Blocking Fake Activity

According to Statista, over 42% of all internet traffic in 2021 was generated by bots, and our own analysis shows almost 30% of email opens and 35% of clicks are fake.

Though bots protect our privacy and keep us safe, the fake data they generate can give us a distorted view on content engagement and break our automation. That can result in us investing in the wrong content areas and passing poor leads to Sales.

Much as we love seeing high open and click rates, we feel data integrity is more important. So we created BotShield.

BotShield is an AI-powered solution that looks for non-human behaviour, blocking fake opens and clicks before they muddy your metrics. Our goal is to deliver metrics, automation and leads you can trust.

Background

Bots are computer programs that perform automated tasks or simulate human activity.

Good bots rank us in search engines, provide website analytics, ensure our emails are virus-free and protect our privacy. Bad bots exploit security, post fake reviews and inflate our paid campaigns.

Many corporations have gateways that scan emails for malicious content. These solutions often follow links in our marketing emails, generating fake clicks.

How it works

BotShield intercepts and segregates opens and clicks as they enter our platform.

Unlike other marketing automation providers we could mention, you don’t need to filter junk activity from your metrics, lead scoring or automation.

So how do we identify bots? Bots have specific characteristics. They often click all links in an email faster than a human possibly could. Or they click a hidden link we place within each of our emails.

Sometimes they have a specific footprint that we can identify (user agent or IP).

BotShield uses machine learning to identify patterns that in turn create processing rules (don’t worry, we check the rules before implementing).

FAQ

How does StoneShot's BotShield technology work?

Email clients such as Apple Mail and Gmail can prefetch or preload images before the recipient opens the email, which causes the tracking pixel to load and generates an open that may not represent real engagement.

Corporate email security systems and gateways often scan or follow links automatically to check for malicious content, generating clicks that were not made by a human.

BotShield uses several detection methods to capture and supppress this fake activity:

• Machine learning and pattern recognition to identify suspicious behaviour and create detection rules.
• Known bot footprints, such as specific IP addresses and user agents commonly associated with security scanners and automated systems.
• Hidden links within emails that humans cannot see or click. Bots that scan every link in an email often trigger these hidden links, revealing themselves as non-human traffic.
• Behavioural analysis, such as detecting contacts that click every link in an email within a fraction of a second—something a human couldn’t realistically do.

How can we export the Blocked Opens/Clicks activity data?

Blocked Opens and Blocked Clicks data cannot be exported, and we are unable to provide information on the email addresses generating this automated fake activity.