Client case studies The work leaves a record.

Client case studies with real results, each one opening a whole system up. Each one is drawn twice: the business as we found it, then the system as built. Every number shows where it came from.

Open the records

Client records: 7Measured
Case studies: 6In depth
Working models: 2Modeled

A drafting table with a sheet of vellum over a floor plan, a red pencil and a blue pencil beside it.

Record 02 · Dental practiceDay 30

Before: 31%After: 47%

Inquiry-to-booking rate

Verified result

Record 05 · Restoration and remediationDay 30

Before: 45 minutesAfter: Under 8 minutes

Call-to-estimator notification time

Verified resultRead record 05

How to read a record

The line beside each label tells you what kind of evidence you are looking at. Red marks a business as we found it. Blue marks the system as built.

Verified result

A real client's before-and-after result.

Client words

A real review, linked to where we found it.

Implementation record

A real deployment, described in plain terms: what we installed and how it changed the work.

Operating model

Something you can inspect yourself: a live demo, a diagnostic, a published method.

Modeled scenario

A calculation from stated assumptions.

Seven client records, measured before and after.

Seven real client results below, each checked against the client's own records before we published a number. Every case below happened to a real client. Names and locations stay private. The metric, the baseline, the result and the window stay public.

Verified result

Record: 05
Business: Restoration and remediation
Window: Day 30

Before: 45 minutesAfter: Under 8 minutes

Call-to-estimator notification time

Emergency calls outside business hours were routed through a slow third-party answering service, letting competitors win urgent work.

How it was measured: Timestamped emergency intake and estimator-notification records compared across the stated installation window.

Illustrative industry photograph for a restoration and remediation business. Not the client.

Measured at a real client

As found

Third-party answering service averaged 45 minutes before estimator notification
Emergency callers frequently hired a competitor before the callback

Installed

AI emergency intake with urgency classification
Direct dispatch SMS to on-call estimator within minutes
Pre-qualified job details sent before arrival

HVAC emergency service

After-hours HVAC demand was hitting voicemail, hangups were high, and competitors offering 24-hour response were taking the work.Before: 38 Google reviewsAfter: 61 Google reviewsGoogle review count, optimization window

Verified result

Confidential North American service business

As found

14 to 18 missed calls per week, mostly after 5 PM and on weekends
Calls after hours went to voicemail with roughly 70% hangup rate
No missed-call text-back or after-hours booking flow

Installed

AI voice agent live within 48 hours
Missed-call text-back
After-hours booking flow
Seasonal past-client reactivation campaign

Documented outcomes

Estimated valueDay 30: 11 of 15 weekly after-hours calls captured with estimated month-1 recovery of $8,960
MeasuredOptimization window: Google reviews grew from 38 to 61Google Business Profile review-count observation before and after the installed review workflow.

Dental practice

New-patient inquiries were getting missed during busy hours, the patient database was dormant, and review growth had stalled.Before: 31%After: 47%Inquiry-to-booking rate, day 30

Verified result

Confidential North American service business

As found

Average of 9 missed calls per week during lunch hours and after 5 PM
1,400-patient database with no reactivation since original EMR setup
Google review count stagnant for 8 months

Installed

AI receptionist for new-patient intake and after-hours booking
Two-segment database reactivation
Post-appointment automated review requests

Documented outcomes

MeasuredDay 30: Inquiry-to-booking rate improved from 31% to 47%Documented inquiry and booking records compared across the stated installation window.
MeasuredOptimization window: Google reviews grew from 31 to 58Google Business Profile review-count observation before and after the installed review workflow.

Personal injury law

After-hours claimant inquiries were going to voicemail, with no real tracking or qualification before those leads contacted another firm.Before: HoursAfter: Under 4 minutesContact-to-attorney acknowledgment time, day 60

Verified result

Confidential North American service business

As found

Estimated 7 to 12 after-hours calls per week going unanswered
Generic voicemail with no callback tracking
No visibility into callers who attempted contact but never left messages

Installed

AI after-hours intake
Qualification script collecting accident type, urgency, and contact details
Warm SMS notification with pre-qualified intake summary to the on-call attorney

Documented outcomes

Estimated valueDay 30: 9 after-hours inquiries captured, representing roughly $27,700 in potential case pipeline at current economics
MeasuredDay 60: Contact-to-attorney acknowledgment reduced from hours to under 4 minutesTimestamped intake and attorney-acknowledgment records compared across the stated installation window.

Aesthetics and med spa

Promotional demand outpaced manual intake capacity, missed calls were not followed up, and a valuable past-client list was unused.Before: Near-zeroAfter: 58%After-hours caller booking rate, day 30

Verified result

Confidential North American service business

As found

11 to 13 missed calls weekly with no follow-up
Promotion-driven spikes the team could not absorb manually
Database of 650 past clients with no reactivation activity

Installed

AI receptionist with calendar-integrated booking
Missed-call text-back inside 60 seconds
Database reactivation campaign
Post-service automated review requests

Documented outcomes

MeasuredDay 30: After-hours caller booking rate moved from near-zero to 58%Documented after-hours call and booking records compared across the stated installation window.
MeasuredOptimization window: Google reviews grew from 42 to 89Google Business Profile review-count observation before and after the installed review workflow.

Restoration and remediation

Emergency calls outside business hours were routed through a slow third-party answering service, letting competitors win urgent work.Before: 45 minutesAfter: Under 8 minutesCall-to-estimator notification time, day 30

Verified result

Confidential North American service business

As found

Third-party answering service averaged 45 minutes before estimator notification
Emergency callers frequently hired a competitor before the callback

Installed

AI emergency intake with urgency classification
Direct dispatch SMS to on-call estimator within minutes
Pre-qualified job details sent before arrival

Documented outcomes

MeasuredDay 30: Call-to-estimator notification dropped from 45 minutes to under 8 minutesTimestamped emergency intake and estimator-notification records compared across the stated installation window.

Residential plumbing

After-hours demand depended on the owner’s personal phone, causing missed emergencies, decision fatigue, and a weak review-growth system.Before: 22 Google reviewsAfter: 51 Google reviewsGoogle review count, optimization window

Verified result

Confidential North American service business

As found

10 to 14 missed calls per week, mostly evenings and weekends
Emergency calls had the highest job value and lowest callback rate
Owner handled after-hours calls on a personal cell phone

Installed

AI voice agent for after-hours and overflow calls
Urgency triage by call type
Missed-call text-back with booking form link
Automated post-service review requests

Documented outcomes

Estimated valueDay 30: 9 emergency calls captured after hours with estimated recovery of $11,340
Reported changeDay 60: Owner stopped taking calls on his personal cell entirely
MeasuredOptimization window: Google reviews grew from 22 to 51Google Business Profile review-count observation before and after the installed review workflow.

Garage door repair

Technicians were splitting focus between installs and inbound calls, while time-sensitive evening replacement leads went unanswered.4 full replacement consultations bookedAfter-hours replacement consultations, day 60

Verified result

Confidential North American service business

As found

Technicians handled inbound calls while on jobs
Mid-install answers sounded rushed to callers
High-value installation leads often came in after 6 PM and went unanswered

Installed

AI voice agent handling all inbound calls
Separate urgency paths for emergency repairs and replacement consults
Missed-call text-back across unanswered lines

Documented outcomes

MeasuredDay 60: 4 full replacement consultations booked from after-hours callsDocumented after-hours lead and booking records compared before and after the installed response route.

Client case studies, drawn in full.

Six client engagements, from an IT certification provider serving learners worldwide to a Texas restoration company, a North Carolina CPA firm and a physical therapy clinic. Each case opens the work up: what we found, what we built, and what changed.

An IT certification provider whose growth became something it could measure, diagnose and improve.

SkillBook Academy

Improvement in conversion: ~35%
Less lead-handling and support workload: 50%+
Lower content-production cost: ~70%

IT training and certification provider · Toronto, serving learners worldwide

Read case 01

An evening study desk for an IT certification learner in Toronto: laptops with cloud architecture diagrams, a network switch, and a tabbed certification study guide. — Case 01

Supreme Restoration Group

The calls were already being answered. The problem started after the phone was put down.

As found

A whiteboard and a group chat

As built

A calendar that refuses a double-booking

Before: 22.9%First 90 Days: 85.6%

of emergency jobs had the insurance packet in within 48 hours. Before against first 90 days.

Disaster restoration (water, fire, and mold) · Texas

Read case 02

A flooded basement mid-restoration: air movers and a dehumidifier running while a gloved hand checks moisture in the wall. — Case 02

A partner's desk after hours in tax season: stacked client folders, a desk phone with a waiting message, the lamp still on. — Case 03

Carter CPA's & Advisors

A four-partner firm that couldn't tell a referral from a cold lead until the call had already started.

As found

Every inquiry in one shared inbox

As built

Sorted and routed before first contact

Before: 21.9%First 90 Days: 65.4%

of consultation requests reached a held consultation. Before against first 90 days.

CPA and accounting advisory firm · North Carolina

Read case 03

Liberty Physical Therapy & Wellness

One clinic. Online, patients kept finding three versions of it, and calling the wrong one.

As found

Three listings for one clinic

As built

One verified listing

Before: 58.9%First 90 Days: 95.7%

of new patients reached the clinic's correct listing on the first try. Before against first 90 days.

Physical therapy and wellness clinic · Florida

Read case 04

An empty physical therapy treatment room in morning light, with the front desk's booking tablet in view. — Case 04

A referral would open the door. The website was quietly closing it again.

IGF IT Consulting

As found

Trust lost at the website

As built

Referral context carried to the call

Before: 17.9%First 90 Days: 45.2%

of referred prospects became a paid engagement. Before against first 90 days.

Independent IT consulting · Ohio

Read case 05

A handwritten letter of introduction beside a closed laptop on a consultant's desk. — Case 05

BGM Insurance Agency

They already paid for a CRM. It just wasn't built to match how the agency actually worked.

As found

Renewals tracked by memory

As built

Reminders at 90, 60 and 30 days

Before: 49.2%First 90 Days: 93%

of renewals got a reminder 30 or more days before expiry. Before against first 90 days.

Commercial lines insurance agency · Atlanta, Georgia

Read case 06

227 reminder sent 30+ days before expiry17 without that lead time

A broker's policy binder open to a renewal schedule with a few dates highlighted. — Case 06

What happens to 250 calls.

A worked model you can reuse. The same 250 monthly calls meet two front doors. The share that survives every stage to a kept appointment is what we call the Intake Friction Index.

Modeled scenario

Question

A business gets roughly 250 calls a month. What does the same 250 calls produce with a generic front door versus a designed one?

Assumptions

Monthly inbound calls250

Average ticket$420

Close rate on kept visits50%

Stages counted5

The stages reflect a typical service-business front door: capture, qualify, book, show. If your intake path looks materially different, redefine the stages before you apply the score.
Every stage's count is a real, countable event you can pull from your own call logs, forms, or booking system.

Method

IFI = kept appointments ÷ inbound calls × 100

IFI equals the final stage's count divided by the first stage's count, times 100. The stages: inbound contact, answered, qualified as a fit, booked, shown. We derive every stage-to-stage percentage from the same whole-number counts, so the score and its breakdown can never disagree.

Monthly revenue = kept appointments × close rate × average ticket. This estimates an average, so fractional customer counts are retained until the displayed dollars are rounded.

Result

Generic front door: 18Designed front door: 56

45 kept appointments against 140. At the stated ticket and close rate, the generic door implies $9,450 a month and the designed door $29,400. The modeled gap is $19,950 a month, or $239,400 a year.

Reading it

The generic door loses the most between identified as a fit and booked an appointment: only 54.9% make that step. The designed door's weakest step moves to answered live or by ai receptionist into identified as a fit, at 78.2%.

Finding which single stage of the front door is losing the most demand, instead of assuming "we need more leads" is the answer.

What 40 follow-ups a week cost.

A business handles 40 new contacts a week that need follow-up. What does that follow-up cost in staff time when it runs on an inbox, a spreadsheet, and a calendar instead of one connected system?

ADM hours = contacts × minutes per touch ÷ 60 × handoff multiplier

As found499.2 hrs/year

As built76.27 hrs/year

Annual labor cost: $16,973 as found, $2,593 as built. Recovered: $14,380 a year. Annual totals use 52 weeks. Hours are rounded only for display.

Modeled at 40 contacts a week. As found: 6 minutes per manual touch and a 2.4x handoff multiplier. As built: 2 minutes and 1.1x. Both at $34 an hour fully loaded.

Field notes from real deployments.

What our AI receptionist deployments change for owner-operators, home-service teams and professional practices, in the words of the work itself.

Implementation record

Taking project inquiries while the owners are on site

For this interlocking business, the owners spend their working days in the field. English is not their first language, which also made handling English-language inquiries more demanding.

The AI receptionist collects the caller’s project requirements and schedules a time for a home visit. The customer can explain what they need while the owners continue their on-site work.

TQP reports that the owner is very happy with the intake experience. The receptionist handles the initial English-language conversation and home-visit scheduling, reducing the need for the owners to personally attend to incoming calls during field work.

Owner-operated service businesses

Solo operators: the next inquiry does not have to stop the current job

TQP describes the change as particularly meaningful for solo operators. The owner is also the person doing the work, so personally handling incoming calls competes with serving the customer already in front of them. TQP reports that its AI receptionist deployments handle initial intake while owners stay focused on their work.

What to take from it. For a solo business, start by deciding what the agent must collect and what the owner needs next. The interlocking deployment below is a concrete example: project requirements and a home-visit time.

Plumbing, electrical, garage-door, locksmith and restoration businesses

Home services: a useful first conversation while the team is in the field

TQP reports successful AI receptionist deployments across these home-service businesses in the United States, with positive feedback from clients and their customers. Initial intake is the shared job described in this account; the individual companies and their contact details remain private.

What to take from it. The implementation still needs to reflect the business. A booked home visit, a request for a callback and an urgent transfer are different outcomes. Use the workflow examples in our test guide to decide which outcome your calls need.

Accounting, legal and cosmetic-surgery practices

Professional practices: improving the first contact without replacing the professional

TQP also reports successful receptionist deployments and happy clients in these practice categories. The first conversation matters across all three, even though their intake requirements differ.

What to take from it. When evaluating a system for a practice, define what belongs in the first conversation and what needs the professional or a secure intake process. Test that boundary alongside the voice and the handoff.

Use the live-call test and launch checklist

Client words, in context

After nearly a year of failed attempts with other voice AI platforms, the system finally works for the clinic.

ClinicClient wordsRead our Google reviews

Faster response

Public reviews mention faster responses for parents, prospects, customers, and clients during busy operating windows.

Families are hearing back faster, staff has more visibility, and things are simply running more smoothly.

Daycare

Follow-up is faster, and there is a better handle on potential customers from the first message onward.

On-site service business

Prospects now receive a response within moments, and far fewer opportunities are lost.

Lead-driven service business

Cleaner booking

Customers call out easier appointment management, smoother inquiry-to-booking paths, and fewer missed opportunities.

Clients can choose available slots, appointments are easier to manage, and taking payments or deposits at booking has helped reduce no-shows.

Hair and beauty business

Everything feels a lot more streamlined, and it is much easier to stay on top of inquiries and bookings.

Appointment-based service business

Response times are faster, and the process from inquiry to booking is much smoother.

Salon

Managed growth work

Review excerpts mention social content, posting, review requests, follow-up, and customer communication becoming easier to keep up with.

The AI receptionist and follow-up system gives parents faster responses, keeps information organized, and makes follow-up easier.

Home daycare

AI-assisted content and scheduling made it feel like someone was helping manage social media consistently, even when we are busy.

Seasonal farm and local retail

Built around real operations

Customers repeatedly mention that the system was shaped around how their business actually runs, not handed over as a generic tool.

They helped set up systems that actually bring in leads without having to chase people all day.

Service business

New inquiries are handled better, follow-up is more consistent, and the business no longer feels constantly behind.

Client-service business

Now inquiries are handled right away, everything is more organized, and far fewer opportunities are being missed.

Busy local business

Signed reviews

Full reviews, with the reviewer's first name and last initial.

The AI receptionist and follow-up system gives parents faster responses, keeps information organized, and makes it easier for us to follow up when we are available.

Hriday M., home daycare. Google review

The AI-assisted content and scheduling made it feel like we have someone helping manage social media consistently, even when we are busy with the farm itself.

Simarjeet S., farm and seasonal business. Google review

Everything feels more streamlined, and it is much easier to stay on top of inquiries and bookings without feeling overwhelmed.

Rubalpreet K., appointment business. Google review

The process has become much more reliable and organized. Families are hearing back faster, our staff has more visibility, and things are simply running more smoothly.

Lovedeep K., daycare. Google review

Test the work before you talk to us.

Call the AI. Read the scope. Every item below is open to inspection, and none of it needs a meeting.

Live AI receptionist pressure test

Operating model

Call the public line with a realistic buyer scenario and test response, qualification, booking language, uncertainty, and escalation behavior.

Live public demonstration

Clear scope and commercial boundaries

Operating model

See the public Smart Website starting point, how deeper systems are recommended, what continues after launch, and which usage costs remain separate.

Public pricing and scope

Products with clear starting jobs

Operating model

See when a Smart Website, Platform Foundation, AI Receptionist, Automation System, or Custom Business System is enough and when it makes sense to step up.

Public product documentation

A practical keep, improve, or replace review

Operating model

See how TQP evaluates what already works, what needs to change, what should stay connected after launch, and what your team can use directly.

Public Systems Review method

Original research you can check and use.

Our accounting website study records what a prospective client could see on 118 public firm websites in the United States and Canada: contact routes, booking explanations, intake and response information. The published definitions, counts and denominators let you check the findings and cite The Quiet Protocol as the source.

This is a convenience sample of public pages. It measures visible information, not the firms' internal processes or revenue. For call answering, use our pressure test to check a demonstration and record the booking or handoff that actually reaches the receiving system.

Read the accounting website study · Check the method · Download the aggregate data · Test the call-to-record handoff

Questions a careful buyer asks about proof.

What proof is currently public on this page?

Seven real client results, with before-and-after numbers we can back up. We keep the client's name private, but the numbers are real. Real, dated Google reviews. In-depth client case studies that open specific systems up from the inside. Two frameworks we use ourselves, with the math shown. Everything on this page tells you which of these it is.

Will my business see the same results?

Every business starts from its own baseline, so we start with yours. The Revenue Leak Diagnostic shows where your front door is losing time and revenue, and a call with us turns that into a plan built around your numbers.

What can I inspect before speaking with TQP?

Read the real client results. Read the reviews. Call our live AI receptionist yourself. Check our published scope and pricing. Run the Revenue Leak Diagnostic with your own numbers. You can do all of this without booking a call or talking to anyone.

Ask us which source backs up any statement on this page, and we will show you.

You've read the record. Now let's draw yours.

Every case here started the same way: the business as it runs today, drawn honestly. A call with us does that for yours, then tells you whether the first move is a website, call coverage, connected follow-up, or something custom.

Book a call