Bot traffic or non-human traffic is yet one more addition to the whole ad fraud nexus.
Publishers often complain about their websites, ads, and campaigns not performing needless to say . They feel ‘non-human traffic’ also referred to as ‘bot traffic’ is one among the explanations .
About 78% publishers report bot traffic on their sites, yet only 38.4% purchase traffic.
Despite publishers knowing the rationale , the matter still continues to persist as they don’t know why and the way bot traffic has been plaguing their efforts. So at the top , what does this unawareness lead to?
The answer is ad revenue loss and website quality decline.
This is why we’ve compiled a blog post that answers some essential questions associated with bot traffic like what it’s , what purpose it serves, and the way to block/remove it.
What is Bot Traffic?
Whether yours may be a big, popular website or a replacement one, a particular percentage of bots can pay you a visit at some point of your time .
Traffic bots or web robots are automated to go to premium websites and appear as targetable humans (audience). Some bots perform repetitive tasks like copying, ad clicking, posting comments, or any activity which will be included in malvertising.
Data has it that nearly 29% of website traffic is bot traffic. This also means 29% budget is being spent on processing artificial pageviews/ad clicks eventually resulting in high (poor) bounce rate (more arising on this).
An acceptable bounce rate of an internet site ranges from 45-65%. Normally, such a figure would seem too unimpressive. However, publishers, advertisers, and marketers became familiar with this range of bounce rate. Why?
This is because website owners know equally of their traffic can’t be real. Holistically, almost 50% of web traffic is bot traffic. In 2016, bot traffic accounted for 51.8% web traffic.
These are staggering numbers and are reflective of the penetration of bot traffic.
Six sorts of Bots to observe Out From
These bots make fraudulent ad clicks, therefore used for click spamming. this is often the foremost threatening bot type for web publishers especially if you follow the PPC model. Consequently, the analytics data gets skewed and budget gets eroded.
These bots also tamper with the analytics-generated user engagement data. However, rather than ad click count, they increase fake download count. just in case where a free ebook download is your end conversion, these bots are likely to ruin your conversion data.
This is the foremost common bot type which disrupts user engagement with distribution of unwarranted content which are spam comments, phishing emails, ads, unusual website redirects, negative SEO against competitors, etc.
These bots visit an internet site with malicious intent一stealing your content. they’re made by third-party scrapers who are employed by competitors so as to steal content, product catalog, and costs . The stolen content is then repurposed to publish elsewhere.
These bots appear as genuine visitors who intent to bypass online security measures. It’s mostly these bots who are liable for attacks like distributed denial of service. They’re also those who inject spyware on your site or appear as fake search engines.
Different Types of Bad Bots
It’s important to recollect that not all bots are bad.
The good ones are created to perform operational tasks like old data scraping, content hygiene, data capturing, etc. Some good bots are backlink checker bots, monitoring bots, social network bots, feedfetcher bots, program crawler bots. Good bots are necessary for users to possess a fruitful experience of browsing the web .
Bad bots, on the opposite hand, as stated before perform all spammy and fraudulent activities that end in losses to publishers and advertisers, both.
Here’s an infographic on how good bots and bad bots are dissimilar in nature.
How to Identify Bot Traffic?
The bad news is that bad bots are becoming smarter. consistent with the Bad Bot Report 2020 that was released by Imperva, bots comprised almost 40% of Internet traffic, out of which bad bots took the larger chunk of that traffic.
Bot traffic is hitting websites every hour. Even while you’re here reading about it. within the beginning of this blog, we mentioned that a lot of publishers fail to know why and the way bot traffic affects their efforts. Also that they don’t skills to affect it. So let’s begin with the primary question now which is how can publishers identify bot traffic?
#1 Recheck Page Load Speed
You may have conducted this test every week ago. As we all know , these test results look a tad different after every short interval. But, subsequent time once you conduct a page-load speed test and see a substantial fall (without any major changes that happened to your site), likelihood is that you’ve been hit by bot traffic.
There might be many reasons for a slow loading site. However, just in case of detecting bot traffic, checking the page-load speed is that the initiative . It’s possible that an entire lot of bots are together trying to strain your servers and take them offline.
#2 Keep Tab On Certain Metrics
If you notice a sudden rise in your traffic count and bounce rate at an equivalent time, your site is perhaps being visited by bot traffic. Here, high traffic count means a high number of bots or high frequency of same bots coming to your site again and again.
And high bounce rate means non-human traffic who visit for no purpose and just leave without exploring more webpages. A suddenly changed session-duration behaviour also indicates bot traffic.
Let’s say your site usually serves long-form content, hence your average session duration lies between two to 5 minutes. However, if you see an expected dip, bot traffic might be the rationale . Alongside these, there also are other common metrics you ought to keep watching .
#3 Verify Traffic Sources And IP Address
Not just metrics, even some data sources can act as buzzers for bot traffic. Regular and high number of visits from an equivalent IP addresses emphasize the very fact you’re getting bot traffic. Tools like Deep Log Analyzer can help probe endless raw server logs and blacklist the offending IPs.
Odd traffic sources are next. Suppose most of your traffic comes from US region and Asian countries. A sudden addition in traffic coming via Arab (non-english) countries could also be one among the indications.
All of this will be checked using website analytics tools like Google Analytics. If you’re new GA, it’s advised to urge familiar with the platform first, then move ahead with understanding the utilization cases with bot traffic identification.
#4 Test For Content Duplication
Your content is that the heart of your website. And with the invasion of bots, it’d be in danger . To detect bot traffic, keep checking for duplicate content to make sure no scraper bots have visited your site and stolen from you.
Tools/platforms like SiteLiner, Duplichecker, CopyScape are handy to use and find if your content is repurposed and used elsewhere.
How to Stop Bot Traffic?
Detecting bot traffic once, immediately involves stopping bot traffic once and for all. Bots are like viruses hitting your website, skewing your set systems, stealing your data, and more. But thankfully, there are methods which will assist you shield against it. Here you go:
Legitimate Arbitrage: Buy traffic only from known sources. to make sure purchased yet safe traffic, many publishers practice traffic arbitrage to make sure high yielding PPC/CPM based campaigns.
Use Robots.txt: Place robots.txt to stay bad bots faraway from crawling your sites . Publishers may additionally want to make sure the crawler settings are as needed to stop troubles in AdSense ads.
DDOS: Execute distributed denial of service (DDOS). Publishers having an inventory of offensive IP addresses leverage DDOS protection to deny those visit requests on their website.
Use Type-Challenge Response Tests: Add CAPTCHA on sign-up or download forms. Many publishers and premium websites place CAPTCHA to stop download or spam bots.
Scrutinise Log Files: Examine server error log files. As bots attempt to overrun servers, thoroughly examining the server error logs helps find and fix website errors caused by bots
How to Detect Bot Traffic In Google Analytics?
As understood by now, bot traffic really messes up with data. Also, as per the above listed methods, stopping bot traffic requires timely attention. But thankfully, there’s an easy thanks to filter bot traffic from Google Analytics to a minimum of prevent the info damage.
Here are the steps which won’t even take 30 seconds:
Visit Google Analytics Admin Panel.
Navigate to look at Settings within the View tab.
Scroll slightly downward to identify Bot Filtering checkbox.
Apply sign up the check box , if unchecked.
Hit Save.This filtration of bot traffic out from your Google Analytics account ensures all kinds of recognized bots (the ones mentioned above) steer beyond your data. However, the tactic might not be ready to debar unidentified or a replacement sort of bots.
Can Bot Traffic Be Ignored?
We also encounter bad bots on our website from time to time. Below is an example of spam comments that we received on our blog:
The treatment to the present is ‘mark these comments as spam’ and that we could have done an equivalent . But since we are experts on the matter, we used this chance to elucidate why we chose to not ignore this bot activity. And why publishers shouldn’t either.
Publishers should start caring about bot traffic on their website because their:
site and ads also are being hurt by ad fraud disguised as bot traffic
precious data/analytics could be getting skewed
website load time and overall performance could be deteriorating
website is getting susceptible to botnets, DDOS attacks, and bad SEO
CPC and revenue are becoming severely suffering from fake clicks
Surprisingly, only 5% publishers work with a fanatical fraud-patrol professional. this suggests , publishers are becoming suffering from ad fraud methods (bot traffic being one), but they’re doing just about nothing about it.
We encourage publishers to consistently check for bot traffic on their website because it could lead on to revenue loss and bad user experience.