The growing surge of fake advertising clicks reported in our analytics programs is frightening. In fact, we’d go as far as saying it’s the biggest future challenge organisations will face when it comes to measuring the ROI of their paid digital marketing campaigns. If you are unfamiliar, not all traffic on the web is from humans, some of it is from bots & web crawlers – who visit our sites, click on our links, and unfortunately sometimes ‘count’ as real-life visitors in platforms like Google Analytics & Google Ads. Many advertisers are seeking ways to stop bots clicking on ads however the sheer scale of different bots that are emerging is making this difficult, we currently have:
- Search Engine bots from the likes of Google & Bing
- Fraudulent traffic bots, whose purpose is to click on ads
- Web scrapers who copy other websites content
- Feed populating bots that share content
- Website monitoring bots
With so many, the digital landscape is quickly becoming a murky place indeed. With many advertisers furious that bot traffic on ads is something they have to pay for – and that fraudulent traffic bots are being created with malicious intent. To look at the scale of the problem, we only need to look at results from the 2019 Bad Bot Report which concluded:
“38% of all internet traffic is now coming from bots, with 20% coming from bad bots”
With this phenomenon showing no signs of slowing down, savvy marketers are now having to learn how to identify bot traffic & need to begin filtering bot traffic in Google Analytics to be able to draw effective conclusions from their data.
How To Identify Bot Traffic The Easy Way
When you spend time looking at your bot traffic in detail, you start to see a few patterns emerging. Firstly, a lot of the bot traffic you are experiencing will likely be coming from the same IP addresses and you’ll also notice that bots don’t stay around long. In fact, they usually come and go from webpages in less than a second. Even if a human dislikes a webpage & wants to bounce, it usually takes a real person at least 3 seconds to process the page content & physically click off the page.
KEY LESSON – SESSIONS WHICH BOUNCE AFTER ONE PAGE VIEW AND
SPEND LESS THAN 1 SECOND ON YOUR WEBSITE ARE USUALLY GENERATED FROM BOTS.
Using this approach to identify bot traffic and spot fake advertising clicks is remarkably easy to do in Google Analytics. All you need to do is:
- Select the dates you want to monitor in Google Analytics and head on over to the ‘Network Report’. This sits inside Technology, within the Behavioural section of GA.
- Here you will see a huge list of all the different Service Providers who have sent you web traffic, you can then sort this list by ‘Avg. Session Duration’.
- Anything that has sent you sessions that have been limited to one single page view AND the Avg. Session Duration is 00:00:00 is likely to be a from a bot.
- You can take this a step further by filtering the traffic down to different acquisition channels, to see if there is a high percentage of fraudulent advertising clicks in any of the channels you are investing in.
The above image shows various bots that have sent one of our websites traffic over the last year, you can clearly see this traffic is of extremely low quality – with the sessions ending almost instantly. Now that you know how to identify bot traffic, the next step is filtering bot traffic in Google Analytics. All you need to do is enter the ‘Admin’ section of GA and select ‘Filters’. Then you want to click the ‘+ add new filter’ button and exclude based on ‘ISP Organisation’. Then it’s just a case of including the organisational names you have from using the Network Report above, just copy them in exactly as they are into the Filter Pattern Field. Each one you add is another bot filtered out of future reports & datasets.
From our experience it’s hard to fully stop bot traffic on ads, so you will likely get some fake advertising clicks across all your channels. However, the two biggest culprits for attracting fraudulent traffic bots are without question Display Ads & Paid Social. If you are running campaigns on these two channels and not getting a good return it may be worth digging into the data to see what percentage of the traffic is human – you might get a surprise.
The Dangers Of Bot Traffic On Our Ads
Stopping bots clicking on ads is a difficult thing to do and in the future it may just be considered the norm. On a personal level though, it’s an area which really does frustrate and which we feel the big advertising platforms need to be doing more to combat. If we continue to turn a blind eye to fraudulent traffic bots, then following happens:
More Advertisers Money Gets Wasted – as more and more clicks come via robots with no intention of ever buying a product or service.
Data-Driven Decision Making – is severely hampered, as high proportions of traffic within web analytics packages is fake. This makes channel analysis & proving ROI a near-impossible task.
Google May Start To Reward Bots More – a lot of advertisers now bid based on conversions, where future ad placements are likely to go to the sites which have performed well in the past. This is dangerous because bots can now fill in contact forms (usually with junk info). If these are being misinterpreted as a conversion in platforms like Google Ads, then sadly more ads will show on lower-quality websites – which accelerates a vicious circle.
Fake advertising clicks are a huge problem in our industry and many marketers are simply too busy to give this adequate time. We would advise you to first understand whether you have a severe problem with bot traffic in any of your marketing channels and to begin filtering bot traffic in Google Analytics. If this is a growing concern it’s also useful to share whatever data you have with your account manager at companies like Google and they should be able to look into the matter further. On occasion, some advertisers have been given a full refund or discount on their upcoming activity.