What results do AI consulting engagements actually produce?

Most AI consulting firms show you case studies with vague metrics — "improved efficiency," "enhanced customer experience," "streamlined operations." Those aren't results. Results have numbers, timeframes, and context. Here are the actual results from our Closer OS deployment, measured over 45 days of live operation in a portfolio brand running $94K/month in ad spend.

Revenue: $200,000 to $3,933,000. That's a 1,866% increase. The business didn't change its product, pricing, or ad strategy. The same team, selling the same offer, with AI sales infrastructure handling the workflow around them. The revenue came from three compounding improvements: more prospects showing up for calls, more calls converting to deals, and faster deal velocity from automated follow-up.

Customer acquisition cost: $11,765 to $1,217. A 90% reduction. Same ad spend, dramatically more conversions. When your show rate triples and your close rate jumps 33%, the cost per customer drops proportionally. The ad team didn't optimize a single campaign — the sales infrastructure made every lead more valuable.

ROAS: 2.1x to 23.4x. For every dollar spent on advertising, the business went from generating $2.10 in revenue to $23.40. This is the metric that matters most for paid acquisition businesses — it determines whether you can scale profitably. At 23.4x ROAS, every additional dollar in ad spend is highly profitable.

Show rate: 26.3% to 77.9%. Nearly 3 out of 4 booked calls were no-shows before deployment. After AI pre-call intelligence was live, nearly 4 out of 5 showed up. This single metric cascaded through every other number because more shows meant more at-bats, and more at-bats with better preparation meant more closes.

Close rate: 19.5% to 26.0%. A 33% improvement. This came from the live call assistance layer — real-time signal detection during calls gave closers contextual prompts for handling objections, identifying buying windows, and adjusting their approach based on the buyer type classification from pre-call intelligence.

Net profit: $3,420,000 in 45 days. After subtracting ad spend and operational costs, this was the bottom-line impact. The engagement cost was a fraction of this. Total deals closed: 138. Build timeline: 6 weeks. The system continues operating and generating results after the engagement ended.

These AI consulting results came from building production infrastructure, not running a pilot. The system was deployed into a live business with real revenue on the line. Every component was monitored, had fallbacks, and was documented for the team to operate independently. This is what AI consulting results look like when the consulting firm actually builds systems instead of delivering advice.