Jono Alderson
Special Ops - Yoast
Read more about Jono

Black Hat Analytics – When Your Data is Working Against You

London 2018 | 11 - 13 June 2018 | 12:25

There’s still a lot of debate about whether black hat SEO is viable, scalable, or even a thing at all. Meanwhile, without you even knowing, competitors and bad actors may be sabotaging your tracking, reporting and analytics data. Black hat analytics is a real, present threat, and something which there are very few defences against. In this session, Jono will explore some of the tactics, attacks and strategies which can compromise your setup, give you tips to spot when you’re under attack, and try to help you to protect yourself.

Many businesses rely on JavaScript-based tracking solutions (like Google Analytics, or Adobe Analytics). These are extremely vulnerable to attacks, both subtle and destructive, and you need to take proactive measures to defend your data.
It used to be that, if you’re seeing odd data in your analytics, chances are that it’s a configuration issue. Now, in an era when referrer spam is the least of your worries, it’s worth considering that your data quality issues might be the product of malicious actors.
Check your analytics for oddly inflated goal conversions or pageviews, odd-looking channel metrics which, and visits with odd attributes (with strange device types, screen resolutions, etc). Imagine that you’re one of your (unscrupulous) competitors, and you wanted to pollute or confuse with your analytics data by sending fake visits or conversions. What would you do? Look there – it might already be happening.
As more and more tools become integrated (think, your analytics data feeds your paid ads spend, which drives consumers who end up in your CRM), the impact of analytics attacks heightens. These integrations need to be owned, continually monitored, and secured.
You definitely shouldn’t be looking for opportunities to inflate, corrupt, or otherwise attack your competitors’ data – at best, it’s legally grey, and at worst, outright illegal. Don’t mess with other people’s tools and data, folks!

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