Author – Ken Hobson.
When someone searches for property in their own suburb—say “Paddington homes for sale”—an ad that actually mentions Paddington feels instantly relevant.

Hyper-local copy lifts click-through rates, lowers cost-per-lead, and shows that your brand truly “knows the neighbourhood”.

Thanks to large-language models (LLMs) you can now create this suburb-specific copy at scale, without writing dozens of near-identical ads by hand.

The Core Idea in One Line

Feed suburb data into an LLM, let it draft location-specific headlines and descriptions, then publish through Google or Meta features that insert the right suburb for each viewer.

Step-by-Step Workflow

1. Collect reliable suburb data

   • Median sale price, days-on-market, rental yield

   • Lifestyle hooks (beachfront, cafés, school zones)

   • Store everything in a spreadsheet or CSV

2. Write a master prompt

   You are a real-estate copywriter.  
   Use the brand voice shown below.  
   Write three ad headlines (30 chars) and two descriptions (90 chars) that highlight:
   • Suburb Name  • Median Price $XXX  
   • Lifestyle Hook  
   Keep reading level Year 5.
   

3. Run the prompt for every row
   Most LLM tools (ChatGPT, Google Gemini, Claude) let you loop through a sheet and return fresh copy for each suburb.

4. Review for brand consistency
   Edit once, then reuse the same tone everywhere.

5. Bulk-upload to the ad platform

   • Google Ads: import as a feed and map each field; Location Insertion will automatically drop the user’s city or suburb into the ad if you add the {LOCATION(City)} placeholder. 

   • Meta (Facebook/Instagram): Advantage+ catalog or housing ads pull suburb, price, and listing URL straight from your feed, and Meta’s new generative text suggestions can create variants on the fly. 

Keeping the Brand Voice Consistent

LLMs mimic the examples you give them. Paste a short “voice guide” at the start of every prompt:

“We are a boutique agency. Tone is warm, confident, and plain English. Avoid jargon. Use active verbs. Never use clichés like ‘must see’.”

Because every suburb prompt uses the same guide, all ads sound like they came from one writer—even though the copy is unique to Randwick, Toowong, or Fremantle.

Sample Output

Each line was generated automatically from one spreadsheet row.

Pro Tips for Real-Estate Campaigns

• Use Lifestyle Hooks: Beaches, schools, transport—data points that matter locally.

• Add Emojis Sparingly: A small 🌊 or 🏡 can lift engagement on Facebook but stick to plain text on Google.

• Refresh Quarterly: Update median prices and days-on-market so ads stay accurate.

• A/B Test Two Variants: Let Google’s or Meta’s AI choose the winner; you’ll learn which suburb benefits grab attention fastest.

• Comply with Housing Rules: Both platforms have strict policies for targeting and wording property ads—double-check before launch.

Expected Results

Agents who shift from generic metro ads to suburb-specific copy typically report:

• Higher click-through rate (CTR): 20–30 % uplift is common.

• Lower cost-per-lead (CPL): More relevance = better Quality Score on Google and lower auction prices on Meta.

• Faster enquiry-to-inspection: Buyers feel you already understand their patch, so trust builds quickly.

Getting Started Today

1. Export suburb metrics from your CRM or a data provider.

2. Test your first LLM prompt on three suburbs to fine-tune the style.

3. Build a simple Google Ads feed or Meta Advantage+ catalogue.

4. Launch, monitor, and scale to every postcode in your service area.

In one afternoon you can turn raw suburb data into dozens of smart, on-brand ads—ready to meet prospects exactly where they live.