Jeremy is the VP of Digital Media at Vovia. He loves all things digital and has an insatiable appetite to learn new things. He spends his free time riding his bicycle in the mountains and backroads of Alberta.

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Using SEO Best Practices For Paid Search Success

It is no secret that Google is committed to machine learning and making AI a big part of automating campaign management on their various platforms like Google Search. Over the past number of years, Google has been releasing AI-driven campaign and ad types such as Smart Shopping, Smart Bidding, Responsive Search Ads, and Dynamic Search Ads to name a few.

It is also no secret that Google has been giving paid results more and more real estate within search results. This often leads to the belief that SEO and good website hygiene is not as important as it used to be, as paid results are likely to get the clicks.  

The promise of automated AI-driven tools is that they allow marketers to step back from the day-to-day micromanagement of campaigns and instead look at things at a more macro level. We can focus more on strategy and “the big picture” of investing time and resources on a mix of channels that drive the best performance, rather than spending time on repetitive optimization tasks. 

Data is King

If there is only one thing you need to know about machine learning/AI it is that it needs data…and lots of it. Machine learning is only possible through the ingestion and analysis of data to feed into algorithms that will in turn offer recommendations or take actions based on a defined desired outcome. This means that in order to start using AI-driven optimization, we first need to supply enough data for it to understand the content of a site to effectively target campaigns with. 

What Does SEO Have to Do With It?

Hold on a second, wasn’t this post supposed to be about SEO? What does SEO have to do with helping to get machine learning working on paid campaigns? 

At its core, SEO (Technical SEO in particular) is about optimizing your website to allow search engines like Google to read and understand the content on the site. Lump in a bunch of other factors and search engines will crawl, index, and rank your site for various search terms and users will find their way to your site organically through searching on the web. Yes, this is a gross oversimplification, but for the sake of this post, we will keep it simple.

It would seem appropriate that if you are an engineer at Google trying to design an algorithm to automate the process of learning about a website for paid campaigns, you would ask the other engineer down the hall that works on search if you can borrow their search engine to help with your machine learning. Google offers a number of automated campaign types like Dynamic Search Ads that crawl a website or a set of pages on a website and generate dynamic ads and keyword sets that will target those pages based on the content found. The ability to do this directly depends on the ability of the search engine to crawl, index, and understand the content and context of the website. Sound familiar? This is exactly what SEO is about. 

If a website is not set up in a search engine-friendly manner, the AI will not be able to get what it needs to run. In fact, on Google’s help article for optimizing DSA campaigns they call out the importance of SEO. 

We often see situations where a website has been configured to block search engines from crawling and indexing pages on a site. Often the thought is that you don’t want a landing page that is being used for paid campaigns to be indexed and show up in organic search results. The issue is that Google uses the same technique to crawl a site for organic and paid, so a different strategy needs to be used to allow this type of setup and it all comes back to things that are looked at as part of website SEO.

This highlights the relationship between strong SEO and automated campaign types like DSA’s. Google uses the same techniques and information (data) to determine when to show automated search ads and what terms to rank for organic listings. This means that you can use the data you collect from one to optimize the other. Things like Quality Score reports on Google Ads can provide you with insights for changing your SEO strategy, and understanding the quality of the traffic you are getting organically can help you to optimize your paid campaigns. Changes that you make to improve your organic rankings (SEO) will then flow into automated campaigns as well. 

Do you incorporate SEO best practices into your strategy for managing automated campaigns? Let me know what your experience has been with this in the comments!