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How to Use Audience Expansion and Lookalike Audiences on LinkedIn
How to Use Audience Expansion and Lookalike Audiences on LinkedIn
Audience expansion and lookalike audiences let you reach more people similar to a source audience — extending beyond the exact audience you defined to people who resemble them, or building an audience modeled on your best customers. This is useful when you need more reach and your core audience is too small, or when you want to find new good-fit people who look like your best ones. But there’s a trade-off: expanded and lookalike audiences are less precise than your carefully defined audience, because you’re reaching people who are merely similar rather than exactly matching your criteria — so you gain reach at some cost to precision. This guide covers how to use audience expansion and lookalikes, and how to manage the trade-off.
Key takeaways
- Audience expansion and lookalikes reach more people similar to a source audience.
- Useful when you need more reach and your core audience is too small, or to find new good-fit people.
- The trade-off: expanded audiences are less precise than your defined audience.
- You gain reach but lose some precision — reaching “similar” people, not exact matches.
- Monitor quality and don’t over-expand — watch whether the expanded audience converts.
What are audience expansion and lookalikes?
Ways to reach people similar to a source audience, beyond the exact audience you defined. Audience expansion broadens your targeting to include people similar to those in your defined audience — so alongside the exact audience you specified, your ads also reach people who resemble them. Lookalike audiences build a new audience modeled on a source, like your customer list or best-performing audience — finding people who look like your best customers or your existing good audience. Both take a source (your defined audience, your customers) and extend reach to similar people.
The purpose of both is to reach more good-fit people by leveraging what you already know works. If a defined audience or a customer list represents good-fit people, then people similar to them are plausibly also good-fit, so expanding to or modeling on them extends your reach toward more people who resemble your best. This is valuable for scaling reach beyond your exact audience while still aiming at people who look like the ones you want. Understanding that expansion and lookalikes reach similar-but-not-identical people is the basis for using them well and managing their trade-off.
What’s the trade-off?
You gain reach but lose some precision, because “similar” isn’t “exact.” Your carefully defined audience is precise — it’s exactly the people matching your criteria. When you expand to similar people or build a lookalike, you’re reaching people who resemble your source but don’t necessarily match your exact criteria, so the audience is broader but less precisely targeted. This is the fundamental trade-off: expansion and lookalikes increase your reach by including similar people, but that inclusion dilutes the precision of reaching only your exact defined audience.
| Defined audience | Expanded / lookalike | |
|---|---|---|
| Precision | High — exact criteria | Lower — similar people |
| Reach | Limited to the defined set | Broader, more people |
| Fit | Exactly your criteria | Plausibly similar |
| Best for | Precise targeting | Scaling reach |
Whether the trade-off is worth it depends on your need. If your defined audience is large enough and precision is paramount, you may not need expansion. If your core audience is too small to deliver the reach you need, or you want to find new good-fit people beyond it, expansion and lookalikes extend your reach toward similar people — accepting some loss of precision for the gain in reach. Managing the trade-off means using expansion when you need the reach, while recognizing you’re trading some precision for it.
How do you manage expansion and lookalikes?
By monitoring quality and not over-expanding. Because expanded and lookalike audiences are less precise, the key is to watch whether they’re actually delivering good-fit people who convert — monitoring the quality of the expanded audience’s results, not just the added reach. If the expanded audience is converting well, the similar people are proving to be good-fit, and the expansion is working; if it’s converting poorly, the similar people aren’t as good-fit as hoped, and you’re gaining reach at too much cost to quality.
This means expansion isn’t set-and-forget: you use it to gain reach, then check whether the added reach is quality reach, and adjust — expanding more if it’s working, pulling back if the expanded audience underperforms. Don’t over-expand blindly, since expanding too far reaches people less and less similar to your source, diluting fit further. The disciplined use of expansion and lookalikes is to extend reach toward similar people when you need it, monitor whether those people are converting, and balance the reach gained against the precision lost, so you’re scaling toward good-fit people rather than just inflating reach with poorly-fitting ones.
The expansion framework
Use audience expansion and lookalikes deliberately:
- Use them for reach — when your core audience is too small or you want new good-fit people.
- Understand the trade-off — you gain reach but lose some precision reaching similar-not-exact people.
- Model on good sources — expand from or build lookalikes of your best audiences and customers.
- Monitor quality — watch whether the expanded audience actually converts, not just the added reach.
- Don’t over-expand — expanding too far reaches less-similar people, diluting fit; pull back if quality drops.
When should you use expansion versus a precise audience?
Use a precise audience when precision matters and your audience is large enough; use expansion when you need more reach and can accept some precision loss. The choice comes down to your priority: if reaching exactly the right people is paramount and your defined audience delivers enough reach, a precise audience serves you best, since it targets exactly your criteria without dilution. But if your precise audience is too small to deliver the reach or results you need, or you want to discover new good-fit people beyond your exact criteria, expansion and lookalikes extend your reach toward similar people, accepting some precision loss for the reach gain. This is a reach-versus-precision decision, and neither is universally right — it depends on whether your constraint is reach (favoring expansion) or fit (favoring precision). This connects to the broader theme of balancing reach and precision in targeting: a very precise audience maximizes fit but may limit reach, while expansion maximizes reach but dilutes fit, so you choose based on which you need more, and you can monitor and adjust as you see whether expanded audiences deliver quality. Using expansion and lookalikes well means deploying them when reach is the constraint, modeling on good sources so the similar people are plausibly good-fit, and monitoring quality so you’re extending toward good-fit people rather than just broadening indiscriminately — a deliberate reach-precision balance rather than a default toward either maximum precision or maximum reach.
Frequently Asked Questions
Q1. How do you use audience expansion and lookalikes on LinkedIn?
Use them to reach more people similar to a source audience when your core audience is too small or you want new good-fit people, modeling on your best audiences or customers. Understand you gain reach but lose some precision, since you’re reaching similar-not-exact people. Monitor whether the expanded audience actually converts, and don’t over-expand, pulling back if quality drops.
Q2. What are audience expansion and lookalike audiences?
Audience expansion broadens your targeting to include people similar to your defined audience, so your ads also reach people who resemble them. Lookalike audiences build a new audience modeled on a source, like your customer list, finding people who look like your best customers. Both extend reach to similar people, leveraging what you know works to reach more plausibly good-fit people.
Q3. What’s the trade-off of audience expansion?
You gain reach but lose some precision, because “similar” isn’t “exact.” Your defined audience precisely matches your criteria, but expanded and lookalike audiences reach people who resemble your source without necessarily matching exactly, so they’re broader but less precisely targeted. Expansion increases reach by including similar people, which dilutes the precision of reaching only your exact defined audience.
Q4. When should you use audience expansion?
When you need more reach and your core audience is too small to deliver it, or when you want to find new good-fit people beyond your exact criteria. If your defined audience is large enough and precision is paramount, you may not need expansion. Use it when reach is the constraint, accepting some precision loss for the reach gain, and monitor whether the expanded audience delivers quality.
Q5. Are lookalike audiences less precise?
Yes — lookalike audiences reach people who resemble your source (like your customers) but don’t necessarily match exact criteria, so they’re less precise than a carefully defined audience. This is the trade-off: you gain reach toward plausibly good-fit similar people, but lose the precision of targeting only exact matches. Whether it’s worth it depends on whether you need the added reach more than maximum precision.
Q6. How do you know if expansion is working?
Monitor the quality of the expanded audience’s results — whether it’s delivering good-fit people who convert, not just added reach. If the expanded audience converts well, the similar people are proving good-fit and the expansion is working; if it converts poorly, they’re not as good-fit as hoped, and you’re gaining reach at too much cost to quality. Adjust based on this — expand more if it works, pull back if not.
Q7. Can you over-expand an audience?
Yes — expanding too far reaches people less and less similar to your source, diluting fit further, so you gain reach at increasing cost to quality. Expansion isn’t set-and-forget; you should monitor whether the expanded audience converts and pull back if it underperforms. Over-expanding blindly inflates reach with poorly-fitting people, so disciplined expansion balances the reach gained against the precision lost.
Q8. Should you use a precise audience or expansion?
It depends on your priority. Use a precise audience when reaching exactly the right people is paramount and your audience is large enough, since it targets your exact criteria without dilution. Use expansion when your precise audience is too small for the reach you need, or you want new good-fit people, accepting some precision loss for reach. It’s a reach-versus-precision decision based on which you need more.
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