Paid social targeting works by letting you choose who can see your ads (audiences), then the platform’s algorithm uses your settings plus its own data signals to deliver ads to the people most likely to take action within that audience.
Think of targeting as guardrails, not a guarantee. On Meta (Facebook/Instagram), TikTok, LinkedIn, and other networks, you set boundaries like location, age, interests, job roles, or “people who visited your website,” and the ad system runs an auction for impressions. If you optimize for leads, calls, or purchases, the system will typically shift delivery toward people inside your audience who behave like converters (not just scrollers). That’s why two businesses can pick the same audience and get different results, your offer, creative, landing page, and tracking quality change what the algorithm learns.
What you can target in paid social
| Targeting type | What it’s based on | Best use | Common pitfall |
|---|---|---|---|
| Location | City, ZIP, radius, “people living in” vs “recently in” (varies by platform) | Local services in Orlando, Winter Park, Lake Nona, Clermont, etc. | Too tight a radius can starve delivery, and “recently in” can pull tourists if you do not want them |
| Demographics | Age ranges, gender, language, household and life-stage signals (platform dependent) | When eligibility matters (example: seniors for denture consults) | Over-filtering shrinks reach and raises costs |
| Interests and behaviors | Content engagement, page follows, in-app activity, inferred preferences | Top-of-funnel awareness and “problem aware” audiences | Interest targeting can be noisy, and platforms change available interests over time |
| Professional targeting (LinkedIn) | Job title, job function, seniority, company size, industry, skills | B2B lead gen, recruiting, high-consideration services | Stacking too many filters can make the audience too small to spend reliably |
| Custom audiences (first-party) | Your customer list (hashed), website visitors, app users, lead form engagers, video viewers | Retargeting and warm follow-up that usually converts best | Needs enough volume, and you must use consent-based data, especially in regulated industries |
| Lookalike or similar audiences | People who “look like” your converters or customers | Scaling once you have solid conversion data | Garbage in, garbage out, if your seed list is low quality, the lookalike will be too |
| Exclusions | People you want to remove (existing customers, recent leads, employees) | Reducing wasted spend and cleaning up reporting | Some platforms limit exclusions in certain cases, so your structure may need to change |
How the platform decides who actually sees the ad
After you pick targeting, delivery is driven by three things: (1) your bid and budget, (2) your ad quality and expected engagement, and (3) the likelihood of the result you chose (lead, call, purchase). If your campaign is set for “leads,” the system will usually favor people inside your audience who have a history of submitting forms or taking similar actions. That is why conversion tracking matters: pixels, events, and offline lead imports help the algorithm learn which clicks turned into real booked appointments or signed contracts.
For most Orlando businesses, the simplest winning setup is: one cold audience (location + broad signals), one warm audience (retargeting), and one scale audience (lookalike or similar). If you need help setting up conversion tracking and lead quality feedback, our PPC management process includes the tracking pieces that keep paid social from turning into “clicks with no calls.”
Orlando and Florida specifics that change how you target
Central Florida can swing between locals and visitors depending on season and where you serve. If you only want residents for recurring services (pest control, dental hygiene, lawn care), use location settings that focus on people who live in your service area, then add exclusions for people who already converted in the last 30 to 180 days. If you do event-driven work (weddings, attractions, short-term rentals), you can test a separate campaign that allows visitors and recent travelers, then compare lead quality.
If you are in healthcare, dental, law, or anything regulated, treat targeting and creative like compliance-sensitive work. Do not upload patient lists without proper permission, avoid implying you know someone’s condition, and keep your landing page forms minimal. A fast, clear landing page also affects performance, and this quick breakdown of website vs webpage vs landing page helps when you are deciding what to send traffic to.
Practical steps to build targeting that performs
- Start with your goal: calls, booked consults, quote requests, or purchases. Pick one per campaign.
- Pick your geography first. For most local services, start broader than you think (city + nearby ZIPs), then tighten after you see where leads come from.
- Build warm audiences: website visitors (last 30 and 180 days), video viewers, IG/FB engagers, and past lead form openers.
- Set exclusions: existing customers, recent leads, staff, and anyone who already booked.
- Run two cold audiences: one broad (location only) and one interest-based. Let results decide.
- Use 2 to 4 ad variations per audience. Targeting is only half the job, creative does heavy lifting.
- Review lead quality weekly, not just cost per lead. If you track booked appointments, you can optimize for what pays the bills.
When you want to tighten performance, track a few simple numbers consistently (cost per qualified lead, booked rate, and cost per booking). This list of SEO metrics to track is built for organic, but the same idea applies: fewer metrics, tied to revenue, beats dashboards full of noise. If you want us to map audiences for your exact service area and set up retargeting the right way, pairing paid social with ongoing social media management often improves both conversion rates and ad costs because your profile looks active and credible when people click through.
