Every marketing team eventually asks the same question after watching a competitor’s campaign blow up: what are they actually running, and where. Advertising intelligence software exists to answer that specific question, pulling back the curtain on which ads a competitor is running, on which platforms, for roughly how long, and sometimes at roughly what spend.

The honest caveat before the list: none of these tools give you a competitor’s actual budget. They give you observed data, ads that ran, estimated impressions, modeled spend, and the quality of that estimate varies a lot by platform and by how much traffic the tool itself sees. Treat every number below as directional, not exact, and the tools become genuinely useful instead of a source of false confidence.

Seven tools compared

ToolStrengthWeaknessStarting price
Semrush Advertising ResearchPPC keyword and copy insightSteep learning curve$129.95/mo (Pro plan)
SpyFuHistorical keyword data back to 2005US-focused, weak on display$39/mo
Meta Ad LibraryFree, official, every active Meta adNo analytics, manual researchFree
AdbeatDisplay and native network depthEnterprise pricing, display onlyCustom quote
Pathmatics (Sensor Tower)Cross-channel spend estimatesEnterprise pricing, complex UICustom quote
Moat (Oracle)Viewability and brand safety dataOracle ecosystem lock-inEnterprise only
SocialPetaMobile app ad creative libraryNarrow to app marketingCustom quote

1. Semrush Advertising Research

Semrush’s PPC module is the tool most marketing teams already half-own, since it’s bundled into a platform most of them already pay for to run SEO. That bundling is the actual selling point: you’re not adding a new vendor, you’re unlocking a module inside software your team already has logins for. It shows a competitor’s estimated ad copy, the keywords they’re bidding on, and rough traffic estimates for their paid campaigns.

Pros: Comprehensive data that ties directly into the same competitor’s organic search picture. Genuinely strong for keyword-level PPC research. One login instead of two separate subscriptions if your team already runs Semrush for SEO.

Cons: The interface takes real time to learn well, Semrush’s breadth is also its complexity problem. Premium pricing if you’re buying it standalone rather than as part of a bundle you already have.

Best for: Marketing agencies and PPC specialists who want ad intelligence layered on top of SEO data they’re already tracking.

2. SpyFu

SpyFu’s whole pitch is depth over breadth: eighteen-plus years of historical keyword and ad data on US domains, which lets you see not just what a competitor is running today but how their paid strategy has shifted over nearly two decades. For anyone trying to understand a competitor’s long game rather than their current campaign, that history is the actual product.

Pros: Historical depth nobody else on this list matches. Genuinely affordable relative to the enterprise tools further down. Sharp focus on keyword-level PPC research specifically.

Cons: Coverage is US-centric, international competitors are thin. Display and native advertising aren’t the focus, this is a search-ads tool first.

Best for: Search marketers researching a competitor’s paid strategy over years, not just this quarter.

3. Meta Ad Library

Meta’s own Ad Library is the most underrated tool on this list precisely because it’s free and official, straight from the source rather than a third-party estimate. Search any advertiser and see every ad currently running across Facebook and Instagram, full creative, full copy, no guessing involved.

Pros: Completely free, and the data comes directly from Meta rather than a scraped estimate. Every currently active ad is visible, not a sample.

Cons: No analytics layer at all, no spend estimates, no performance data, just the raw creative. Research has to be done manually, one advertiser at a time, with no bulk export.

Best for: A free first pass at understanding exactly what a specific competitor is running on Meta right now.

4. Adbeat

Adbeat specializes narrowly and does that narrow thing well: display and native advertising across ad networks, with publisher-level detail on where a competitor’s creative is actually showing up. If your competitive question is “which publishers is this brand buying banner space on,” Adbeat answers it more precisely than any general-purpose tool.

Pros: Genuine depth on display and native networks that most tools treat as an afterthought. Publisher-level placement data. Creative downloads for swipe-file research.

Cons: Enterprise pricing that puts it out of reach for small teams testing the waters. Covers display and native only, so it’s the wrong tool if your competitor’s real spend is on search or social.

Best for: Media buyers and display-heavy advertisers who need publisher-level placement intelligence.

5. Pathmatics (by Sensor Tower)

Pathmatics, now part of Sensor Tower’s broader market-intelligence suite, covers the widest range of channels on this list. Display and social sit alongside video, all in one dashboard, with spend estimates layered across each. That cross-channel view is genuinely rare, most competitors specialize in one channel and leave you stitching data from three tools to get the same picture.

Pros: A real cross-channel view instead of a single-network snapshot. Spend estimates and creative galleries in one place. Strong for understanding a brand’s overall paid strategy, not just one platform’s slice of it.

Cons: Enterprise pricing, and the platform’s depth means a genuine onboarding period before a team gets full value from it.

Best for: Enterprise marketing teams and agencies that need one dashboard covering a competitor’s full paid-media footprint.

6. Moat

Moat, now under Oracle Data Cloud, brings something the other tools mostly skip: viewability and brand-safety measurement layered on top of competitive ad intelligence. For advertisers who care as much about where their own ads are showing up safely as they do about competitor research, Moat serves both jobs from inside the Oracle ecosystem.

Pros: Viewability data that ties competitive research to actual media-quality measurement. Deep integration for teams already inside Oracle’s advertising stack.

Cons: Enterprise-only, with pricing and access that assumes a large existing Oracle relationship. Not a realistic pick for a team not already in that ecosystem.

Best for: Large enterprise advertisers already running Oracle Data Cloud who want brand safety and competitive intelligence in one place.

7. SocialPeta

SocialPeta zeroes in on a category the general tools handle poorly: mobile app advertising, with a creative library spanning more than seventy ad networks worldwide. For game studios and app publishers specifically, this specialization beats a general-purpose tool’s shallow app-ads coverage.

Pros: Genuine mobile-app specialization with global network coverage. Deep creative library for swipe-file research specific to app install campaigns.

Cons: Narrow focus means it’s the wrong tool entirely outside mobile app marketing. Premium pricing for the depth of coverage it offers.

Best for: Mobile app marketers and game developers researching install-campaign creative across networks.

Free versus paid: where the line actually sits

Meta Ad Library, TikTok’s Creative Center, and Google’s Ads Transparency Center are all free and official. They’re also often the first stop that matters most. Between the three of them, you can manually pull every currently active ad from a specific competitor across the platforms where most consumer ad spend actually lives, without paying anyone a subscription fee.

What the free tools don’t give you is history, aggregation, or estimation. You can’t see what a competitor ran six months ago on Meta unless you happened to screenshot it at the time. You can’t pull fifty competitors’ ads into one spreadsheet without doing it by hand, one search at a time. And you get zero spend estimate, just the raw creative sitting there.

That gap is exactly what the paid tools sell. SpyFu and Semrush add history and keyword-level detail. Adbeat and Pathmatics add spend estimation and cross-competitor aggregation. Whether that gap is worth $39 to several thousand dollars a month depends entirely on how often your team actually needs to answer “what changed” rather than “what’s happening right now,” since the free tools answer the second question perfectly well on their own.

What to actually do with a competitor’s ad

Finding a competitor’s ad is the easy part. Most teams stop there, screenshot it, drop it in a Slack channel, and move on without extracting anything useful. A more disciplined pass asks three questions of every ad worth noting.

What’s the hook in the first three seconds or the first line of copy? That’s usually the single most transferable insight, not the specific offer, but the pattern of what’s grabbing attention right now in your category. Second, how long has this exact creative been running? A tool showing continuous duration for six weeks is signaling a winner the competitor hasn’t rotated out yet, worth studying closely. A creative that appeared and vanished within days probably underperformed and got killed, which is its own useful data point about what doesn’t work.

Third, where does the ad actually send people? The landing page tells you more about a competitor’s current priorities than the ad creative itself usually does, a new landing page often means a new offer, a new price test, or a pivot in positioning that the ad copy alone won’t reveal.

Reading the numbers correctly

The single biggest mistake teams make with ad intelligence data is treating a spend estimate as a fact rather than a model output. Every tool on this list infers spend from observed impressions, ad duration, and platform-specific pricing benchmarks, it’s a calculated guess dressed up in a clean dashboard number, and the accuracy of that guess drops sharply outside the largest ad networks.

Google and Meta get sampled heavily, so estimates there tend to land in a reasonable range. Smaller programmatic networks and regional platforms get sampled far less, and a spend number for a niche network should be read as “this brand is active here” rather than “this brand spent exactly this amount.” Cross-check any number that’s about to inform a real budget decision against a second source before trusting it.

The second mistake is chasing every competitor’s every move. Pick two or three direct competitors and one aspirational one, and watch their creative refresh cadence over a full quarter rather than checking daily. Ad intelligence rewards pattern recognition over time far more than it rewards a single snapshot.

Choosing between the enterprise tools

Adbeat and Pathmatics, along with Moat, all sit behind a sales call rather than a self-serve checkout. The choice between them usually comes down to one question your team already knows the answer to: what channel does the budget actually live in?

If display and native placements are where the real spend sits, Adbeat’s publisher-level detail earns its price. If the question spans several channels at once, social alongside video and display, and leadership wants one number for “total estimated competitor spend,” Pathmatics is built for exactly that ask. Moat only makes sense as an add-on to an existing Oracle relationship, not as a standalone purchase, its viewability data is genuinely valuable but the access model assumes you’re already inside that ecosystem for other reasons.

A useful test before signing a contract with any of the three: ask for a sample report on a competitor your team already knows well. If the estimated spend and creative list roughly match what your team’s own intuition already expected, the tool is calibrated well for your category. If the numbers feel wildly off from what you know to be true, that’s a signal worth taking seriously before committing a budget line to a full year of access.

Building this into an actual workflow

A monthly competitive-ads review, thirty minutes, calendar-blocked, beats an ad-hoc check whenever someone remembers to look. Pull the top three competitors’ current creative, note what’s new versus last month, and flag anything that signals a strategy shift, a new offer, a new audience being tested, a channel they’ve never used before.

Pair the paid-ads picture with organic positioning. A competitor’s Meta Ad Library results plus their current landing pages plus their recent blog content tells a much more complete story than ad data alone, because paid creative is usually the loudest, most polished version of a message the rest of their marketing is also quietly testing.

A note on volatility in this category

Ad intelligence tools have gone through more ownership changes in the past few years than most marketing categories. Pathmatics moved under Sensor Tower. Moat moved under Oracle after starting as an independent measurement company. SocialPeta has expanded well beyond its original scope. Before signing a multi-year contract, check who currently owns the tool and whether the roadmap you’re being sold reflects the current owner’s priorities or a pitch deck that’s a year out of date.

This matters practically, not just as trivia. A tool absorbed into a larger platform sometimes loses standalone pricing and gets folded into a bigger, more expensive suite at renewal. Ask directly during any sales conversation whether standalone access is guaranteed for the length of the contract you’re signing, not just for the current fiscal year.

Ad intelligence works best paired with the rest of a marketing stack rather than sitting alone. For the automation layer that turns competitive insight into actual campaigns, our HubSpot alternatives guide covers the marketing automation options. For the email side of the funnel, see Mailchimp alternatives. And for measuring what actually happens after someone clicks one of these ads, Google Analytics alternatives rounds out the picture.

FAQ

What is digital advertising intelligence software?

Tools that surface a competitor’s paid advertising, which ads they’re running, on which platforms, at roughly what estimated spend, targeting which keywords or audiences. Semrush and SpyFu lead the search side of this category in 2026, with Adbeat and Pathmatics covering the display and cross-channel side. Marketing teams use them to benchmark spend, borrow creative ideas honestly, and catch strategy shifts before a competitor’s campaign fully rolls out.

What is the best ad intelligence software in 2026?

For PPC and keyword-level competitor research, SpyFu and Semrush are the dominant choices. For display and native ad intelligence specifically, Adbeat remains the specialist standard. For a genuine cross-channel view including video and social spend, Pathmatics offers the broadest picture. Most serious teams end up running Semrush or SpyFu alongside one channel specialist.

How accurate is ad intelligence data?

Reasonably accurate for the largest networks, Google, Meta, major programmatic exchanges, where these tools sample heavily and have years of benchmark data to calibrate against. Accuracy drops noticeably for smaller platforms, geo-restricted campaigns, and advertisers running below a certain scale. Treat every number as a directional benchmark, not an exact figure you’d bet a budget decision on without a second source.

How much does ad intelligence software actually cost?

Semrush’s advertising research module is bundled into plans starting at $129.95 a month. SpyFu starts at $39 a month, the cheapest real option on this list. Adbeat and Pathmatics both run custom enterprise pricing, typically thousands of dollars monthly once you’re past a sales call. SocialPeta and Moat sit in similar enterprise territory, priced for teams with real ad budgets to protect.

Is using ad intelligence software ethical?

Yes, these tools observe publicly displayed ads and public traffic signals, not private data anyone had a reasonable expectation of keeping secret. Every ad shown to the public is, by definition, public. The practice is standard across the marketing industry and widely accepted; the data is descriptive of what already happened publicly, not predictive of a competitor’s private internal strategy.