There are two honest ways to put your ad in front of the right person: pay attention to who they are, or pay attention to what they're doing right now. Both work. The skill is knowing when to lean on each — and, increasingly, how to use them together.
Audience targeting: who they are
Audience targeting reaches people based on what you know about them — their interests, past behaviour, or that they're already your customer. Think "people who've bought from us before," "people who put something in a cart and left," or "people who look a lot like our best customers" (that last one is called a lookalike).
It's powerful because it follows the person, not the page. The catch: it depends on data about that person — and the cleanest, most durable source of that data is your own (your customer list, your site visitors), not borrowed third-party data.
Contextual targeting: what they're reading now
Contextual targeting ignores who the person is and looks at where they are. Someone reading an article about marathon training is, in that moment, a great person to show running shoes — no profile required. You match your ad to the content and keywords on the page.
It's having a renaissance for a simple reason: it doesn't need cookies or personal data at all. The signal is the page itself, which is right there in the open.
Third-party cookies — the little trackers that followed people across unrelated sites — are going away. Audience targeting built on them is fading; targeting built on your first-party data and on context is what lasts.
So which should you use?
- Reach a known group (existing customers, cart abandoners)? Lean audience, using your first-party data.
- Launch something new or want brand-safe relevance at scale? Lean contextual — match the moment.
- Privacy-sensitive market or category? Contextual keeps you effective without personal data.
- Want the best of both? You don't have to choose — see below.
Why you don't actually have to choose
The strongest campaigns blend them. You might use contextual to find relevant moments, then layer in audience signals and geography to prioritise the views most likely to pay off — all on one plan. A good DSP lets you mix and match these levers per campaign, and lets the AI decide which combination is working.
That's how adZoic does it: audience, contextual, keyword, geo and retargeting in one place, with machine learning weighing each opportunity. Want to know how it decides? Read how ML values an impression.