You launch a Facebook ad, set a budget, and a few hours later it appears in front of thousands of people.
But who really decides who sees it?
The answer comes down to two words: the Facebook algorithm. Or more precisely, Meta’s advertising system, which chooses in a fraction of a second which ad to show each user.
On 28 October 2026, Meta published a detailed explanation of how it works. It reveals that the biggest budget does not necessarily win, that the experience after the click counts, and that artificial intelligence now does most of the targeting work.
In this article, we break down how the Facebook algorithm works for ads, from Meta Andromeda to the auction system, and above all what you can do to get the most out of it.
How does the Facebook algorithm work for ads?
The principle is simple: the advertiser sets the direction, the Facebook algorithm takes care of the rest.
Your role: defining your strategy, your budget and your objective (sales, leads, app installs).
The role of Meta’s AI: selecting, ranking and recommending the ads to show each person.
To make this choice, the system takes four elements into account:
- where the person is in their buying journey;
- their likelihood to take action;
- the content of your ad itself;
- the experience of your previous buyers.
Your ad then competes with the other eligible ads every time an ad slot becomes available. According to Meta, this process happens hundreds of billions of times a day, across Facebook, Instagram, Threads, Messenger, WhatsApp and Audience Network. It draws on the interests of 3.64 billion people who use at least one of the group’s apps every day.
Performance boosted by AI
Meta states that its advertising system performs significantly better than in 2025:
- Q2 2026: +8.3% clicks and +15.7% conversions on Facebook;
- Q3 2026: nearly +2% additional conversions on certain segments of the Facebook feed.
✅ Good news for advertisers: these improvements apply automatically to all campaigns, with no settings to change.
Meta Andromeda: the first step of the Facebook algorithm
Meta Andromeda is the system that makes the first cut among all available ads. Its role in numbers:
- Tens of millions of ads could potentially be shown to a user;
- Andromeda narrows them down to a few thousand candidates, the ones worth evaluating in detail for that specific person.
The image Meta uses: a personal shopper
Picture a shopper who has thirty seconds to find you the right product.
In the past, they only had time to look at brands you already knew, products similar to your past purchases or the most popular items.
With Andromeda, they can now browse the entire store.
💡 Great news for lesser-known brands. Your product, once “tucked away at the back of the store”, can now be found by the person looking for exactly that kind of thing.
📈 The result: in Q3 2026, improvements to Meta Andromeda increased conversions on Facebook by 1.4%.
⚠️ Key takeaway: if your ad does not pass this first filter, it has no chance of being delivered, whatever your budget.
GEM, sequence learning and Lattice: the other building blocks of the algorithm
Once Andromeda has made its shortlist, other models take over to choose the best ad. Sticking with the personal shopper image, each one plays a very specific role.
GEM: knowing your tastes
GEM (Generative Ads Recommendation Model) is presented by Meta as the industry’s largest foundation model for recommendations. It learns from trillions of signals, then passes its knowledge on to lighter models that choose ads in real time. It is the shopper who knows your style, your size and what you usually buy.
Sequence learning: anticipating what comes next
Sequence learning analyses the order in which a person takes their actions. The example Meta gives says it all: if you have just booked a ski trip and bought boots, the system understands that you are more likely to need a ski jacket than a second pair of boots.
Lattice: connecting everything
Meta Lattice brings it all together into a single ranking system. Rather than using a separate model for each advertising objective and each app, it learns across all of them. It is, in a way, the shopper’s brain, piecing all the information together to decide what you might buy next.
Finally, in Q2 2026 Meta introduced GenRecs, a model that relies on large language models (LLMs) to match ad content with user preferences.
The Facebook auction: why the biggest budget does not always win
Before each impression, your ad takes part in a real-time auction against the other eligible ads. Contrary to popular belief, the advertiser who pays the most does not automatically win. Meta looks for a balance between three parties: users, who should see relevant ads, advertisers, who need results, and the overall quality of the platform.
The Facebook algorithm relies on three main criteria:
1️⃣ Your bid. This is the amount you are willing to pay for the opportunity. Meta converts your budget and objectives into a bid for each impression, adjusted continuously according to market conditions. This is known as pacing.
2️⃣ Ad quality. It covers the whole experience, from the ad itself to what happens after the click. Meta takes user feedback into account (clicks, hiding the ad), detects low-quality practices such as engagement bait or withheld information, and draws on more than 200 million customer survey responses every year. These surveys cover satisfaction with purchases, delivery delays, unexpected fees and the feeling of having been misled.
3️⃣ Estimated action rate. This is Meta’s models’ prediction of how likely a person is to take the action you are aiming for.
The result: a more relevant ad, backed by a good customer experience, can beat a higher bid. A complicated checkout, late delivery or absent customer service can therefore directly penalise your campaigns.
Facebook Ads targeting: what the algorithm does for you
For a long time, a successful Facebook campaign relied on very precise targeting. With today’s algorithm, the logic is reversed.
❌ Before: you defined your audience yourself (age, interests, behaviours).
✅ Today: artificial intelligence identifies the people most likely to act, by analysing their behaviour, their preferences and the content of your ad.
In practice, your role is no longer to guess who your ideal customer is, but to give the system enough material to find them. Meta therefore recommends:
- adopting Meta Advantage+ as a whole, rather than feature by feature;
- giving the system room to learn;
- varying your visuals and messages, so the algorithm has more options to test and reaches different profiles.
Facebook Ads targeting is therefore increasingly driven by your ad creatives. According to Meta, the better the system gets at finding the right people, the more results each impression delivers.
Facebook Ads optimisation: the levers you still control
1. Choose the right objective
Aim for the result you actually want, not the metric that is easiest to measure. As Meta points out, a lead is not a sale, and an app install is not a subscriber.
2. Share what each conversion is worth
Tell Meta the value of each conversion, not just the fact that it happened. Delivery will then shift towards your most profitable customers. This is exactly what the Value Optimization and Value Rules features are for.
3. Measure with the right method
Optimise for the measurement you trust: Meta’s standard attribution, your own custom attribution model, or incremental attribution, which only counts conversions that would not have happened without the ad.
Meta's tips for your next campaign
Beyond these three decisions, Meta makes several practical recommendations:
- 🎨 Bet on creative variety: give the system room and feed it with as many different visuals and messages as possible.
- 📊 Steer with the right metrics: judge your campaigns on cost per result or return on ad spend (ROAS).
- 🧪 Test incrementality: run a Conversion Lift or Brand Lift study. Platform results show what happened; these studies show what happened because of your ads.
- 📦 Audit your customer experience: delivery speed, customer service responsiveness, product quality and a smooth checkout directly affect the quality of your ads. Treat them with the same rigour as your creatives.
- 📅 Plan for seasonal peaks: set aside budget for the periods when your customers are most ready to buy, using budget scheduling.
Conclusion: the Facebook algorithm rewards advertisers who send it the right signals
The Facebook algorithm has never been more powerful. But that power does not replace strategy.
What the AI does
With Meta Andromeda, GEM, sequence learning and Lattice, AI now identifies on its own the people most likely to buy. These improvements automatically benefit every campaign.
What holds your results back
- A poorly chosen objective
- Creatives that lack variety
- A disappointing customer experience
What makes the difference
Sending clear signals to the algorithm and taking care of every step of the journey, before and after the click.
Need help with your Meta campaigns?
Our Social Ads experts help you structure your campaigns, set up your conversion signals and produce creatives built for the algorithm.
FAQ - Facebook Algorithm
It is the set of artificial intelligence systems that decide which ad to show each user on Facebook, Instagram and Meta's other apps. It shortlists relevant ads, ranks them, then runs an auction for each ad slot.
Meta Andromeda is the shortlisting system of Meta's advertising algorithm. It narrows tens of millions of ads down to a few thousand candidates for each person, before other models choose the final ad.
No. The Facebook algorithm combines your bid, the quality of your ad (including the experience after the click) and the likelihood that the person takes the intended action. A more relevant ad can beat a higher bid.
Meta recommends giving its system room and adopting Advantage+, with AI identifying the people most likely to act. Your main lever becomes the variety of your creatives and the quality of the signals you send (objective, conversion value).
Choose an objective that matches your real business result, share the value of your conversions, offer varied creatives, and take care of your customer experience, from delivery to after-sales service.
