Major ad platforms have come under fire in recent months for allegedly inflating advertisers’ results artificially, increasing costs and generating incorrect data. And it’s not the first time ad platforms have faced these allegations.

Back in 2018, Facebook was served with a lawsuit claiming it had knowingly overestimated the number of users in its ‘potential reach’ metric. Facebook told advertisers it had a potential reach of 230m adults, when census data suggested only 170m adults used Facebook.

More recently, Meta is facing lawsuits claiming they’ve inflated ad viewership figures by up to 400%. LinkedIn, meanwhile, has paid more than $6.6m to settle a proposed lawsuit suggesting they inflated video ad views.

These lawsuits are costing ad platforms huge sums of money (Meta is reportedly being sued for around $7bn). But the outcomes will also have serious implications for accountability within the ad industry as a whole.

So are ad platforms actually overcharging you? And if so, how can you make sure your data is reliable and you’re getting the best results for your ad spend? Here, we’ll look at whether you can really trust your ad platform, plus how to spot ad performance inflation and verify your results.

How trustworthy are ad platforms?

PPC marketers are reliant on ad platforms to generate revenue. But as more platforms are implicated in these lawsuits, it’s time to ask how trustworthy they really are.

In 2024, a US judge ruled that Google illegally monopolized online search by breaking antitrust laws. Google paid several companies more than $26bn to remain the default search engine on mobile devices. They’re now facing a second antitrust lawsuit to determine whether they’ve also unlawfully monopolized digital advertising.

Google is the go-to ad platform, with 98% of PPC marketers based in Europe saying they use Google search advertising. But despite so many users, it’s one of the least trusted ad platforms, with 54% of PPC marketers worldwide saying they trusted it less than other platforms. Only X was ranked lower in terms of user trust.

Current legal issues aside, there are a few other reasons to be wary about trusting major ad networks (and, more importantly, the data they provide). Here’s why:

1. Invalid traffic

Invalid traffic (IVT) is a longstanding problem in the online ad space. Bots and other fake users cause big problems for advertisers: skewing your data, draining your ad spend, and generating fake leads. 

Unfortunately, there’s little incentive for ad networks to tackle the IVT problem. As a result, most ad networks have avoided doing so. Google offers credits if you can prove you’ve been impacted by IVT. But Meta takes no responsibility for the impact of IVT on advertisers at all. Here’s an extract from their advertising terms:

“Facebook shall have no liability for click fraud or other improper actions, or for invalid clicks or other technological issues, each of which may affect the cost of advertising.”

‍Since most ad networks aren’t prepared to clamp down on IVT, it’s understandable that many advertisers are wary of placing too much trust in them. Especially when more ad platforms are taking control away from advertisers via automated black box platforms like Google’s Performance Max.

2. Attribution bias

Perhaps unsurprisingly, most ad platforms are biased when it comes to attributing conversions in PPC. Ad platform bias happens when one platform takes full credit for a conversion, disregarding any other marketing touchpoints that helped generate the purchase. This often means a platform will inflate its own success.

As a result, it’s hard to rely on attribution reports from one specific ad network, especially if you advertise across multiple channels. But unifying data from multiple sources comes with its own challenges — namely, which data you should trust.

3. Privacy regulations

With the advent of GDPR and other sweeping data protection developments in recent years, user privacy is critical. Most browsers now block cross-site tracking and limit first-party cookie lifespans, preventing user tracking. 

This makes it much harder to correctly attribute each touchpoint, especially if you’re dealing with a longer sales cycle. While ad networks are (rightly) compelled to protect user privacy, this can make it more difficult to trust the data their platforms generate.

Are ad networks overcharging? The evidence so far

Recent legal cases have shone a spotlight on ad networks and their capacity to overcharge users. Let’s take a deeper look at these cases and where ad platforms have damaged user trust.

Meta is accused of inflating ad reach by up to 400%

Advertisers are claiming more than $7bn in damages after alleging that Meta has inflated its potential reach metric by up to 400%, possibly including bots and fake users.

The potential reach metric is designed to help advertisers see how many users might see their ads. According to the court documents, the plaintiff’s team established that:

“The default Potential Reach shown to advertisers is always inflated by at least 33% and the targeted Potential Reach is always inflated by at least 10%.”

Exaggerating this metric is said to have inflated ad costs for less effective campaigns. It also calls into question Meta’s reliability as an ad platform, giving advertisers pause when it comes to setting budgets for Facebook and Instagram advertising.

LinkedIn pays $6.6m+ to settle ad inflation case

Despite being one of the more trusted ad networks out there, LinkedIn recently paid out a significant sum after being accused of wrongly inflating video ad views. The plaintiffs claim LinkedIn counted views even when videos played off-screen after the user had scrolled past.

In 2020, LinkedIn also revealed bugs in its platform may have contributed to more than 418,000 overcharges (of which most were less than $25).

While LinkedIn has not admitted any wrongdoing, they did provide credits to the majority of those affected by these overcharges. They also agreed to hire an external auditor to review its ad metrics for two years.

Google admits overcharging for impressions

In February 2024, a Google spokesperson reported that some advertisers had been overcharged for impressions on Google’s Display Network and Video 360:

“We detected a bug that resulted in a limited number of partners being overcharged for a small number of impressions on Display & Video 360. These overcharges were minor. We resolved this issue in December 2023, and yesterday, notified impacted advertisers that we have issued them credits for the overcharged amount.”

Google is arguably the most proactive ad platform when it comes to issuing refunds or credits in these cases. If you suspect there’s invalid activity on your account, you can request a click investigation. Google may credit your account if they find evidence of invalid clicks.

X is (still) plagued by bots

Despite Elon Musk’s claims that he’s tackling X’s bot problem, real advertisers believe there’s a lot more work to be done. One user said that while X reported almost 350 clicks through to their site, Google Analytics showed fewer than 10 views in the same timeframe — none of which came from X:

“I asked a few social media “experts” I know about this anomaly and they all offered similar responses: bots. You know, those non-human software robots that proliferate everywhere. Few, if any, of those clicks were actually human, they said.”

All this said, many businesses rely on digital advertising to generate revenue. So the solution isn’t as simple as moving away from untrustworthy ad platforms and finding a new way to make money. Instead, we need to understand how we can get the best data and the best ROI from our PPC efforts.

How to spot ad performance inflation & verify your results 

Spotting ad performance inflation isn’t always easy. And because there’s no real incentive for ad platforms to tackle problems like invalid traffic themselves, the onus is on advertisers to detect unrealistically high performance. Here are 5 ways to identify performance inflation and verify your PPC results.

1. Get to know your data

Knowing how your data normally looks will help you spot any unexpected anomalies that may indicate ad performance inflation.

For example, say a social media platform charges you for 100 clicks, but Google Analytics doesn’t show a corresponding rise in site traffic, you may need to investigate further and determine where the issue lies. Using multiple sources of data will give you a more informed picture of your results. 

2. Review results more often

Regularly check your PPC results and where they’re coming from. This can help you tackle ineffective campaigns more quickly, saving you money on tired or unprofitable campaigns. But it can also help you better understand where results are generated and which ad platforms are underperforming.

3. Use an unbiased reporting tool

If you think your ad platform is overreporting its own success, consider using an independent PPC analytics tool to get unbiased results. This will give you a more accurate representation of attribution across all your marketing channels, so you can better allocate your ad spend and minimise the risk of overcharging.

4. Use conversion modelling

As privacy measures restrict user tracking and cookie placements, conversion modelling can help you bridge the gap caused by this lost data.Using advanced algorithms, conversion modelling tools analyse impressions, clicks, and conversions to accurately predict where and when future conversions are likely to take place. This enables you to give credit to each platform and allocate your resources accordingly.

Platforms like Google and Meta are already using conversion modelling tools to provide data without relying on cookies. But for a completely unbiased view, it’s best to use a trusted independent conversion modelling tool.

5. Switch to a hybrid attribution model

Last click attribution models are commonly used, but they allocate all the credit to the last touchpoint in your user’s journey. If you use several advertising channels and/or have a longer sales cycle, this type of attribution model is unlikely to give you an accurate picture.

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Combining multiple attribution models — such as last click and linear models — gives you more information about the entire buyer journey. So you can allocate spend more fairly and ensure you’re optimizing for the right channels and campaigns.

6. Conduct incrementality testing

Incrementality testing analyses the behavior of those who have seen your ads versus those who haven’t. This shows you how your campaigns are affecting user behavior, so you can see whether ad platforms are artificially enhancing performance.

You can also use incrementality testing to trial new ads and tactics. Importantly, incrementality tests don’t encroach on user privacy, and you can run them on any paid channel. So this is a great way to boost revenue while optimizing campaigns and detecting performance inflation.

We recently spoke to PPC expert Nick Handley about using incrementality and uplift tests to measure the true impact of marketing efforts. Take a listen to Nick's insights on incrementality at 17:09, or watch the full episode for a more in-depth look.

Get more from your ad spend with Lunio

As ad platforms move towards more black box campaign types that limit visibility, it’s going to get harder to identify performance inflation and overcharging. But with the tactics above, you can get a better picture of where users are converting and optimize for these touchpoints, helping you get more from your ad spend.

Removing invalid traffic from your performance marketing campaigns will also boost your PPC return on investment. Lunio detects and removes IVT so you can minimize wasted ad spend and get the best possible results.

‍Take a tour of our IVT detection software, then get a free two-week traffic audit with Lunio to see how much IVT is affecting your PPC campaigns.