17 industries · five services
A call agent that answers, a website that converts, content, campaigns and follow-up. Five services, each one shaped around how your particular trade actually runs.
How the site converts
A site that takes the booking
People look you up on a phone, late, deciding where to go on Saturday. If the prices are not there and the only way to book is to ring during opening hours, they keep scrolling.
The work in photographs, the price list in full, and a booking form that arrives as a message rather than sitting in an inbox nobody opens. Built to load on a phone, which is where salon traffic comes from.
Key features
Example calculation
400 visits a month × 1 booking in 20 × €45 ≈ €900 a month
An illustrative projection built from typical figures for this trade — not a result we have measured.
How the call agent handles it
Answers while both hands are busy
Hands are in someone’s hair from nine in the morning. The phone rings anyway, and the caller rings the next salon on the list.
A stylist mid-colour cannot pick up the phone. The agent answers every call, gives the price and the opening hours, takes the booking — service, stylist, day and time — and sends it through the moment the call ends.
Example calculation: 6 recovered bookings a week × €45 average ticket ≈ €1,170 a month
How we grow the audience
The before and after does the selling
The transformations get photographed and then sit on a phone. Posting happens when somebody remembers, and the messages underneath go unanswered for days.
The transformations your stylists already photograph, captioned and posted to a plan rather than whenever somebody remembers. Comments and messages get answered, because a question left for two days is a booking that went somewhere else.
Example calculation: 3 enquiries a week from messages × 1 in 3 books × €45 ≈ €180 a week
How we turn spend into demand
The streets around the salon, not the country
Boosting a post reaches people who will never travel to your chair, and nobody can say what a booking actually cost.
Facebook and Instagram campaigns aimed at the few kilometres people will actually travel, for the services with the best margin. Setup, creative and copy, adjusted each month against what books rather than what gets liked.
Example calculation: €200 spend ÷ €25 per booking = 8 bookings × €45 ≈ €360
How we bring people back
The message that fills the empty chair
A client who came every six weeks stops coming and nobody notices for four months. Half the empty chairs on a Tuesday are people who simply forgot to rebook.
A client who came in eight weeks ago and has not rebooked gets a message with one link in it. A confirmation the day before cuts the no-shows. Both go out on a schedule you set once and then leave alone.
Example calculation: 2 fewer no-shows a week × €45 ≈ €390 a month
How the site converts
The menu, not a photograph of the menu
The menu is a PDF that opens sideways on a phone, and the only way to book a table is to ring during service.
What you serve, what it costs, and a table booked in three taps — on the phone somebody is holding while deciding where to eat tonight. The food photographed properly and the address in a link that opens maps.
Key features
Example calculation
900 visits a month × 1 booking in 30 × 2 covers × €28 ≈ €1,680 a month
An illustrative projection built from typical figures for this trade — not a result we have measured.
How the call agent handles it
Takes the booking while the room is full
The phone rings hardest during service, which is exactly when nobody can answer it. The table that wanted Friday at eight books somewhere else.
Nobody should walk away from a paying table to answer the phone at seven on a Friday. The agent takes the reservation — covers, time, the high chair, the allergy — and it reaches the pass before the caller has hung up.
Example calculation: 4 recovered tables a week × 4 covers × €28 a head ≈ €1,792 a month
How we grow the audience
The dishes, the room, the specials
The kitchen plates something worth photographing forty times a night and none of it gets posted, while the place down the road posts daily.
The plates photographed properly, the room when it is full, and the specials while they are still on. Posted to a plan rather than whenever the chef remembers, and the message asking whether you open on Monday gets a reply.
Example calculation: 6 bookings a week from messages × 2 covers × €28 ≈ €336 a week
How we turn spend into demand
The streets people will actually walk from
The budget goes to people who are not hungry, not nearby and not looking — and Tuesday stays quiet anyway.
Campaigns aimed at a couple of kilometres and at the hours people decide where to eat, promoting a set menu or an event rather than the restaurant in general.
Example calculation: €300 spend ÷ €12 a booking = 25 bookings × 2 covers × €28 ≈ €1,400
How we bring people back
The table you fill on a quiet Tuesday
Someone has a good dinner, means to come back, and does not. Nothing ever arrives to remind them.
Guests who came once and never came back get a reason to. Set menus, events and the quiet nights go to the list you already own rather than to strangers you have to pay a platform to reach.
Example calculation: 12 covers a week from the list × €28 ≈ €1,344 a month
How the site converts
A page a patient in pain can actually use
Patients arrive nervous and looking for reassurance — what it costs, what it feels like, who does it. A phone number and three stock photos answer none of that.
Treatments and what they cost, the team with faces and credentials, and a booking form that works on the phone somebody is holding in a waiting room. No price list hidden in a PDF and no contact form that goes nowhere.
Key features
Example calculation
600 visits a month × 1 booking in 25 × €180 ≈ €4,320 a month
An illustrative projection built from typical figures for this trade — not a result we have measured.
How the call agent handles it
Triage before the phone is put down
Reception is with a patient. The call that goes to voicemail was an implant consultation, and it rings the next clinic instead.
A patient in pain does not leave a voicemail, they call the next clinic. The agent answers, asks what the problem is, tells an emergency from a check-up, books it into the right kind of slot, and passes the urgent ones to your desk while the caller is still on the line.
Example calculation: 3 same-day emergencies a week × €180 first treatment ≈ €2,160 a month
How we grow the audience
Proof that it does not hurt any more
Dentistry is bought on trust, and nobody can see the work. The cases you are proudest of sit on a hard drive instead of where a nervous patient would find them.
Fear is the obstacle, so the content answers it: the room, the equipment, the person who will be holding the drill. Posted to a plan, with the questions underneath actually answered rather than left for a week.
Example calculation: 2 enquiries a week from messages × 1 in 4 books × €180 ≈ €360 a week
How we turn spend into demand
Advertising the treatments worth advertising
Bidding on the word “dentist” against every clinic in the city buys check-ups, not the treatments that keep the practice open.
Implants, aligners and whitening rather than a general advert for the clinic, aimed at the area people will actually drive to. What gets counted is consultations booked, not clicks collected.
Example calculation: €400 spend ÷ €50 a consultation = 8 consultations × €180 ≈ €1,440
How we bring people back
The recall nobody has time to phone
Recalls are somebody’s job until the day gets busy. A patient due every six months goes two years, and the hygienist’s diary has holes in it.
Six-month check-ups come due and nobody is going to ring four hundred people about it. The reminder goes out on its own with a link that books, and a second one follows for the patients who never opened the first.
Example calculation: 18 recalls booked a month × €40 consultation ≈ €720 a month
How the site converts
The listings, searchable on a phone
Buyers filter on a phone in ninety seconds. Slow photographs, a missing floor area and an eleven-field viewing form, and they are gone.
Properties with photographs, the price and the area, filtered the way buyers filter — rooms, budget, neighbourhood. Every listing has a button that books a viewing rather than a form that lands in a shared inbox.
Key features
Example calculation
1,200 visits a month × 1 enquiry in 40 = 30 enquiries × 1 sale in 15 ≈ 2 a month
An illustrative projection built from typical figures for this trade — not a result we have measured.
How the call agent handles it
Qualifies while you are in a viewing
Enquiries land while you are standing in an empty flat with a buyer. A viewing request that waits four hours is a buyer who booked with another agent.
An agent showing a flat cannot take the phone, and a buyer who does not get through rings the next agency. The agent asks the budget, the area and the timeline, says what is available, books the viewing, and sends it to you with all of it attached.
Example calculation: 2 extra viewings a week × 1 sale in 12 × €2,400 commission ≈ €1,700 a month
How we grow the audience
The walkthrough people watch to the end
Listings get posted the day they go live and never again, so the account reads as a noticeboard rather than somebody who knows the street.
A flat filmed properly does more than twenty photographs. Posted to a plan, with the price in the caption so the messages that arrive are from people who can afford it — and those messages get answered.
Example calculation: 4 enquiries a week from messages × 1 viewing in 3 ≈ 6 viewings a month
How we turn spend into demand
Advertising the listing, not the agency
The budget is spread over everyone in the city instead of the few thousand who could afford that flat and are looking this month.
Campaigns for the properties that need moving, aimed at the postcodes people are actually searching in. Counted in viewings booked rather than impressions served.
Example calculation: €500 spend ÷ €35 a viewing = 14 viewings × 1 sale in 12 ≈ €2,400
How we bring people back
The buyer who was not ready in March
Most people who enquire are six months from buying. With nothing arriving in between, they are somebody else’s client by then.
Somebody who viewed and did not offer is not a lost lead, it is a lead with a date on it. New listings matching what they asked for go out on their own, to the list you already own.
Example calculation: 8 buyers re-engaged a month × 1 viewing in 4 ≈ 2 viewings
How the site converts
The stock list that sells overnight
A buyer wants the mileage, the monthly figure and whether it is still there — at eleven at night. A site that makes them ring in the morning loses them.
Every car with its photographs, the year, the mileage and the monthly finance figure, filtered by budget and body type. A test drive booked from the vehicle page at eleven at night, with nobody on the floor.
Key features
Example calculation
2,000 visits a month × 1 enquiry in 50 = 40 enquiries × 1 sale in 8 ≈ 5 a month
An illustrative projection built from typical figures for this trade — not a result we have measured.
How the call agent handles it
Catches the test-drive request
Saturday is the busiest day on the floor and the worst day to reach anyone by phone. Part-exchange questions and test-drive requests go to voicemail.
A salesperson on the floor cannot break off to answer, and a buyer who does not get through calls the next dealership. The agent takes the model and the trim, notes the part-exchange, and books the test drive before the caller has hung up.
Example calculation: 3 recovered test drives a week × 1 sale in 6 ≈ 2 sales a month
How we grow the audience
The walkaround that shifts the unit
Stock photographs of cars that could be on any forecourt. Nothing shows how it sounds, how it drives, or who hands over the keys.
The car filmed the way a buyer walks around it — the wheels, the interior, the boot, the mileage on the dash. Aimed at the stock that has been standing longest, and the messages underneath get answered.
Example calculation: 5 enquiries a week from messages × 1 sale in 10 ≈ 2 sales a month
How we turn spend into demand
Advertising the car, not the showroom
Advertising the whole forecourt to the whole county costs more per enquiry than putting one car in front of the people searching for that model.
Campaigns for specific stock rather than for the dealership, on a wider radius than most trades use, because people will travel to buy a car. Counted in test drives booked.
Example calculation: €800 spend ÷ €60 a test drive = 13 drives × 1 sale in 6 ≈ 2 sales
How we bring people back
The customer whose finance ends in April
The person who test-drove and did not buy is the warmest name on the list, and nobody ever contacts them again.
Somebody three years into a four-year agreement is a buyer with a date on them. The message goes out before the dealership down the road works that out, carrying cars that match what they are already driving.
Example calculation: 12 finance-end contacts a month × 1 sale in 6 ≈ 2 sales
The problem
Reception lines are jammed at peak hours while patients wait on hold — many hang up and call another clinic. After hours, the phone simply rings into voicemail nobody checks.
How the call agent handles it
The agent picks up every call, triages the reason for the visit, and books patients directly into open slots. Urgent cases are transferred to staff immediately; routine ones are handled end-to-end, day or night.
Key features
The result
12 recovered appointments per month × €90 consultation ≈ €1,080/month.
The AI agent costs a fraction of that — and answers on the first ring.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
Direct-booking calls arrive around the clock — and every one that lands in voicemail becomes an OTA booking with 15-20% commission attached. Night shifts can't staff the phones properly.
How the call agent handles it
The agent answers 24/7, quotes live room availability and rates, and books direct — no commission. Guest questions about check-in, parking, or breakfast are handled instantly in multiple languages.
Key features
The result
9 direct bookings per month × €160 per stay ≈ €1,440/month — with zero OTA commission.
The AI agent costs a fraction of that — and works every night shift.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
The phone rings all day — quotes, MOT bookings, and the same question ten times over: is my car ready. The mechanic is under a car with oily hands, so it rings out, and the job goes to the workshop down the road.
How the call agent handles it
The agent answers every call, takes the registration and the symptom, books the slot, and tells the caller when the car will be ready — without anyone putting down a spanner.
Key features
The result
5 recovered jobs per week × €120 average bill ≈ €2,600/month in recovered work.
The AI agent costs a fraction of that — and never has oily hands.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
Front desk staff coach, tour, and clean — the phone is nobody's first job. Trial-class inquiries after 8 PM land in voicemail, and tomorrow they've joined the gym across town.
How the call agent handles it
The agent answers membership questions, books trial classes into real schedules, and follows up with SMS reminders that actually get people through the door. Every inquiry becomes a booked visit.
Key features
The result
18 trial classes per month → 7 new members × €40 ≈ €280/month recurring — compounding every single month.
The AI agent costs a fraction of that — and never skips a shift.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
Potential clients call in a moment of urgency — a dispute, an accident, a deadline. If they reach voicemail, they call the next firm. Attorneys can't bill hours and answer intake calls at once.
How the call agent handles it
The agent handles first contact professionally, triages the case type, captures the essentials, and books a consultation with the right attorney. Your intake pipeline fills itself while you practice law.
Key features
The result
6 extra consultations per month × €180 ≈ €1,080/month — before the value of the cases themselves.
The AI agent costs a fraction of that — and bills zero hours.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
During tax season the phone doesn't stop; the rest of the year, every interruption breaks deep-focus work. New-client calls compete with deadlines — and deadlines usually win.
How the call agent handles it
The agent books consultations, answers scope-and-pricing basics, and sends new clients the document checklist by SMS before they even arrive. Your team stays heads-down; the pipeline keeps moving.
Key features
The result
4 new retainer clients per quarter × €250/month ≈ €330/month recurring — compounding as the book grows.
The AI agent costs a fraction of that — even in April.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
A burst pipe at 2 AM doesn't wait for office hours. Technicians can't answer from under a sink — and an emergency caller who hits voicemail hires whoever picks up next.
How the call agent handles it
The agent answers around the clock, captures the emergency, dispatches the on-call technician, and texts the customer a live ETA. Routine quotes and maintenance visits get scheduled without interrupting jobs.
Key features
The result
7 captured emergency jobs per month × €240 average ticket ≈ €1,680/month.
The AI agent costs a fraction of that — and answers at 2 AM.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
Estimators are on site, not at a desk — quote requests pile up in voicemail for days. By the time you call back, the project has been promised to a competitor.
How the call agent handles it
The agent captures every quote request in full — project type, size, budget, timeline — and books the site visit while interest is hot. Your estimators show up with the details already in hand.
Key features
The result
3 extra site-visit quotes per month → about one project per quarter ≈ €2,000+/month averaged.
The AI agent costs a fraction of that — and never leaves the office.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
Crews are inside client homes and offices all day; the phone rings in a van. One-off callers who can't book become someone else's recurring contract — the revenue that actually matters.
How the call agent handles it
The agent quotes standard jobs, books one-off cleans, and converts them into recurring weekly or bi-weekly schedules on the call. Reminders and reschedules are handled by SMS automatically.
Key features
The result
9 new recurring clients per quarter × €130/month ≈ €390/month recurring — compounding every quarter.
The AI agent costs a fraction of that — and never misses a callback.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
"Where is my order?" is 60% of your support volume — repetitive, urgent to the customer, and expensive to staff. Slow answers turn into disputes, refunds, and one-star reviews.
How the call agent handles it
The agent looks up orders instantly, reads out live tracking, and handles returns and exchange questions end-to-end. Your human team keeps only the conversations that actually need them.
Key features
The result
320 status calls handled per month ≈ 21 support hours saved ≈ €420/month — plus fewer disputes and refunds.
The AI agent costs a fraction of that — at any order volume.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
Claims calls spike exactly when your team is busiest — after storms, accidents, weekends. New-policy leads wait behind claim intakes, and both walk away frustrated.
How the call agent handles it
The agent files claim intakes step by step, looks up policy details, and qualifies new-coverage leads — separating the urgent from the routine so your brokers work the right calls first.
Key features
The result
20 qualified leads per month → 3 policies × €210 average commission ≈ €630/month.
The AI agent costs a fraction of that — rain or shine.
An illustrative projection built from typical figures for this trade — not a result we have measured.
The problem
Trip inquiries arrive at 11 PM, on weekends, from different time zones — long after the office closes. Each unanswered call is a €2,000 holiday booked with an online competitor.
How the call agent handles it
The agent captures destination, dates, party size, and budget the moment inspiration strikes, then books a consultation with your travel expert. Warm leads land in your inbox every morning.
Key features
The result
10 trip inquiries per month → 3 bookings × €350 commission ≈ €1,050/month.
The AI agent costs a fraction of that — in every time zone.
An illustrative projection built from typical figures for this trade — not a result we have measured.