Audience targeting in paid ads is how you tell an ad platform who should see your ads (and who should not) so your budget goes to people most likely to become customers.
Instead of showing your ads to “everyone in Orlando,” you set rules and signals like location, age range, interests, recent online behavior, and past interactions with your business. Google Ads and Meta (Facebook/Instagram) build audience segments from these signals, then match your ads to people who fit your settings. The practical payoff is simple: fewer wasted clicks, better lead quality, and cleaner data when you review results.
What you can target (and what it looks like for a local business)
| Targeting type | What it does | Best use | Orlando example |
|---|---|---|---|
| Location and radius | Shows ads only in specific cities, ZIP codes, or within a distance from a point | Service-area businesses and storefronts | Only show ads within a 10 mile radius of your office, or exclude areas you do not serve |
| Demographics | Targets by age range, gender, parental status, household signals (varies by platform) | When your buyer profile is truly narrower than “any adult” | A pediatric dentist focuses on parents, a retirement community service focuses on older adults |
| Interests and intent | Reaches people likely interested in topics or actively shopping for something | Discovery and demand capture outside pure keyword search | Home services reach homeowners browsing repair topics, not just searching “near me” |
| Your data (remarketing and customer lists) | Targets people who visited your site, engaged with ads, or are on a customer list | Following up with warm prospects and reducing no-show leads | Show a follow-up offer to people who visited your pricing page but did not book |
| Lookalike or similar audiences | Finds new people who resemble your best customers or converters | Scaling prospecting once you have solid conversion data | Build a lookalike from booked consultations to reach new, similar prospects |
| Exclusions | Prevents ads from showing to people you do not want | Stopping wasted spend and avoiding customer annoyance | Exclude existing customers, job seekers, or out-of-area ZIP codes |
On Google Search, keywords still do most of the heavy lifting, but audience targeting can be layered on top to guide bidding and messaging. On paid social, audiences are often the main driver since people are not searching in the same way.
How we usually set it up for small and mid-size businesses
- Start with geography: draw your real service area first. If you are a service business in Central Florida, radius and ZIP exclusions can matter as much as the ad copy.
- Match intent to the funnel: use higher-intent audiences (and tighter targeting) when you need leads now, and broader targeting when you have strong tracking and creative that qualifies buyers.
- Build a warm layer: remarketing and customer lists are often the cheapest wins because you are speaking to people who already know you.
- Use exclusions early: they protect budget and reduce repeated impressions to the wrong crowd.
If you are new to audience work, keep it simple and measurable: one audience change at a time, clear conversion tracking, and enough time for the platform to learn. If you are also dialing in service-area settings, our guide on PPC location targeting pairs well with audience planning because geography is usually the first filter that saves money.
For growth, lookalikes can work well once you have consistent conversion volume and clean tracking. If that is the direction you are headed, the plain-English explanation of lookalike or similar audiences helps you set expectations and avoid over-broad expansion.
When you want targeting that fits your market, offers, and seasonality (tourism, commuters, and neighborhood-by-neighborhood differences are real in Orlando), we can map your audiences to each campaign goal as part of our PPC management. If most of your spend is on Facebook and Instagram, pairing it with paid social support can help your targeting and creative work together, which is usually where the biggest performance jumps come from.
