Part 1 The problemWhy teams need this
01 · THE PROBLEM
In home services, the first contractor to call back usually wins the job. This client had leads arriving from Meta, Google, their website, Angi and missed calls, landing in different places, with reps cherry-picking and good leads going cold. They didn't need more leads. They needed every lead answered, fast, by the right person.
Part 2 How it worksWhat it does, step by step
02 · WHAT IT DOES
Built for a US exteriors contractor drowning in leads from six places. Every enquiry lands in one door, gets de-duplicated, matched to the right contact, read by AI, scored A to D and routed to the right rep by region, skill and workload. The CRM gets the full picture and the customer gets a holding text, all before a human has picked up the phone.
03 · HOW IT RUNS
Step by step, as built.
One door for every source
Six lead sources post to a single webhook. Each is mapped to one lead shape, the phone number is normalised, and an idempotency key makes retries harmless.
One person, one record
The person is matched by phone and email before anything is created, then created or matched in GoHighLevel.
AI reads, rules decide
An LLM turns the free-text enquiry into structured fields. A transparent rubric scores it 0 to 100 and gives an A/B/C/D tier with a plain-English reason. If the AI fails, a keyword classifier takes over.
Route with live context
Routing checks service area, rep skills and each rep's current load. Emergencies skip the queue and go to the on-call rep; unclear leads go to a review queue.
Hand over in the CRM
GoHighLevel gets the enriched contact, the opportunity at the right stage, a routing note and, only for routed leads, the holding text.
04 · WHERE A PERSON STAYS IN
The machine drafts. A person decides.
Low-confidence, unclear and existing-customer leads go to a review queue for a person to decide. Spam and review-queue leads never get an automated text.
05 · TOOLS AND APPS
Built around the systems already in the process.
06 · WHEN SOMETHING BREAKS
Failure is designed in.
- 8nodes retry automatically when an external API fails.
- 1node has its own error branch, so a failure is routed and handled, not just logged.
- 4decision points (IF or Switch) check the data before it moves on.
Standard on every build
- Schema validation before downstream writes
- Retry and error routes for external API failures
- Duplicate-safe processing and idempotent updates
- Human approval where the action carries business risk
- Execution logging for support and audit review
Part 3 The impactWhat it's worth, and how we'd build yours
07 · PROJECTED IMPACT
What it should change in the business.
Projections for a typical deployment. The calculation below shows the math, and you can put in your own numbers.
08 · ROI CALCULATION
How it pays back in your business.
The starting numbers are a hypothetical deployment sized to the projections above. Change any of them to your own volumes and costs, and the math updates underneath.
- Full-time equivalent freed
- 0.7 people
- Gross value
- $48,960
- Running cost
- −$720
- Return per $1 of running cost
- $68
The math: 600 inbound leads × 12 min × 12 months × 85% ÷ 60 = 1,224 hours a year × $40/hour = $48,960. Net value = gross value − $720 running cost a year.
09 · HOW WE'D BUILD YOURS
How we'd build yours.
- Discover: map the current process, systems, volumes, owners and exceptions.
- Design: define the canonical data model, approvals, retries and system boundaries.
- Build: implement credentials, nodes, validation and observable error routes.
- Prove: run controlled data through success, duplicate and failure scenarios.
- Operate: publish runbooks, ownership and measurable service levels.
