Suburb-level vs city-wide ads for AU service businesses

When a plumber from Marrickville sets up Google Ads and targets "Sydney," they're competing against every plumber in a 70km radius — including the ones in Parramatta, Penrith, and Castle Hill who have zero interest in servicing Marrickville at all. The result is a higher CPC, worse quality scores, and leads from suburbs that are either too far to serve efficiently or outside the postcodes where the business has actual reviews and word-of-mouth.

Suburb-level targeting is one of the most consistent wins we see across AU service business ad accounts. Here's the logic and the implementation.

Why "Greater Sydney" campaigns fail

Sydney's metro area spans roughly 12,000 square kilometres. Melbourne's isn't much smaller. A plumber based in Balmain has a realistic service radius of maybe 12–15km before travel time kills the job margin. Running ads city-wide means you're paying for impressions and clicks from Campbelltown, Blacktown, and Sutherland — all of which require 45-minute drives that eat into profitability on a $350 job.

Beyond the geographic waste, there's a quality score issue. Google rewards ads that are highly relevant to the searcher's location. A campaign with tightly defined suburb targeting and a landing page that mentions those suburbs will outperform a city-wide campaign on Quality Score — which means lower CPC at the same position.

How we structure suburb-level campaigns

The approach we use for most AU service businesses:

Identify your core 6–10 suburbs. These are the postcodes where you already do the most work, have reviews, and can service quickly. For a Balmain plumber, this might be Balmain, Rozelle, Lilyfield, Annandale, Glebe, Forest Lodge, Leichhardt, and Petersham.

One campaign per cluster, not per suburb. You don't need 10 separate campaigns. Group geographically close suburbs (same council area, similar demographics) into one campaign with its own budget and bid. This gives you spend control per zone without the management overhead of 10 campaigns.

Match the landing page to the cluster. This is where most businesses leave money on the table. The ad says "Plumber in Balmain" but the landing page says "Sydney's most trusted plumber." The location signal is broken. A landing page that specifically mentions Balmain, Rozelle, and Leichhardt — with a headline referencing the suburb — will convert dramatically better.

Bid modifiers for high-value suburbs. If your data shows that Glebe calls convert to booked jobs at 50% while Leichhardt is 25%, apply bid adjustments. You want more of Glebe, fewer of Leichhardt. Most accounts don't do this — they treat all suburbs the same.

A Melbourne example pattern

Consider a typical inner-north Melbourne electrician running a single city-wide campaign at $120/day. The pattern in this kind of account: a large share of spend (often 50–60%+, industry est.) bleeds into geographies the business never wins jobs in — south of the river, far suburbs — despite all of the operator's reviews coming from a tight cluster of inner-north postcodes (Fitzroy, Carlton, Brunswick, Northcote).

When a service business switches from broad-match Google Ads to tightly-grouped suburb-cluster campaigns and cuts the geographies it doesn't actually serve, CPA can drop 30–50% inside the first few weeks of optimisation, and bookings on the same daily spend tend to climb meaningfully. (Pattern from industry research and account audits; specific results vary.)

The Meta approach (different mechanics)

On Meta (Facebook/Instagram), suburb-level targeting works differently. You can't target by postcode with the same precision as Google. The workaround:

• Use a pin-drop radius around your home base. Start at 10km and test down to 7km if leads are coming from too far afield.
• Use custom audiences built from your existing customer list — Meta will find lookalikes in the same geographic clusters where your current customers live.
• Exclude suburbs that haven't converted historically. If your data shows 30 clicks from Penrith and zero booked jobs, add Penrith to your exclusion list.

The postcode data you need

Before you restructure any campaign, pull your job history for the last 12 months. Group jobs by postcode. Identify your top 10 by volume and your top 10 by average job value (these are often different). Target the overlap first — high volume + high value suburbs get the most aggressive bids. Low volume, low value suburbs either get a modest secondary budget or nothing.

This sounds obvious written down. Almost no AU trade business has done it systematically.