Ten modeled builds, with every assumption exposed.
These are illustrative implementation playbooks—not client case studies or testimonials. Each one starts with declared assumptions and shows the architecture, controls, and measurement method a real engagement would require.
- Home Services
- Roofing
- Med Spas
- Dental
- Mortgage
- Law Firms
- Fitness
- Auto Services
- Solar
- Agencies
Illustrative: 2.4x storm capacitySurviving a 400-lead storm week without hiringHail season used to break their intake completely. We built triage that sorts by claim stage and books inspections against crew territory.
Illustrative: 3.1x rebooking rateAn AI agent that books consultations at 11pmA third of their enquiries arrived after closing and sat until morning. Now they get answered, qualified and booked before anyone opens the clinic.
Illustrative: 31% fewer no-showsRefilling the chair that just cancelledA no-show rate everyone had accepted as normal turned out to be an untuned reminder sequence and an unused waitlist.
Illustrative: $610k recoveredEleven thousand dead records, worth $610kA back-book nobody had touched in four years, segmented on original rate and loan age, then mobilised in a single weekend.
Illustrative: 0 records lostFourteen years of Keap history, migrated without downtimeBoth systems ran in parallel for three weeks. The cutover happened on a Tuesday morning and nobody in the firm noticed.
Illustrative: 24% lower churnCatching cancellations six weeks before they happenAttendance data already showed who was leaving. Nobody was reading it. We turned the drop-off signal into a coach conversation.
Illustrative: 3.4x work recoveredThree years of declined work, finally called backEvery recommendation a customer had ever turned down, sitting in the shop system. We sequenced follow-up to the actual safety interval.
Illustrative: 2.9x referral rateTurning a five-week permit silence into referralsHomeowners went dark between contract and install and stopped referring. Milestone updates fixed a problem nobody had named.
Illustrative: $41k MRR in 9 monthsA white-label launch that survived its first yearThey had switched SaaS Mode on twice and abandoned it twice. The third attempt started with a margin model instead of a price.How to use a modeled implementation playbook
A model is useful only when its assumptions are visible and replaced with real baseline data before decisions are made.
- Replace every input.Lead volume, response time, conversion, cost, staffing, and compliance conditions must come from the business being modeled.
- Define the attribution method.Use a baseline or holdout where practical, record concurrent changes, and do not assign every movement to automation.
- Validate before scaling.Pilot on a bounded cohort, monitor guardrails and exceptions, then publish only verified outcomes with client consent.
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