Case study · 45-day engagement
An Indianapolis carpet cleaning company had been losing the price war for two years. The local market was full of bait-and-switch operators advertising "whole house carpet cleaning $39" then upselling at the door. The owner refused to play that game, which meant his quote requests kept getting beaten on first call. He needed a way to win on value when the lead first hit his website, not after.
The challenge
The $39-whole-house ads work as bait. The actual cost when the customer pays the bill is usually $180 to $250 after upsells, but by then the customer is already at the house and the cleaning has started. Honest operators cannot match the headline. The owner had been told for two years that he needed to lower his prices or accept losing.
The audit showed something different:
The plan
Built a real pricing page. Three tiers (basic clean, deep clean, premium with stain protection) at fixed per-room rates. The page shows what is included at each tier, what is not included, and explicitly addresses the "$39 whole house" trap with a side-by-side comparison.
Owner had hundreds of customer-permission photos sitting in a phone gallery. We pulled 47 of the most dramatic before/afters into a scrollable gallery on the homepage. Each image has the actual ticket price visible. Visitors can scroll through and see exactly what their money buys.
Wrote a real "how we clean" page covering the equipment used, the chemistry of the process, the dry time, and the warranty. Most carpet cleaning websites have nothing like this. Took the owner about 90 minutes to walk through the actual process with us.
18 new ad headlines that lead with quality language: "Truck-mounted Steam Cleaning · 24-Hour Spot Warranty · 287 Five-Star Reviews." Quality score climbed from 5/10 to 9/10 because Google ranks ads partly on landing-page relevance and our pages now actually match the ad copy.
For visitors who left without requesting a quote, the Meta retargeting ad shows a "what \"$39 whole house\" actually costs" calculator. Click-through rate on the retargeting set is 4.8%, well above the 1.4% baseline.
AI tools we used
We do not pretend the work happens by hand. Three of our internal tools are the reason this engagement moved as fast as it did. Each of them replaces what used to be days of human time.
Auto-builds a scrollable gallery from customer photo permissions, with ticket prices and basic auto-cropping. Saves the owner about 8 hours of manual web design.
Side-by-side calculator showing real cost vs bait pricing. Drops bounce rate by about 30% on the pricing page.
Generates ad headline variants tuned for landing-page relevance, runs A/B tests automatically, retires losers. Lifted quality score from 5/10 to 9/10 in 21 days.
The execution
| Week | What we shipped | What moved |
|---|---|---|
| Week 1 | Pricing transparency page + before/after gallery shipped | Quote request rate doubles by day 9 |
| Week 2 | Methodology page + 18 new ad headline variants live | Quality score climbs 5 to 8 |
| Week 3 | Retargeting bait-callout campaign active | Retargeting CTR 4.8%, qualified visits up |
| Week 4 | Quote-form simplification: 5 fields → 3 fields | Form completion rate +52% |
| Week 5 | Mid-engagement review with owner | Average ticket climbing from $189 to $278 |
| Week 6 | Quality score tuning, final ad copy lock-in | Average ticket settles at $312 |
The numbers
The lift in average ticket came from:
The owner stopped trying to compete on price and started competing on visible value. The bait operators in his market still exist. They just no longer steal his customers at the moment of decision.
Two agencies told me to drop my price. One told me to add a $19 special. I knew that was the wrong direction. Mark looked at my reviews and told me my problem was that I was hiding what made me different. That was the whole answer.
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