From a standing start to A$501k in new revenue.

A high-value service with no way to be found.

Sunroof repair is a classic high-intent, low-frequency service. When a customer needs it, they need it now, and they are searching for it the same day. Auto Comfort had the workshop skill and the job value, with a typical repair sitting in the A$250 to A$1,500 range and an average job worth around A$500. What it did not have was a reliable way to be in front of those searches at the moment of need.

Two problems compounded that. First, there was no paid presence to build on, so every enquiry had to be created rather than optimised. Second, the standard industry habit of charging an inspection fee was quietly turning away ready-to-buy customers at the first contact. The business needed demand and it needed that demand to convert into booked, completed jobs, not just phone calls.

Build the demand, then model what makes it pay.

Because this was a "Both" engagement, the paid media was never run in isolation. The work was scoped around a simple commercial question: not "how many enquiries can we generate", but "how many of those enquiries become jobs, and at what cost". That framing is what makes a trade lead-gen account profitable rather than merely busy.

• High-intent demand capture, from zero. Search campaigns were built to capture the precise moment a local customer searches for a sunroof repair, prioritising the highest-commercial-intent queries over cheap, irrelevant volume.
• Pipeline analytics on the real funnel. Rather than stopping at lead count, the team tracked the full enquiry-to-job path, so spend could be judged on completed work and revenue, not form fills. This is the standard discipline of measuring cost per qualified outcome, not cost per click.
• Offer modelling to remove friction. The inspection-fee objection was replaced with a free inspection offer. Removing a small upfront cost at the top of a high-value funnel is a textbook conversion-rate move: it lifts the share of enquiries that progress without touching the underlying job economics.
• A website rebuilt to pre-qualify. The site was reworked to set price expectations early (the A$250 to A$1,500 range), build trust, and push a call-first path, so the enquiries that came through were already primed to book.

The lever was not more clicks. It was tracking enquiry-to-job, then removing the one cost that was stopping ready buyers from raising their hand.

None of this is a single channel trick. The paid spend created the demand, the analytics told the team which demand was worth paying for, and the offer and site turned that demand into booked work. Each part made the others measurable.

A$501k in new revenue, and a 65% enquiry-to-job rate.

From a standing start, the account built to roughly A$41,762 in monthly revenue and a cumulative A$501k of new revenue from Google Ads. Critically, the gains came with efficiency: enquiries arrived at A$41.70 each and converted to completed jobs 65% of the time, returning A$4.84 for every A$1 spent.

The combined result, demand created from nothing, converted efficiently, and modelled to job-level revenue, earned the account an APAC award. It is the clearest proof of the "Both" thesis on this site: paid media generated the enquiries, analytics decided which were worth paying for, and offer and site work turned them into completed, profitable jobs.

The economics were designed, not hoped for.

Plenty of trade accounts can buy clicks. Far fewer can tell you, with confidence, that two in three of the enquiries they buy turn into completed work at a known average value. By instrumenting the enquiry-to-job step and pricing every decision against it, the team could push spend toward the queries that actually produced booked jobs and strip out the volume that only looked good in a click report. The free-inspection offer and the pre-qualifying website then did the quiet work of lifting conversion without eroding the A$500 average job value, so each extra enquiry compounded into revenue rather than cost.