Every brand running paid Instagram or Facebook ads has marketing budget right now. Here's how to surface them, filter by your niche and country, and pitch before competitors do.
*Every brand running paid Instagram or Facebook ads has marketing budget right now. Here's how to surface them, filter by your niche and country, and pitch before your competitors do.*
Ask any creator how they find brands to pitch and you'll get one of three answers. They scroll through similar creators' feeds looking for #ad posts. They check influencer marketing platforms for posted campaigns. Or, most commonly, they wait for brands to find them.
All three approaches share the same fundamental limitation: they only surface brands that have already chosen their creator partner, or platforms that match you to whatever the brand happens to be running this week. You're always second in line. By the time a brand's deal with another creator is visible enough to track, the brand is mid-campaign and probably not looking for another partner.
There's a category of brand discovery that almost no creator does well: finding brands with active ad spend who haven't picked their next creator yet. These brands have already proven three things — they have marketing budget, they're willing to spend it on Meta platforms, and they're actively in-market right now. The only question is whether you reach them before someone else does.
The data source for this discovery has existed since 2019. It's called the Meta Ad Library, and it's free, public, and almost completely unused by creators. This post is about why it matters and how to use it without losing your weekend to manual scrolling.
The Meta Ad Library is a transparency tool Meta launched in response to regulatory pressure around political advertising. It expanded to cover every active ad on Facebook and Instagram — not just political ads. Today, if a brand is running paid ads on either platform, those ads appear in the library within roughly 24 hours of launch, alongside metadata about the advertiser.
You can search it directly at facebook.com/ads/library. Pick a country, search for an advertiser by name, and you'll see every ad they're currently running. You can also search by keyword to find advertisers in a topic area.
The library is built for journalists, regulators, and researchers — not for creators. It assumes you already know which brand you want to investigate. For creator-side brand discovery, the workflow is inverted: you don't know which brands you want, you want the library to surface them based on niche and geography. That's where the library becomes useful and where the manual workflow becomes painful.
Not every brand with marketing budget pays creators. But every brand running consistent paid ads on Instagram and Facebook is doing three things that strongly correlate with creator partnerships.
First, they have an established marketing function. Someone at the brand has approved an ad budget, set up Meta Ads Manager, and is actively reporting on performance. That same function almost always includes influencer marketing as a line item, even if it's a small one.
Second, they're spending money to reach audiences on the exact platforms where you publish. A brand running Instagram ads has decided their customer is on Instagram. The cheapest way to test new creative angles and tap into pre-built audiences is to work with creators whose followers match that target. Sponsored content is often a more efficient version of what their paid ads are already trying to do.
Third, they're under pressure to find content that performs. Paid ads burn out quickly — creative fatigue sets in within weeks. Brands are constantly hunting for fresh angles, formats, and faces. A well-pitched creator with audience overlap is an obvious solution to a problem the marketing team already has.
Compare this to a brand with no paid ad spend. They might still work with creators, but you have no signal that they have budget, no signal that they value social as a channel, and no signal of urgency. Ad spend is the closest thing to a public buying signal a brand will ever give you.
Here's what manually using the Meta Ad Library for brand discovery looks like in practice.
You go to the ad library and set a country filter. You search a keyword for your niche — say, "skincare" if you're a beauty creator. You scroll through results, which are returned as individual ads, not as advertisers. So a single brand running 12 ads shows up as 12 entries, mixed in with every other brand running skincare ads. You manually note the advertiser names, deduplicate, and try to assess which ones look like real businesses versus dropshippers.
Then you check each advertiser's Instagram profile. Do they tag creators? Do they have an ambassador program? Are their existing partnerships with creators at your size? You write a pitch tailored to each one. Then you send it.
If you do this thoroughly, it takes four to six hours to surface maybe twenty qualified brands and send twenty pitches. The information decays fast — within a week or two, the ads you scraped may have rotated, the brand may have already picked a creator, or new entrants may have appeared. The workflow doesn't scale, and most creators give up within a week of trying it.
This is the gap that automated tools fill. The data is public. The methodology is well understood. What's missing is the filtering, deduplication, and prioritization that turn the raw ad library into a usable list.
When you automate Meta Ad Library scraping for creator brand discovery, you're solving five specific problems.
The raw library returns ads, not brands. A clean workflow groups ads by advertiser so a brand running 20 ads shows up once, with an ad count attached. That count is itself a signal — a brand running 20 active ads is investing meaningfully in paid media and is far more likely to have a creator budget than a brand running one.
Keyword search in the library is brittle. "Skincare" returns acne products, sunscreen, anti-aging serums, and luxury brands. A creator focused on clean beauty for sensitive skin doesn't want to pitch any random skincare brand — they want the ones whose products actually fit their content. Automated niche filtering uses brand metadata, product category, and creative content to narrow the list to brands you'd realistically partner with.
Most creators have geographically concentrated audiences. A US-based creator with 90% US followers shouldn't waste pitches on UK-only brands whose ads don't even run in their region. Filtering by country at the ad-library level means every brand on your list is one whose customers could realistically be in your audience.
Some brands run perpetual evergreen ads. Some run short bursts around launches and promotions. Brands in launch mode are dramatically better pitch targets — they have campaign budgets, deadlines, and active creative needs. Tracking creative freshness (when did this brand's current ads first appear?) surfaces the brands that just entered an active campaign window.
Once you have a clean, filtered, prioritized list, the bottleneck shifts to outreach. Writing twenty personalized pitches still takes hours. Tools that auto-generate a starting pitch — pulling brand name, product, and your own positioning into a template you can edit — collapse that work from hours to minutes. You're still the one who edits and sends, but you're not starting from a blank page.
This is exactly the workflow OutSponsor's Meta ads radar runs in the background. You pick your niche and country once. The tool pulls the ad library daily, deduplicates by advertiser, scores by ad volume and freshness, and queues a draft pitch for each brand. You review, edit, and send — or skip the ones that don't fit.
Meta ad library discovery is proactive. It surfaces brands with budget who haven't picked a creator yet. It pairs naturally with reactive discovery — watching specific creators in your niche and catching the brands they just worked with.
Reactive discovery answers a different question: which brands have already proven they pay creators at my level, in my niche? When a creator slightly above your size posts a sponsored Reel for a brand, that brand has just shown they have an active creator partnership budget, they value your content category, and their audience targeting matches yours. The pitch is almost pre-written: "I saw your collaboration with [creator] and noticed [specific thing about it]. My audience overlaps with theirs in [specific way], and I'd love to discuss a follow-up campaign."
Run both in parallel and you cover both sides of brand discovery: brands with active ad spend who haven't found a creator yet (proactive), and brands who just paid a creator like you (reactive). Most creators run neither systematically. The few who run both tend to be the ones with consistent monthly sponsorship income.
A pitch to a brand you found through ad-library discovery is structurally different from a generic cold pitch. You have a specific data point — they're running ads — and you should use it without sounding like you scraped them.
The hook references their current campaign. "I've been seeing your campaign for [product] in my feed and noticed you're leaning into [angle]. That positioning lines up well with how my audience already talks about this category."
The bridge connects your audience to their paid-media targeting. If they're running ads to a demographic, your audience probably overlaps. Reference your own audience demographics (US women 25–34, fitness-curious, etc.) and frame your follower count as a sample of that demographic.
The idea is a creator-led version of their existing creative. "Your ads test [angle X]. I'd love to make a Reel that tests the same angle but in a [your-format] context. If it performs, it's a creative variant you can amplify with paid spend." This positions you as an extension of their paid-media strategy, not a separate marketing line item.
The proof point is selective: one or two metrics that map to what their ads are trying to drive. If their ads have a strong conversion-style CTA, lead with link-click or save data. If they're brand-awareness ads, lead with reach and engagement.
The close is low-friction: "Would you be open to a quick one-pager with a few concepts and rates?" Don't ask for a call. Don't attach your media kit. Just open the door.
The biggest mistake is treating an ad-library list as a high-volume cold-pitch list. The brands on it are warm leads, not lottery tickets. Sending fifty identical pitches with the brand name swapped in defeats the purpose of finding them through a buying-signal data source.
The second mistake is pitching dropshippers and short-life brands. Some brands in the library are aggregator drop-shops that run high-volume cheap ads with no real marketing function. Their ad volume might be high but their willingness to pay creators is zero. Filter for brand stability — domain age, follower count, content history — before pitching.
The third mistake is ignoring creative freshness. A brand that's been running the same three ads for eight months is in maintenance mode, not campaign mode. They're less likely to have active partnership budget than a brand that just refreshed their creative last week. If your tool surfaces freshness, weight it heavily.
The fourth mistake is country mismatch. A creator with an Italian audience pitching a US-only brand is wasting their best leads. Filter aggressively by geography even if it shrinks your list.
For a decade, creator brand discovery has been a roughly even mix of luck, network effects, and platform-mediated matchmaking. You hoped a brand found you, you hoped a marketplace surfaced a relevant campaign, and you occasionally got lucky with a cold DM.
The Meta Ad Library — and the tools that turn it into a usable creator workflow — represent a structural shift. The data has always been there. What's changing is that creators can now access it at the same level of sophistication that brands have been using for competitive intelligence for years. You can know, in advance, which brands have budget right now, in your niche, in your country, with what creative freshness. That's not a small advantage. It's the same kind of asymmetric information that built every successful sales function in every industry.
If you're a creator at any size with an engaged audience, the brands you'll work with twelve months from now are running ads today. The question is whether you find them this week, this month, or never. The data is public. The workflow is automatable. The pitch is yours to write.
Start with one niche and one country. Pull the list. Send three pitches by the end of the day. Then do it again tomorrow.