Washing Machine Broken. Asked Facebook. Found You. Messaged. AI Booked the Repair.

When someone messages your Facebook business page about a broken appliance — a washing machine that won't spin, an oven that isn't heating, a fridge that's stopped cooling, or a dishwasher leaking on the kitchen floor — the AI reads their message, understands the appliance repair context, and sends a professional reply within seconds. The AI demonstrates genuine diagnostic knowledge: if someone describes a washing machine that fills with water but won't spin, the AI mentions common causes like worn motor carbon brushes, a failed motor control module, or a faulty door interlock. It then asks for the make, model number (located on a sticker inside the door frame), and the customer's postcode so you can check parts availability and schedule a visit. Every conversation generates a lead notification with the customer's details, the appliance type, the symptoms described, the brand and model if provided, and their location. Your Facebook page badge updates to "Typically replies instantly," which is critical for appliance repair because a broken washing machine or a dead fridge creates genuine household urgency.

Appliance breakdowns trigger a very specific request pattern in Facebook community groups: "can anyone recommend someone to fix a washing machine?" This question appears in local groups and mums' groups multiple times per week, because appliance failures are common, urgent, and affect daily family life. The responses come quickly — "we used [your name], he was brilliant, fixed our Bosch in twenty minutes" — and within minutes, the original poster has clicked through to your Facebook page and messaged you. These referral-driven leads are exceptionally high quality. The customer arrives at your page already trusting your competence because someone they know has vouched for you. The conversion rate for appliance repair leads from Facebook referrals is remarkably high because the combination of built-in trust and genuine household urgency means the customer isn't comparison shopping — they want you, specifically, to come and fix their appliance. The AI's instant, knowledgeable response confirms the good impression that the referral created, and the repair gets booked within minutes of the original Facebook post.

The AI is configured with knowledge of common fault patterns across major appliance types, which allows it to provide genuinely helpful preliminary guidance in its initial Messenger response. When a customer describes their washing machine filling but not spinning, the AI mentions motor brushes, control boards, and door interlocks as common causes — not as a definitive diagnosis, but as reassurance that the symptom is recognisable and fixable. When someone describes their tumble dryer stopping mid-cycle, the AI mentions thermal fuse failure and blocked lint filters. When an oven isn't heating on the fan setting, the AI mentions the circular heating element. This diagnostic knowledge serves two purposes. First, it reassures the customer that you know what you're talking about — they feel they're dealing with a genuine appliance specialist, not a general handyman. Second, it helps you prepare: if the AI has captured the model number, the brand, and the symptoms, you can identify the likely fault and check parts stock before you visit. Arriving with the right part and completing the repair in a single visit is the hallmark of a professional appliance engineer, and the AI's information capture makes this possible.

Yes — the AI handles enquiries across all major domestic and commercial appliance brands and types. Whether the customer has a Samsung, Bosch, LG, Hotpoint, Indesit, AEG, Miele, Beko, Siemens, Whirlpool, Zanussi, or any other brand, the AI confirms that you repair their make and asks for the specific model number for parts identification. The AI also covers the full range of household appliances: washing machines, tumble dryers, washer-dryers, dishwashers, ovens, hobs, cooker hoods, refrigerators, freezers, fridge-freezers, and microwave ovens. Each appliance type generates different diagnostic questions — the AI asks about spin issues for washing machines, heating problems for ovens, temperature readings for fridges, and water ingress for dishwashers. Whether customers find your Facebook page searching for an appliance repair engineer, a washing machine repair service, an oven repair company, a white goods engineer, a domestic appliance technician, or an appliance fixer, the AI captures their enquiry with the right brand and diagnostic context.

The Messenger automation is £29 per month as an add-on to the Speed Receptionist Core plan at £89 per month. Unlimited messages are included with no per-conversation charges. There's a one-time setup fee of £299, fully refundable within 30 days. For an appliance repair business, the value is obvious when you consider typical job values and the urgency that drives conversions. A washing machine repair with parts is worth £80 to £180. A tumble dryer repair is £70 to £150. An oven element or thermostat replacement is £80 to £160. A fridge compressor repair or gas recharge is £120 to £250. A dishwasher pump or valve replacement is £80 to £150. If the Messenger AI captures just one additional washing machine repair per week from a Facebook referral — a mum who messaged your page at 6pm after a group recommendation — the weekly return exceeds the monthly cost. Appliance repair has particularly high conversion rates from Facebook because the urgency (family without a working washing machine) drives immediate booking decisions.

The urgency created by a broken essential appliance is fundamentally different from other home repair needs. A leaking tap can be managed with a bowl underneath. A cracked tile is cosmetic. But a dead washing machine with three children's worth of school uniforms, sports kits, and daily clothes creates a genuine, escalating household crisis. Every day without the machine means either hand-washing, trips to the launderette, or an increasingly desperate pile of dirty laundry. The same applies to a broken fridge in summer, a dead oven during the week, or a dishwasher flooding the kitchen floor. This urgency means that the customer who messages your Facebook page isn't casually browsing — they need the repair done as soon as physically possible. The AI's instant response captures them at this peak moment of motivation. If your page responds in seconds with knowledgeable diagnostic guidance and asks for their model number, they feel confident that a professional is handling their problem. If your page takes three hours to respond, they've already booked someone else. For appliance repair, response speed directly equals booking rate.

Yes — the AI handles the initial engagement and diagnostic capture, then you take over for parts confirmation, pricing, and appointment scheduling. This workflow is ideal for appliance repair because the AI captures the information you need most: the appliance type, the brand, the model number, the symptoms, and the customer's location. When you take over the conversation, you can check your parts stock against the model number, estimate the likely fault from the symptoms, and offer a specific appointment time. The customer sees a single continuous conversation thread — no awkward handover. Many appliance repair engineers find that the AI's initial capture saves them ten to fifteen minutes per lead: instead of calling back, asking "what make is it?" and "what's happening exactly?", they already have everything they need to schedule efficiently. This is particularly valuable when you're at a customer's house mid-repair and can't take calls — the AI captures the next lead while you're focused on the current job.

It's common for customers to message about more than one appliance issue, particularly if they've been putting off repairs. A message like "my washing machine is making a grinding noise AND the oven fan isn't working — can you fix both?" is handled naturally by the AI. It asks diagnostic questions for each appliance separately: the washing machine brand, model, and specific noise description, followed by the oven brand, model, and which setting isn't working. This multi-appliance capture is valuable because it increases the visit value — a single attendance that fixes both a washing machine and an oven is worth £150 to £300, compared to £80 to £150 for a single repair. The AI presents this as convenient for the customer: "great, we can look at both during the same visit." By capturing complete information for both appliances upfront, you can check parts for both machines before attending, increasing the likelihood of completing both repairs in a single visit — which impresses the customer and maximises your time efficiency.

Appliance breakdowns cluster around usage times — mornings and evenings for washing machines, mealtimes for ovens and dishwashers, continuously for fridges. A washing machine that fails during the Saturday morning laundry session generates a Messenger message by Saturday lunchtime. An oven that stops working at 5pm on a weekday while dinner is being prepared generates a frantic evening message. These are the moments when appliance repair leads are created, and they happen almost exclusively outside business hours. The AI captures these leads instantly, providing reassurance and diagnostic capture at the exact moment the customer is most motivated to book. Without the AI, your page sits silent from 5pm Friday to 9am Monday — and by Monday morning, every weekend appliance breakdown has been booked with another engineer. With the AI, you arrive on Monday morning with a complete list of weekend leads: each one pre-qualified with appliance brand, model, symptoms, and location, ready to schedule into the week ahead.

Most appliance repair businesses are live within 48 hours. The setup connects your existing Facebook business page to the AI — we handle the technical integration. During a brief onboarding conversation, we learn about your appliance repair business: the appliance types you repair (washing machines, tumble dryers, dishwashers, ovens, hobs, fridges, freezers), the brands you cover, whether you carry common parts or order per job, the areas you serve, and the diagnostic approach you want the AI to take. The AI is then configured to respond to the full range of appliance enquiries with appropriate brand awareness and diagnostic guidance. We test with simulated messages across multiple appliance types before going live. Your total time commitment is about fifteen minutes. Once active, every Messenger message — whether a panicking mum at 7am on a Monday or a methodical homeowner comparing engineers on a Sunday afternoon — receives an instant, knowledgeable response that captures the right diagnostic details for your follow-up.