and checked the downstream results.
I also built an automated monitor to flag changes in AI disclosure requirements for review. That gave the team a recurring way to identify potential updates to its conversational flows.
Pilot results
The pilot recorded 214 conversations and five bookings on $396.70 in reported campaign spend. It established an initial booking cost and a basis for further testing.
After the audience update, reported spend per booking was $58.83, based on $294.17 and five bookings. The conversation-to-booking rate for that period was 3.3%.
Bookings are not attended calls or paying coaching clients. Those later outcomes are not established by this report, and five bookings are not enough to claim repeatable performance at scale.
Where this work helps
I help connect campaign reporting to what happens next, then use that evidence to guide the creative, audience and website work.
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