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Every workshop knows the job in the bay. Tyres, brakes, batteries, air conditioning and shock absorbers are fitted quickly and fitted well. Demand is the part that is still guesswork. Bays overflow on a Saturday and sit half empty on a Tuesday, and blanket discounts only make the swing worse. An unsold bay hour never comes back. At MotorK, we built PredictSparK to make that calendar predictable. This is what happened when a national fast-fit network with 300+ centres put it to work.
The challenge
The money doesn't leak in the work itself. It leaks through three quieter problems that you can't see on a walk around the shop floor. They only show up once the numbers are added up.
Idle capacity. Peaks create queues and walkouts, while quiet days leave paid technicians standing idle. Blanket promotions make it worse, because they pile even more demand onto days that are already full.
Lost repeat visits. Customers price-shop and drift away. A technician flags an advisory at the ramp, such as front pads at 3 mm. The note is recorded, and then nobody acts on it.
No standard, and no proof. Every site promotes in its own way, and reporting stops at clicks. Nobody can tie a campaign back to an invoice, so nobody can say what actually worked.
What they did
Together with MotorK, the network used PredictSparK to score every customer every day on how likely they were to buy each service in the next 30 days. Head office set one playbook per service line (tyres, brakes, batteries, air conditioning and shock absorbers). Only the top-scoring customers were invited, by SMS and email. Each centre chose how many customers to contact, so the invitations matched the free capacity in its bays. Every result was then matched to real invoices, campaign by campaign and centre by centre.
The results
€1.8M in workshop revenue from invoices linked to the campaigns
30 campaigns across five service lines
40,757 messages delivered
11.9% of customers reached came back within 60 days (4,854 visits)
302 of 303 centres reached customers
Every service line converted at double-digit rates:
Batteries: 17.5%
Air conditioning: 16.6%
Tyres: 10.2%, the highest volume and the highest revenue (€519k)
Brakes: 10.1%
Shock absorbers: 10.1%
On campaigns whose 60-day window has already closed (April to July 2026), the return rate is 14.4%.
The operator sets the balance between precision and volume. Campaigns that invited only customers scoring 90 or above converted at 19.1%. Lowering the minimum score to the 75–90 range reached far more customers, at 8.8%.
Conversion means an invoice on the same vehicle within 60 days of the message, excluding the first 2 days. Rates are calculated on messages delivered. Revenue counts every invoice on that vehicle in the window, not only the promoted service. The most recent campaigns are still maturing, so the rate is expected to rise.
Why it works
Wear on tyres, brakes and batteries follows a clock of mileage and time, and a workshop's own invoices already record it: kilometres per year, last fitment, vehicle age, season and location. That makes after-sales demand some of the most predictable in automotive. The signal is already in the data; it only has to be read and acted on. That is the principle behind PredictSparK: we don't add new data, we read the data your workshops already own.
What it means for you
Fast-fit is one of the toughest tests in after-sales: high volume, price-shopped customers and little loyalty. That's why we're proud of these results, and why we're bringing the same approach to every workshop we work with. The pilot reached only around 5% of the network's 860,000+ customers, so scaling is a targeting decision, not a new project. Want to see what PredictSparK could do for your workshops? Request a demo.
