Machine learning is a subset of artificial intelligence, and the tools required for effective machine learning use are becoming more than something that’s simply ‘nice to have.’ When the link between SEO, business growth, and machine learning becomes increasingly intertwined, marketing departments and SEO specialists need to start thinking more about the information that they are lacking and how machine learning can help them gain access to those insights.
With the creation of the RankBrain algorithm, Google positioned itself at the forefront of machine learning. They have gone a lot further since the late 90s, though, and continue to lead the way. When Google bought out the software company DeepMind, they also bought the next step in machine learning. The computer program AlphaGo was the first artificial intelligence to beat a human at the famously complex board game Go, and now Google continues to make AI advances that cover a variety of different areas, many of which are directly linked to SEO. These include:
● Advertising and marketing
● Image analysis
● Health and safety
● Video analysis
However, when it comes to data SEO, it’s hard to overestimate the importance of RankBrain.
This algorithm is doing more than simply working out which websites are any good. What RankBrain does is fine-tune the way that the Google search engine understands both context and relevance when different words are used. The goal of RankBrain is to more quickly and comprehensively understand the intent and ideas behind every query.
As new words, sayings, and trends emerge, that algorithm learns, deepening its understanding of user intent in an ever-changing world.
For digital marketers and SEO specialists, that has meant creating content and adopting certain technical measures to ensure that Google can rank websites accordingly. Experts take specific SEO requirements such as keywords and utilize them across the back end and content structure of a website in the hopes of being ranked higher on search engine results pages (SERPs) where they will be more likely to be clicked on by a user. By using data analysis, those keywords, and even the content itself, can be both analyzed and/or created by a smart algorithm or machine learning tool.
There is more data available to SEO professionals than ever before, and there are more branches of SEO than ever as well. Data and SEO come together because that data can be used to build and fine-tune a website so that it has maximum impact on search engines. The four key targets for data SEO are:
● Overall Website: Data can be used to provide a vast amount of technical information about a website, from the metadata being used in the right way to the title tags that are not being used.
● Specific Pages: From the number of people who visit a specific page to its technical stats, inbound link information, and the social media impressions that it makes, every page on a site can be analyzed according to your current marketing goals.
● Words and Language: Keyword research is a fundamental element of SEO, and machine learning combined with the available volumes of data can make it much easier to identify the relevant keywords to grow brand visibility and promote content on Google and other search engines.
● People: Customer research is essential in the digital age, and, by processing and analyzing the data of the people that visit your website, you can gain deeper insights into what those potential customers want. If a site visitor shares your content or interacts with you on a social platform, then you gain access to data that is invaluable when that data can be gathered in high volumes.
Digital marketing and data are only going to grow more connected. As the volume of data grows and the diversity of that data continues to become increasingly complex, machine learning tools are only going to become the standard tool of the modern digital marketer.
From an incredibly basic point of view, the content that sits on your website is little more than information that has been published. As Google has become the single largest curator of big data, that content became a clearly definable and quantifiable entity.
Search engines turn your content into data, and by doing so they are better able to conduct real-time analysis that allows them to deliver the right content to the right query. You can see how far this has come simply by doing a basic search on Google right now. You’ll see that local search packs and rich snippets have become the norm, simply because they allow search engines to deliver more immediate and precise answers to queries.
Anyone in the field of SEO (or any other form of digital marketing) needs to be able to keep up with the rapid learning curve of Google, and that means a shift in thinking: content is data.
By using the right machine learning tools, it’s possible to dive deep into the semantics of your content so that it performs more effectively on SERPs.
There are some major challenges facing anyone in the SEO field. Machine learning and data analysis have helped to eradicate those challenges, making it far easier to grow your business’s digital footprint and grow your customer base. Traditionally, we approach SEO with a basic understanding of best practices and then use manual processes and linear thinking to improve SEO standing. An example of this would be identifying that your ranking competitors for a search term are using more backlinks and internal links. The natural conclusion would then be to adopt the same practices and spending time on building those links. This is nothing more than common sense, but a deeper understanding is vital. Data science not only speeds up the process of identifying issues, but it can also identify the specific variables that are actually having a bigger impact on your rankings.
The goal for any SEO strategy or digital marketing team is, ultimately, to get more website visitors and convert them into paying customers. To hit the target of more those conversions, it is essential to locate and identify any specific correlations between the vast amounts of user data. How the addition of a more streamlined navigation design aids conversions (for example) can be measured in precise detail, and experts can leverage the lessons learned from those datasets to make further improvements. Thanks to a huge range of third-party analytics tools, those datasets are easily accessible, with everything from Google Search Console to Bing Webmaster Tools helping to identify issues with content data so that adjustments can be made more effectively. Those analytics tools mean that you can:
● Learn how much time is spent on every page by every user
● Highlight existing conversion rates
● Identify the number of backlinks that have driven traffic
● Record the number of onsite clicks
It’s important to look too at social media analytics, especially considering that those platforms are an almost endless trove of data-driven user and behavior insights. At the time of writing:
● Facebook: Currently has 1.69 billion users
● Twitter: 44% of U.S. adults age 18-24 tweet monthly
● Blogs: There are currently an estimated 600 million blogs online right now
Factor in LinkedIn, Instagram, TikTok, and Tumblr, and that’s a lot of people, a lot of activity, and an extraordinary amount of data. Google is, more than anything else, a big data company.
Although they say that social media isn’t specifically factored into SERP performance, it’s not a stretch to see that Google especially cannot afford to ignore the vast amounts of data and information that social platforms provide. That means SEO professionals need to start looking closer at the analytics provided by those platforms and using machine learning tools to process and analyze that data to develop more robust, informative, and actionable strategies.
By making use of data science, your marketing team can make more informed decisions that will have a measurable impact on your audience reach, sales, and growth. That’s because data science tools allow you to:
● More easily visualize varied combinations of data to clarify the actions that will have the most impact
● Develop an improved understanding of your audience so that marketing campaigns can be more easily targeted to appeal to those specific audience members
● Highlight pain points in the customer journey that can then be addressed
● Recognize changing buying preferences quickly
● Identify the referral sites that are delivering the highest traffic and the most conversions
● Perfect technical SEO analysis so that loading time, bounce rates, redirects, and response errors are identified in real-time, limiting negative exposure and bad first impressions to new audiences
● Recognize the pages on your site that are not being crawled by search engines
● Alert you when a new source of website traffic is identified
This huge number of advantages will, of course, only be of value if you can apply that information to your SEO. That will mean:
● Knowing your sources: With so much data available from so many different platforms, it’s easy to get overwhelmed. You need to know which are the best and most valuable data sources for your SEO goals. For that, you’re going to need to be using the right data analyzing tools. Some of the most popular of those tools are Google Analytics, Ahrefs, and SEMrush.
● Adjusting to ecosystem thinking: SEO is a hugely complex arena that addresses technical requirements, content, the customer experience, research, services, and sales. Data SEO tools allow you to integrate those methods and strategies to create a more cumulative mix of data results. That way, you can evaluate data value and assess negative factoring issues (such as bot activity), and adapt your conversion funnel so that insights turn into actions, improving the potential for business growth.
● SEO alignment with marketing: You need to optimize every factor that affects your SEO, which means that your marketing team needs to collaborate extensively with the sales teams, the UX design team, and the customer service department for maximum effectiveness. Data science and machine learning tools can take those relationships (whether they are in-house or outsourced) and make it easier and more impactful to align those teams to a goal. So if you want more conversions, your SEO effectiveness can be monitored and analyzed across the whole scope of your business.
● Visualization: Looking at a spreadsheet and trying to identify common patterns is time-consuming, and it’s very easy to miss out on the most valuable insights when you’re doing data analysis manually
Data SEO tools present you with information that is easy to read so that you can compare and contrast different datasets, analyze huge data volumes that will scale with your company, speed up the time it takes to access insights, and even identify solutions that you didn’t know you needed. Being able to recognize trends and patterns in your SEO strategy and its effectiveness comes down to one thing: visualization. It is the key to the insights that you need.
If you want your SEO to be built on a framework of facts rather than gut-feeling, then data-based SEO analysis is critical in a way that can’t be underestimated.
Data volume is only growing. Already, the SEO industry is huge in terms of both size and scope, simply because SEO has an effect on almost every facet of a modern business. Every year, SEO professionals have to do more, and that includes coping with that growing quantity of accessible data. However, you wouldn’t know that by looking at the employees of a business, because only an estimated 31.5% of businesses employ a data scientist. SEO experts have a hard task, simply because they have no choice but to try and keep up with one of the most technologically advanced companies in the world: Google. It’s the need to keep up with Google that has seen the SEO industry always keeping ahead of the curve when it comes to new technologies and business practices.
If you’re still working on the content marketing model of churning out 500-word articles that have a couple of embedded authority links and a scattering of keywords, then you’re already falling behind the demands of cutting-edge, data-driven SEO. Search engines have been fine-tuned continuously, and the shift to the customer experience is starker than ever. Content now needs to be:
● Targeted to specific audiences
● Written to answer specific queries
● Aligned with your brand’s tone of voice
While balancing these essentials, those keywords and links still need to be utilized effectively. By applying the right machine learning tools, you will learn how to change your content so that it is more valuable, more tonally in line with your brand image, and is the type of writing that will have the most impact on your specific audience demographics and their buying habits. One of the important aspects of using artificially intelligent data analysis is that the more you use it, the more it learns, and the more value it provides.
Even previously challenging tasks, like identifying exactly what content to deliver at specific points in the customer buying journey, is much easier to achieve and can have a dramatic
Consider how, in ecommerce, having automated repricing or AI-generated, personalized product descriptions can save time while being more influential than doing everything manually. Already, companies are using personalized, AI-generated product descriptions that use basic keywords around a framework that uses an individual’s own datasets for more successful targeting.
Machine learning is more useful than just creating, perfecting, and guiding the creation of content. By analyzing the data provided by your website, machine learning tools will be able to determine exactly where improvements need to be made in terms of:
● Meta data used
● Structured data
● How your content relates to search indexing
● Keyword performance
However, it should also be utilized to measure specific user experience (UX) data as well. That means looking at the following metrics to gain beneficial insights:
● Bounce rates
● On-page activity (clicking links, filling out forms, etc.)
● Scrolling speeds and click patterns
● Video content views
By combining these metrics, you can build an actionable overview of the total user experience, highlighting where there are issues, and taking the necessary steps that will lead to a higher position on SERPs, a greater volume of click-through rates, and your conversion rate optimization.
There are more tools than ever that have been designed to aid professionals with their SEO development. These come in a wide range of specialty areas, but even a cursory bit of research will reveal a variety of very helpful resources that can up your SEO game, including:
● Automation tools that can update your SEO strategy in real-time following algorithm changes on search engines
● Identify key times to make simple changes to your existing SEO strategy to allow for more immediate wins and a higher number of organic site visitors
● Continuously monitor for new backlink opportunities and/or code upgrades
The reason why these data SEO tools are so high-value is that they present very straightforward, actionable insights that can be implemented immediately by an SEO team. Even a simple resource like an AI-powered simulated search engine can be very beneficial because it will allow you to test different SEO solutions safely and quickly. Rather than waiting a few weeks to find out if a search engine will recognize, reward, or punish your SEO changes, a data-backed simulator can predict how changes will affect your website traffic and SERP rankings immediately. As the value of data in the field of SEO continues to grow, expect to see more tools being developed and launched. The future of SEO is set to look very different from its current state.
Whichever tools you use to make greater use of your data, the key is having the right datasets and knowing how best to use them. Whatever your goals, be it producing better content or speeding up your website loading speeds, there are a variety of steps that you can take to start implementing a data-powered SEO strategy. These first steps in the world of machine learning and SEO will give you a suitable framework that you can build from.
It’s a simple fact that if someone stays on your website for longer, then search engines will reward you for that with a higher SERP ranking. Website structure is essential for ensuring that potential customers are directed through a pre-set customer journey that leads to an action. Whether your intention is to make a sale, get a social media share of your content, or to get a sign-up to your email newsletter, a streamlined navigation map is essential. A good place to start is with Google Analytics. This will allow you to see just how differently your web pages are performing in terms of length of time visited. Check out the ‘Behavior’ tab in Google Analytics and start looking at the range of insights that you can gain access to. You may see that one particular page has a much higher bounce rate than others, indicating that changes need to be made. From adding CTAs to aid both navigation and meet your goals, it’s never been easier to use data to evaluate existing website performance.
To create the right content, you need to know what your website visitors are looking for. If you have an existing search bar function embedded into your webpages, the data from that addition alone can provide you with a variety of insights. Again, Google Analytics is the first port of call when you’re looking for answers. By using the data that tells you what people were searching for either before they got to your website or while they were visiting, you can then start to create the content that you know they are looking for. That could mean adding product descriptions or links into existing content or restructuring your landing pages to allow for more immediate value to users. On Google Analytics, head to ‘Acquisition’ and then to ‘Queries’. Ideally, those queries should be related to your industry, and by identifying what users are searching for you can then create the content that will best answer those queries.