Why Meta Only Spends on a Few of Your Ads (Creative Similarity Explained)

You launched 30 ads. Meta spent on 4. That is not a budget bug, a learning phase problem, or bad luck. Meta’s retrieval system grouped most of them into a single entity and gave that group one entry into the auction. Here is how to check whether it is happening to you, and what actually creates a genuinely distinct ad.

Almost every account I look at has some version of this problem. A batch goes live, budget concentrates on two or three ads, and everything else sits at near-zero spend. The usual diagnosis is that the winners are just better.

Sometimes that is true. Increasingly it is not.

What Actually Happens When You Upload 30 Similar Ads

Meta rebuilt its ad retrieval system, and the part that matters here is how it decides which of your ads even enter the auction.

When Andromeda evaluates your ads, it uses computer vision to analyze visual elements, natural language processing to analyze copy, and audio analysis for video ads. If multiple ads score above a similarity threshold across these dimensions, they get collapsed into the same Entity ID.

An Entity ID is one ticket to the auction.

If you upload 30 ads that share the same template, same background, same visual structure with different text overlays, Andromeda collapses them into one Entity ID. One Entity ID = one ticket to the retrieval auction. If that single ticket fails for a particular user segment, your other 29 “different” ads never get a chance. They don’t exist in that auction.

That is the whole mechanism. You are not flooding the system with options. You are doing 50x the work for 1x the opportunity.

The uncomfortable implication: a lot of what teams call creative testing is not testing anything. Four hooks over the same B-roll is one ad wearing four hats.

Where to Check It in Ads Manager

This used to be pure inference. Meta now gives you a partial view.

You get three metrics there:

Top Creative Themes is the fastest read of the three. It sorts your ads into buckets like lifestyle, product-focused, testimonial, humor, social proof, and savings. If most of your budget sits in one bucket, you are clustered on a single branch of the tree and the similarity number is only confirming it.

The thresholds

Meta now exposes a Creative Similarity Score in Ads Manager. When scores exceed 60%, the system collapses similar ads into one Entity ID, and 303 London’s diversity guide recommends keeping the index below 40% across active assets so the system treats each ad as a distinct candidate.

Meta released three new KPIs that offer the first real insight into how the platform perceives creative uniqueness: Creative Similarity, Creative Fatigue, and Entity ID.

Go look at yours before reading further. If it is above 60%, the rest of this post is your diagnosis.

Why Copy Changes Do Not Save You

The most common mistake is assuming that different words mean different ads.

Meta uses advanced computer vision to look past ad creative headline or hook changes, focusing instead on the raw visual DNA of your content. If the algorithm detects significant overlaps in composition or style, it consolidates your ads into a single “Entity ID.” Even if the script changes, Meta may still see them as the same.

So the following almost certainly do not produce new entities:

• New headline over the same hero image
• New primary text on the same video
• Same template, different colour
• Same footage, different caption style
• Same talent, same setting, same framing, different script

The diversity needs to register at the visual, audio, and structural level the model is actually parsing.

What Actually Creates a Distinct Ad

Meta organises creative hierarchically. Andromeda organizes ads into a hierarchical tree: top-level themes (social proof, product-focused, lifestyle, humor), mid-level execution patterns (direct-to-camera, split-screen, animation, UGC), and individual creatives at the leaves. To be classified as a diverse creative pool, your 20-some ads need to land across different branches of that tree, not cluster on a single branch.

That gives you a practical way to plan a batch. Vary along these axes, not along copy:

How Many Ads, Really

Volume is genuinely part of this now, but only distinct volume.

Brands testing 20+ new ads per month are seeing 65% higher ROAS than brands testing under 10. The top-performing advertisers run roughly 395 live ads versus 296 for the bottom third.

But the caveat is the whole point:

Volume without diversity is counterproductive. Andromeda clusters similar-looking ads into a single entity, so 395 ads that all look the same perform no better than 10.

A workable target that shows up repeatedly: build 8 to 12 conceptually distinct ad concepts per campaign (different hooks, formats, emotional triggers, visual treatments) and then use Meta’s AI tools or your own production to spin variations.

There is also a structural finding worth knowing: one ad set with 25 diverse creatives generates 17% more conversions at 16% lower cost than five ad sets with five creatives each. Consolidating rather than fragmenting gives the system a wider pool to retrieve from.

Making Ten Concepts Without Ten Shoots

The obvious objection to everything above is cost. Ten distinct concepts with two or three variations each is thirty assets, and nobody is booking thirty shoots a quarter.

This is where generative video earns its place, and where most people immediately misuse it.

I use Higgsfield for this, generating stills with Seedream and animating them with Seedance. The full workflow is in the AI UGC guide, but the short version is that you write the scene, generate stills, pick the one that looks right, and animate that still with a motion prompt. Prompting video from scratch gives you no control over what the scene actually looks like.

Do not generate the whole video. Keep at least 60% of every ad as real footage. Use AI for the opening two seconds, for a location you cannot get to, for a seasonal setup you cannot shoot in the current season, and for texture B-roll nobody will study. Shoot the product, shoot the faces making your actual claim, and shoot anything a customer will look at closely.

The reason is the same argument this whole post is built on. If you generate thirty clips from one model with one prompt style, you have reproduced the exact problem: visually consistent output that the retrieval system reads as one thing. The tool changed, the mistake did not. AI video expands how many genuinely different scenes you can afford. It does not excuse you from making them different.

Used that way, generating ideas is the cheap part. You can mock up eight openings in an afternoon, see which ones look distinct in a grid, and only shoot around the ones that survive.

Refresh Cadence, Because Fatigue Got Worse

The second-order effect nobody warns you about.

Andromeda also introduced severe ad fatigue. Where previously relaunching campaigns or swapping hooks could reset performance, the new algorithm quickly degrades ads with repeated messaging. The old reset trick, duplicate the campaign and relaunch, does not work the way it used to.

The cadence most practitioners are landing on: The 50/30/20 creative refresh model (50% new concepts, 30% refined variants, 20% proven performers) balances exploration with stability on a 2 to 3 week cycle.

A Diagnostic You Can Run This Week

Six steps, in order.

1. Open Analyze & Report → Ads Reporting → Account Insights. Check the Creative Similarity Score and the Top Creative Themes split. Anything over 60% similarity, or most of your budget in one theme, is your answer.
2. Screenshot the first frame of every live ad and lay them out in a grid. Count how many visually distinct groups you actually have. That number, not your ad count, is roughly what Meta sees.
3. Check spend distribution. If 80% of budget sits on under 20% of ads and the rest are near zero, that is consolidation, not a preference.
4. Look at your last “hook test.” Did the variants share footage? If yes, it was not a test.
5. Count real concepts, not ads. Aim for 8 to 12 distinct ones per campaign.
6. Check signal quality while you are in there. Clean conversion signal quality (Pixel and CAPI running simultaneously, Event Match Quality above 7) is the other half of this, because the retrieval system is only as good as the events you feed it.

What This Changes About Testing

The old model was narrow audiences plus many small creative variations. That model is obsolete.

The old strategy was: Narrow Targeting + High Volume of Similar Creatives. The Meta Andromeda strategy is: Broad Targeting + High Diversity of Entity IDs.

Two consequences worth sitting with.

Creative is the targeting layer now. Interest-based settings are either unavailable or far less influential. As a result, creative controls the targeting: advertisements are delivered to users who respond to the message rather than those in a narrow demographic group. You choose your audience by what you make, not by what you tick.

Your test design has to change. If you want to know whether a question hook beats a bold-claim hook, the two versions cannot share footage, or you will get one entity and a meaningless read. Test the variable, but rebuild everything around it enough that the system treats them as separate.

I wrote more about the mechanics of the ranking change in my post on Meta’s Andromeda system, and the practical scaling side in the 2026 Shopify Meta Ads scaling guide. If your creative is fatiguing faster than you can replace it, fixing ad fatigue covers that separately.

The Short Version

Meta is not ignoring your ads. It grouped them.

Similar creative collapses into one Entity ID, one Entity ID gets one entry into the retrieval auction, and everything underneath it competes for the same slot instead of expanding your reach. Copy changes do not break the grouping. Visual, audio and structural difference does.

Check your Creative Similarity Score, keep it under 40%, build 8 to 12 genuinely distinct concepts rather than 30 variants of two, and refresh on a two to three week cycle.

And stop calling it a hook test if all four versions share the same footage.

I’m Nikhil Sharma. I run data and operations engineering for a DTC brand and write about the unglamorous parts of ecommerce that actually move margin. If you want a second pair of eyes on your ad account or creative pipeline, book a consultation.

Nikhil Sharma

I run data and operations for a DTC brand on Shopify, consult on Meta and Google Ads, and build AI automations for ecommerce teams. I write about what I build and run.

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