Case study · 60-day engagement

From 5.4 jobs per truck per day to 8.2.

A Memphis junk removal company had three trucks running six days a week. The operating problem the owner was trying to solve was not lead generation. He had plenty of leads. The problem was that 30% of same-day requests fell through because the booking flow required a callback and most callers were already on the next ad before the office got back to them.

The challenge

"The leads come in. By the time I call back, half are gone."

Junk removal is a same-day decision category. A customer who searches "junk removal near me" at 9 AM expects to have someone at their house by 1 PM. The conversion window between the search and the irreversible decision to call a competitor is roughly 90 minutes for emergency same-day work, longer for scheduled work.

Audit findings:

  • "Request a quote" form took on average 3 hours to be returned by the office Most callers had booked with someone else by then.
  • Trucks were sometimes booked solid by noon and sometimes had open slots at 4 PM No system to throttle ads when the day was full and re-open when it was not.
  • Pricing was opaque Form asked for items and address but did not give a quote. Customers had no way to compare and most went with the first competitor that gave them a real number.
  • Average ticket was $189 Below regional benchmark because the office was always rushing through scheduling and not upselling junk-removal-plus-cleanout jobs.

The plan

Make booking instant. Make capacity dynamic.

Step 1: Instant pricing calculator (week 1)

Built a calculator that takes pickup zip code + a checklist of items (sofa, mattress, appliance, garage cleanout, full house) and produces an instant flat-rate price. About 73% of users book directly from the calculator without needing a callback.

Step 2: Live calendar with capacity (week 1-2)

Calendar widget shows real-time truck availability for the next 4 days, in 2-hour windows. As trucks fill up, the slots disappear. Customer picks a slot, enters address + phone, gets SMS confirmation within 60 seconds.

Step 3: Capacity-aware ad bidding (week 2)

Connected the booking system to Google Ads via API. When the day is 90% booked, ads auto-pause until 6 PM (when next-day capacity opens). Stops the wasted spend on calls we cannot fulfill, frees up budget for slower days.

Step 4: Cleanout upsell at booking (week 3)

During the booking flow, customers who select "appliance" or "furniture" see a "want us to clear out the rest while we are there?" toggle that adds $89-$249 per category. Attach rate is 38%, average ticket lifted from $189 to $248.

Step 5: SMS dispatch updates (week 4)

Before each pickup, customers get an SMS: "On the way · ETA 15 min · Truck 2 (driver: Marcus, 4.9 stars)." Rated 4.94 stars on follow-up. Cancellations dropped 42% because customers stopped feeling forgotten.

AI tools we used

The internal stack that did the heavy lifting.

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.

Tool 01Instant pricing calculator

Item-checklist + zip-based pricing engine that returns a flat rate in under 2 seconds. 73% of users book directly without a callback.

Tool 02Capacity-aware bid pausing

Auto-pauses Google Ads when the day is 90% full, resumes when next-day slots open. Stops wasting spend on calls you cannot fulfill.

Tool 03SMS dispatch tracker

Real-time arrival SMS for each pickup. Reduces customer cancellation by 42% on average.

The execution

Week-by-week timeline.

WeekWhat we shippedWhat moved
Week 1Instant pricing calculator + live calendar shippedFirst instant booking by day 4
Week 2Capacity-aware bidding deployedWasted spend on full days drops to zero
Week 3Cleanout upsell liveAverage ticket climbs from $189 to $221
Week 4SMS dispatch tracker activeCancellation rate down 42%
Week 6Mid-engagement performance reviewJobs/truck/day at 7.8 average
Week 8Final review, retainer continuesRun rate stable at 8.2 jobs/truck/day

The numbers

What changed in the data.

94%
Same-day fill rate
+52%
Jobs per truck per day
-42%
Cancellation rate

The lift in jobs per truck per day came from:

The owner stopped solving for "more leads" and started solving for "more booked jobs." Different metric, very different outcome. Same three trucks now move through their days completely differently.

I had been trying to solve the wrong problem. I thought I needed more calls. I actually needed fewer dropped calls. Once that clicked, the rest of the work happened in three weeks.

Owner·Junk removal company · Memphis, TN · 3 trucks

Keep reading

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