RankBrain’s potential effect on your paid search campaigns

Just weeks ago, Google announced that it would be releasing improvements to its Dynamic Search Ads, making its targeting even more precise and relevant than before.

But one example from the announcement caught my attention: “Ads that point to a landing page about iced coffee makers will be less likely to show for less relevant searches like ‘iced coffee’.

What gave me pause here isn’t that Google is getting better at understanding queries on a small scale, but that it is doing this in alignment with Google’s understanding of your page content.

This, to me, hints at the use of Google’s RankBrain artificial intelligence, which utilizes machine learning to analyze query intent.

Previously, analysis of RankBrain has focused on how it assesses organic relevance. However, some focus should now shift over to how this AI impacts the paid portion of the search results page.

How RankBrain may effect paid search

To be clear, I don’t work at Google and thus I have no idea if RankBrain is truly behind the new targeting mechanism. That said, I would like to walk through what I believe is the most likely scenario going on here.

What makes this most interesting – as it relates to the machine learning feedback mechanism – is the process used when creating campaigns with the assistance of AdWords.

The advertiser provides the website that they want to drive traffic to, and Google then analyzes the pages and creates an ad campaign based on the perceived content on those pages. The advertiser can then adjust the campaign to fit their perceived goals.

One method used in performing these adjustments is to include negative keywords. (Negative keywords tell Google that the advertiser does not want their ads to appear for queries that include those words, phrases, or exact string of words.)

In thinking about the ways in which the use of negative keywords will impact RankBrain’s machine learning, the potential feedback from millions of advertisers with millions of pages of content should vastly improve the AI’s ability to provide more precise ad targeting.

As RankBrain learns what is and what isn’t acceptable to certain advertisers (not only at the query level but also based on site content), it becomes increasingly powerful.

What does this mean for advertisers?

It means if you haven’t already been studying SEO processes and utilizing best practices when building your landing pages, it is definitely time to start.

Creating landing pages that focus on a specific theme – and adequately communicating that theme as close to the top of the page as possible – will be even more important than ever.

As an advertiser, RankBrain effectively gives you a bit more leeway to help Google hone in on what your page is about. When you give Google a clear sense of what you are providing, it will better help you reach the right audience.

The benefits to advertisers could extend even beyond the aforementioned Dynamic Search Ads. The insight that RankBrain gleans from landing pages and associated keyword targets, determined from the initial Dynamic Search Ads data set, can reasonably be applied at a basic level to the other AdWords search auctions.

This enhanced relevancy can help advertisers reach conversion-ready queries and increase click-through rate, thus allowing for better utilization of ad spend.

My advice for advertisers is to get your landing pages RankBrain-ready:

• Understand your audience.
• Give your pages clear, unique themes.
• Use alternate keyword variations throughout your copy that still relate to the page theme.

These are methods that have always been helpful to successful search advertising in the past, but they become even more important moving forward.

Kevin Gamache is Senior Search Strategist at Wire Stone, an independent digital marketing agency for global Fortune 1000 brands.