Running an online news website is a tricky business. From delivering a fresh story with accuracy to keeping it interesting for readers — news publishers put a lot of effort to build their position in the market.
What if I tell you that a top news website generating millions of pageviews is fake? Albany Daily News, a website reaching 10M pageviews in August 2019, is fake. The saddest part — it got 5 times more pageviews than the original 160-year-old Albany Times Union newspaper.
Similarly in Canada, City of Edmonton News has generated more pageviews than authentic local news operations such as the Edmonton Journal and Edmonton Sun. The list doesn’t end here.
These fake websites don’t have a good site structure and are not updated for months. Then how are they getting so much traffic and running ads? To answer this question, we have created this article to understand the depth of ongoing ad fraud.
They Use Fake Niche Sites and Click-Bait Content
How to spot a fake website?
- They have no named beneficiary,
- No social media account,
- Use re-written content from other original publications,
- Try click-bait articles such as celebrity content,
- Have bad design and no updates for months,
- And one cannot find their office address or contact details.
These websites are known to steal money from brands by showing ads on sites and apps with fake or manipulated audiences.
They Launder Traffic by Showing Ads
You might have seen click-bait ads such as ‘30 Before-After Pics of Celebrities Who Lost Weight’ and similar native ads on various websites.
In some cases, it has been found that fraudsters are running similar ads on these websites using such click-bait content. Meaning, the users are redirected from one fake site to another — inflating traffic for each of these.
If this doesn’t sound alarming, then consider this: Fake-website-1 shows a clickbait ad to redirect to Fake-website-2. For this, Fake-website-2 pays $5. Now, Fake-website-2 shows an ad from an actual brand that paid $8 for the impression. Given both these fake sites are managed by one fraudster, $3 (8-5) made it to their account without doing anything.
Both the fake sites sold inventory — upscaling their overall score. The second ad resulted in more money is a hypothetical situation, it can make less money than the number invested by fraudsters. But if we add more such fake websites to the mix, the average will always be more for the fraudster.
They Generate Artificial Traffic
There are tools available to detect bot traffic. But some traffic bots have sophisticated designs to manipulate preventive measures. Artificial traffic is one such example. An artificial user (bot), controlled by a technical algorithm, visits one of the sites of the scheme directly or with a fake referrer.
This artificial bot contains the forged personal data to share with DMPs. These bots are designed to click on the specific types of ads to make them valued prospects for brands. And when these real brands show ads to these bots, they make sure to click to get money from them.
These are indeed a long-term scheme that requires great knowledge of ad tech. And this is why the pointer directs toward the ad networks who understand all the ins and outs to misuse them.
Long-Term Investment Fraud in Ad Tech
As mentioned above, these fake websites are known to either have support or are owned by known ad technology companies.
Imagine an ad network running 5 such fake sites — all the revenue generated by showing redirect ads, ads from the actual brand, and clicks from bot traffic — a share of all this will go to the ad network.
Consider the above example again, if Fake-website-1 and Fake-website-2 are handled by an ad network, then a percentage share of both the ($5 and $8) ads will go to this ad network. Adding $3 made by doing this scam, this ad network is not only inflating its earnings but also making additional dollars.
This ad network can show to its investors that they are making a huge amount of money and their business is a success. They can even ask more investors to put their money in the business — leading to investment fraud.
Why is This Bad for Publishers?
The real advertisers are at a clear loss here. Their ad spending is being wasted on bot traffic and uninterested users. However, this also affects publishers, here is how:
- Brand reputation: These fake sites often copy the name of real news/magazine brands for users to trust them. But when they show low-quality sites and content, it ultimately risks the reputation of real publishers.
- Financial Loss: Ad money spent on fake sites is also a loss for publishers. Over 2000 newspapers have been shut down in the US in the last 15 years. The prime reason for this being a decrease in funding. And then we have these fraudsters taking away brands’ ad spending while real journalists are forced to close.
Why shouldn’t you work with such partners?
Cons of working with such partners outweigh the limited advantages they offer. They could be redirecting your users to their fake sites and using personal data of your users to forge sophisticated bots.
Final Word
Here are some immediate steps needed to overcome such fraud:
- Ability to detect traffic laundering
- Revert the revenue spend on sophisticated bots
- Penalize ad tech companies involved in such practices
- Immediate investigation of such long-term scams after the discovery
Ad tech works best for those who understand the ins and outs of it. This is the reason we are seeing such bad practices without anybody calling out the fraudster — it’s not illegal to own a website if you are a network.
We need a system of a professional and independent audit of digital assets and technical companies. And finally, publishers need to assess the partners they are signing up with to protect themselves against the above-mentioned downsides.
These bits are taken from a report by Social Puncher: Investment Fraud as the Next Level of Ad Fraud
Shubham is a digital marketer with rich experience working in the advertisement technology industry. He has vast experience in the programmatic industry, driving business strategy and scaling functions including but not limited to growth and marketing, Operations, process optimization, and Sales.