The Meta Ads Library gives you free access to every ad your competitors are running. You can see the images, videos, copy, launch dates, and whether each ad is active.
That sounds like everything you need for competitive creative research. It is not.
The Ads Library does not show revenue, return on ad spend, or how much money is behind an ad. It gives you the creative without telling you what is actually working.
For years, using that information required a slow manual process. AI and SuperScale have created a much faster way to do it.
The old way: fb ads library
The traditional workflow starts inside the Meta Ads Library.
Search for a direct competitor, filter for active ads, and sort by impressions from high to low. Ads that have been active for a long time are usually the best place to start because brands tend to keep successful ads running.
But longevity is only a clue. You still cannot see whether the ad is profitable, how much it has spent, or whether it is beginning to fatigue.
From there, you manually choose an ad, save the creative, upload it into Claude, ChatGPT, or another AI tool, add your product, explain your branding, and ask the tool to recreate it.
This can work, but it creates four problems:
- You need to know the right competitors to research.
- You are guessing which of their ads are producing revenue.
- Each ad requires a separate manual workflow.
- The output often looks generic or off-brand without several rounds of prompting.
You can spend a lot of time recreating an ad that may already be losing performance for the original advertiser.
The new way: automate the research before generating creative
The newer workflow starts with the same public information, but removes most of the manual work.
Inside SuperScale, we create a competitive set for the brand. The platform tracks the ads those businesses are running and lets us recreate a relevant concept for a specific product without downloading files and rebuilding every prompt from scratch.
The important difference is not simply faster image generation. It is having the research, brand context, products, and creative workflow connected in one place.
Instead of opening dozens of browser tabs and copying ads individually, we can move directly from a competitor concept to an on-brand variation.
Market trends crush
Only watching direct competitors can keep a brand trapped inside the same ideas as everyone else in its category.
The Ad Trends workflow looks across the wider market to identify formats and themes that are rising across many advertisers.
This lets us find a format working in another category, apply it to our own product, and move before every direct competitor is using it.
We want inspiration from what is rising, not what is already fatigued.
FLYWHEEL
The final step is the most important.
Competitor ads and market trends provide new directions, but the brand’s own ad account provides real performance data.
We define a winner using both spend and return. Then AI can locate the ads that meet those thresholds and produce new iterations using current market trends.
That is the difference between the two workflows.
The old way helps you manually copy individual ads based on educated guesses.
The new way combines competitor research, live market trends, brand context, product information, and actual account winners into one creative loop.
The goal is not to copy competitors faster. It is to turn all the available signals into a repeatable system for producing more relevant creative at scale.
Want access to all of Sam’s best performing creatives in every category?
