Can an Insurance Agency Copy Competitor Ads From the Meta Ads Library the Way E-commerce Brands Do?

An independent agency owner opens the Meta Ads Library, types in the digital agency that keeps outbidding them on auto quotes, and sees every ad that competitor currently has running. Images. Headlines. Launch dates. Free.

Then comes the real question: which of those ads produced a bound policy? The library does not say. In insurance, that blind spot costs more than it does in retail.

Can an insurance agency copy competitor ads from the Meta Ads Library?

Yes, and the library is free, but the workflow does not transfer intact. E-commerce brands validate a copied ad against revenue in days. An agency validates it against bound policies weeks or months later, after underwriting. You can copy format and structure. You cannot copy performance, because performance is not visible.

Sam Piliero, who walks through the workflow his team uses at The Moonlighters, names that limit in the opening stretch of the video: "The main problem is you can't actually see which of these ads are driving real revenue for the business, and therefore you don't know what to recreate for your own brand."

Two more frictions hit an agency specifically:

• A retail brand copying a competitor risks a wasted week of spend. An agency that copies a competitor's savings or coverage language inherits a claim it cannot substantiate from its own book. That is a compliance exposure, not a media test.
• Watermarks get in the way. Working through his own example brand, Piliero says "everything says protected", that this makes the image hard to drop into an AI tool, and that Claude and ChatGPT will often refuse to do anything with a file carrying that watermark. That is what he saw in his example, on an apparel brand. Check whether the listings you pull behave the same way.

Which advertisers should an insurance agency study in the Ads Library?

Not the national carriers. A carrier buying television-scale brand advertising is usually paying for recall, not quote starts. The more useful comparison set is agencies close to your size and licensing footprint, digital-first agencies selling the same lines, and lead generation ads from outside insurance that ask for a commitment the size of a quote form.

The sorting step from the video does carry over. Piliero filters to active ads and sorts by impressions from high to low, which he reads as showing which ads have been active the longest. His reasoning: "every single time we have a high-performing ad, we don't pause that ad". That is his interpretation of the sort, not documented behaviour of the library, so treat longevity as a hint rather than proof. An ad a competing agency has run for months is a signal worth studying. An ad launched last Tuesday is not.

Where to look, in order:

1. Agencies in your state running the same line, sorted by how long each ad has been live.
2. Agencies in states you are not licensed in, which removes the fear of tipping off a direct rival.
3. Non-insurance lead forms with a comparable ask, like mortgage pre-qualification or a tax consultation.

What counts as a winning ad when an insurance lead is not a sale?

Return on ad spend does not exist at the moment an insurance lead arrives. There is no revenue event on the thank-you page. A winner in an agency account is better defined by cost per contactable quote, quote-to-bind rate traced back to the specific ad, and the line of business the lead landed in.

The video's own threshold shows the mismatch. The prompt Piliero writes for the AI defines the target this way: "the definition of a winner in my ad account is above a 2x return on ad spend and has spent more than $5,000 over the last 30 days". Plug that into an agency account and nothing qualifies, because the ad platform never sees the commission.

One piece does port cleanly. In the manual version of his method, he picks candidates by spend concentration: "If you need to define this, think of it as a total of 5% of the campaign value coming out of this single ad." That is a delivery signal rather than a revenue signal, so it survives the absence of a purchase event.

Measure your own lag before you copy anyone's window. If your auto quotes bind in days and your commercial quotes take weeks, one lookback period cannot serve both. The numbers for that comparison are in your management system, not in this article and not in the video.

What has to be checked before an AI-generated insurance ad goes live?

Everything a generative tool rewrote. When you hand an AI a competitor's ad and ask it to swap the branding and write new headlines, it can also introduce claims nobody at your agency underwrote. Piliero's own test run produced an ad he called "very okay" and off-brand. In insurance, off-brand is the smaller problem.

His complaint was that the output had no flavour and did not sound like the brand. The checklist below is not his and is not in the video. It is this article's own reasoning, and it is not legal advice.

Check each generated asset against:

• The insurance advertising rules that apply where you are licensed. What must be displayed, and what may be called a quote rather than an offer, is set by rule and not by whatever a competitor's ad happens to do. Confirm the current requirements with your department of insurance or your compliance counsel.
• Your carrier agreement. Logo use, co-op marketing terms and pre-approval requirements sit in your appointment paperwork. A competitor using a carrier mark does not mean you may.
• Savings and coverage language. Any number an AI invents about premiums, discounts or what a policy covers is a claim you have to substantiate.
• Meta's current advertising policies. Read the live policy documentation for your specific offer, including any restricted or special category rules that may apply to it. The Ads Library shows creative. It does not show what restrictions applied to the account that ran it.
• Faces and testimonials. An AI-generated person presented as a satisfied policyholder is a fabricated testimonial.

How many new creatives can an insurance agency actually handle?

Fewer than an e-commerce brand, and the ceiling is not the ad budget. It is producer capacity. A home run in retail is a spike in orders. A home run in an agency is a spike in leads that a licensed producer has to call back while they are still warm.

Piliero's reason for high volume is explicit: "a lot of ads increases my chance of actually hitting a home run". That logic assumes the winner pays off the moment it lands. An agency pays for the miss twice, once in spend and once in the leads that went cold in the queue.

Before scaling creative volume, work out your own numbers:

• How many leads your team contacts within the hour today, and how many of those bind.
• What happened to that bind rate the last time volume doubled, from your own busy month.
• Which lines you actually want more of, since a flood of minimum-limit auto is not a flood of commercial.

If a two-producer agency cannot work more leads this quarter, more creative variations do not help. Better creative aimed at a narrower line does.

Which tools can an insurance agency use to research competitor ads and build creative?

No single tool covers competitor research, creative production, delivery and insurance compliance review, so most agencies end up combining three or four. The table below lists what each one does, what it solves for an agency, and whether it assumes you already know how advertising works. It is a list, not a ranking.

Disclosure: SaleADS.ai is the product of the company that publishes this site. It is listed here as one option among the others, with its limits stated in the same column as everyone else's.

The Ads Library row reflects what the video shows. The other rows are this article's own description of each product's stated purpose. No product here was tested, scored or ranked, and no prices, star ratings or benchmark figures appear, because none were measured.

Where does the method in this article come from?

From one source video and from this article's own analysis. The competitive research method comes from the video "Claude + Meta Ads Library = Unlimited Winning Ad Creatives" by Sam Piliero, fourteen minutes, 35,734 views. Everything specific to insurance here is this article's own reasoning, not the video's, and not legal advice.

Link: https://www.youtube.com/watch?v=B7z0vcKS67k

Taken from the video: the Ads Library sorting step, the observation that revenue is not visible in the library, the protected-watermark problem, the creative fatigue warning, the spend concentration rule and the winner-definition prompt with its return on ad spend threshold. Piliero's examples are e-commerce apparel brands.

Not from the video, and this article's own work: the translation to insurance lead generation, the substitute winner definitions, the compliance checkpoints, the producer capacity ceiling and every row of the tool table except the Ads Library row.

Worth knowing about the source: a large part of the video is a demonstration of a commercial product called SuperScale, which the presenter says he and his team use for their brands and helped build a feature inside. What is claimed there about that product is his claim, not verified here, which is why SuperScale is not listed in the tool table above.

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Quotes used, for verification against the transcript

Every timestamp above is the start of the transcript block in which the quoted words appear. The transcript is segmented by block, so no finer position is claimed. The only figures in this article that sit outside a quotation are the video's length and view count, taken from the source file header. No third-party statistic and no industry benchmark was introduced.