Lookalike audiences are one of Meta Ads' most powerful targeting tools. They allow you to find new customers who share characteristics with your existing customers, essentially letting Meta's algorithm do the hard work of finding your best potential new customers across millions of users.
What Is a Lookalike Audience?
A lookalike audience is a targeting option in Meta Ads that identifies users who are statistically similar to a source audience you define. You tell Meta: "Find me people who look like these customers." Meta then analyzes hundreds of data points about your source audience, demographics, interests, behaviors, engagement patterns, and finds other users who match that profile.
What Makes a Good Source Audience?
The quality of your lookalike audience depends entirely on the quality of your source audience. The best source audiences are:
- Your existing customers (upload a list of phone numbers or emails)
- People who completed a valuable action on your website (purchased, submitted a form, clicked WhatsApp)
- Your highest-value customers specifically, not all customers equally
A source audience needs at least 100 people to create a lookalike, but 1,000+ people produces significantly better results because Meta has more data to work with.
How to Use Lookalike Audiences Effectively
Lookalike audiences work best when combined with your strongest creative, since you're targeting cold audiences who don't know your brand yet, the creative needs to quickly communicate your value proposition and generate interest.
A common and effective campaign structure for Saudi businesses is:
- Lookalike audience campaigns to find new customers
- Retargeting campaigns to convert people who showed interest but didn't act
- Customer loyalty campaigns to re-engage existing customers
This three-layer approach maintains a constant flow of new interest, follow-up, and retention. For more on retargeting, see What Is Retargeting and How Does It Work? And for the complete Meta Ads foundation, read How Facebook and Instagram Ads Work.
Source Quality Decides Everything
A lookalike is only as good as the list it copies. Built from everyone who visited your site, it resembles a crowd that includes people who bounced immediately. Built from paying customers, it resembles people worth having.
Rank your available sources by how close they sit to revenue: paying customers first, completed enquiries second, engaged visitors third, all visitors last. Use the highest one that has enough records.
Where the customer list is small, adding a value column, how much each customer spent, lets the platform weight toward the profitable ones, which recovers some of the quality lost to a short list.
Size, Percentage and Geography
The percentage setting controls how closely the audience resembles the source. One percent is the closest match and the smallest reach; ten percent is loose and large.
For a business serving one Saudi city, geography constrains the audience far more than the percentage does. The difference between one and five percent inside a single city is often negligible, so starting broader is usually safe.
For national campaigns the setting matters more. There, starting at one to two percent and widening only if delivery is constrained is the more reliable sequence.
When Lookalikes Underperform
With a thin source list they are close to guesswork. Below roughly a hundred records the resemblance is statistically weak, and results usually match plain broad targeting without the extra complexity.
They also decay. A lookalike built from customers acquired two years ago describes a market that may have moved, and refreshing the source list annually keeps it honest.
And they cannot fix a weak offer. A perfectly constructed audience shown an unconvincing ad produces an efficient delivery of indifference.
Using Them Alongside Everything Else
Lookalikes sit between cold prospecting and retargeting: colder than people who know you, warmer than everyone. They work best as one part of a structure rather than the whole of it.
Exclude your existing customers and site visitors from the lookalike audience, or you will pay prospecting rates to reach people you already had.
Compare their cost per result against plain broad targeting periodically. Meta's automated delivery has improved enough that broad sometimes wins outright, and it costs nothing to check.
Building the Source List You Do Not Have Yet
Most small businesses discover they have no usable source list at the moment they want one. Customer records sit in a phone, in WhatsApp threads, or in an invoicing app nobody exports.
Start collecting now even if you will not advertise for months. A simple record of customer name, phone and value, kept current, becomes the highest-quality targeting asset the business owns.
For Saudi businesses where most contact happens on WhatsApp, this is largely an exercise in exporting what already exists rather than gathering anything new.
A Realistic Sequence for a Small Advertiser
Run broad targeting first while conversion data accumulates, since lookalikes need a source and the source needs customers. Attempting the sophisticated version first usually means building a lookalike from noise.
Once fifty to a hundred customers exist, build the first lookalike and run it against broad targeting as a straight comparison. Keep whichever wins, and re-test quarterly.
Add exclusions from the start rather than later. Excluding existing customers costs nothing and prevents the most common form of wasted prospecting spend.
Lookalikes for Service Businesses
Service businesses often assume lookalikes are for retailers with thousands of transactions. In practice a contractor with two hundred past customers has a better source list than an online shop with ten thousand low-value orders, because the records describe people who paid meaningfully.
Where the service is geographically constrained, the lookalike mostly serves to prioritise within the city rather than to expand beyond it. That is still useful: it front-loads delivery toward the people most likely to respond.
The one adjustment worth making is excluding areas you cannot serve before building the audience, so the resemblance is calculated on people you could actually work for.
What Privacy Changes Did to Lookalikes
Lookalike audiences are less powerful than they were, and understanding why prevents a lot of misdirected effort. Platform tracking across other websites and apps was substantially curtailed by operating system privacy controls, which means the behavioural signal available for matching is thinner than in the period when these audiences earned their reputation. The mechanism still works; the raw material feeding it is poorer.
The practical consequences are consistent. Website-based source audiences built from pixel data are less reliable than they used to be, because a share of visitors is no longer observable. Source lists you own outright, such as customer phone numbers and email addresses, have become comparatively more valuable, since they do not depend on tracking. And broad targeting with strong creative now competes well against carefully built lookalikes in many accounts, which was not true a few years ago.
This reorders what a small advertiser should do. Prioritise collecting first-party data properly, which for most Saudi businesses means capturing phone numbers at the point of sale or enquiry with consent to contact. Set up the conversions API rather than relying on the browser pixel alone, so server-side events fill part of the gap. Then test broad targeting against your lookalike rather than assuming the lookalike wins, and let the result decide. Treat lookalikes as one option among several rather than as the default sophisticated choice they were once considered.
Refreshing the Source and the Audience
A lookalike is a snapshot rather than a living thing, and its quality decays as the source ages. A source list built from customers acquired two years ago describes a business, a price point and a market that may have moved since. Rebuild the audience from a current source every few months rather than leaving one in place indefinitely, and expect the newer version to perform differently rather than identically.
Keep the source itself growing. A customer list that is added to as sales happen, exported and re-uploaded quarterly, produces steadily better audiences than a one-off file uploaded when the account was set up. Where you use website or engagement-based sources, note that they roll forward automatically within their membership window, which makes them lower maintenance but also more sensitive to a quiet trading period.
Test rather than assume the refresh helped. Run the rebuilt audience alongside the existing one for a fortnight on the same creative and compare cost per enquiry, since a new source occasionally performs worse, particularly if the recent customer mix is unrepresentative. Keep whichever wins and rebuild again next quarter. This is a small habit that separates accounts whose targeting improves over time from those quietly running on a two-year-old file.
