Content Marketing
What Is SEO Data Science? 5 Ways to Boost SEO With Data Science
Learn more about data science SEO and how to use it to supercharge your SEO strategy in our complete SEO data science guide for marketing and web publishing.
Are you tired of relying on gut feelings and guesswork to inform your search engine optimization (SEO) strategy? If so, SEO data science may be right for you.
Around ⅔ of leading marketers believe that data-driven decisions are better than those based on instinct.
Fortunately, thanks to artificial intelligence (AI) and other advanced technologies, it has never been easier to collect, analyze, and interpret massive amounts of data so that you can make the kind of data-driven SEO decisions that can get you to the top of the search engine results pages (SERPs).
Read on to learn more about data science SEO and how to use it to supercharge your SEO strategy.
SEO data science uses tools, algorithms, and other techniques to extract insights from massive datasets that can help boost search engine rankings. Its goal is to analyze the data and find hidden patterns and correlations that you can use to enhance your SEO strategy.
Of course, these insights aren’t exactly hidden — all the information you need is already in the database, ready for you to use.
However, with the sheer amount of data available, uncovering these data-driven insights by hand can be a barrier for busy content marketing professionals.
By automating data collection and analysis with data science SEO, you can let the technology crunch the numbers, freeing up time to focus on other aspects of your content optimization strategy.
Ready to see what SEO data science can do for you? Here are five ways to use its insights to improve your search engine rankings.
Every content marketer knows that high-quality content starts with comprehensive keyword research, and data science can help you take yours to the next level.
By understanding how, when, and why your target audience is searching for certain keywords, you can ensure your website provides the information they’re after.
More specifically, using data science in keyword research can help you:
For example, let’s say the data shows that searches for the keyword “pumpkin spice” tend to spike in fall. In response, you may want to create an article focusing on that keyword and publish it in October.
In a fast-paced industry like content marketing, anything you can do to stay current or even ahead of the curve is a plus. Analyzing historical data can help you predict future shifts in search engine or user behavior so you can proactively adjust your SEO strategy.
With data science SEO for predictive analytics, you can:
For example, if the data indicates that Google penalizes sites with AI content, you may choose to remove generative AI text from your site before it causes a problem. Fortunately, you can leverage technology for this by using an AI site scanner.
Did you know that B2B websites that load in one second have three times the conversion rate of sites that load in five seconds?
It may just be a few extra seconds, but a slow loading time can be a major hit to user experience (UX). Providing a good UX can therefore be critical for online success, and data science tools can help you optimize your site.
By analyzing past user behavior data and metrics, companies can:
For example, let’s say you find that your bounce rate has been high on a particular page for months. You can then analyze this page and make changes to its loading speed, design, or other factors to improve its UX and, by extension, SERP performance.
UX may not matter much if your site isn’t attracting the right users. Luckily, SEO data science is also useful for gathering and analyzing key information about your target audience. With this data, you can create more targeted buyer personas, which can help inform your entire marketing strategy — not just SEO.
When it comes to customer behavior analysis, data science can help you:
For example, a programmer may use customer purchase history and demographic data to build a model that predicts the types of products and services they may be after next, if any. From here, businesses can make data-driven decisions about the best way to retain and engage their customers.
Competitor analysis is one of the most important ingredients for an SEO recipe for success, and data science can help you out here as well.
By collecting data on what your rivals have been doing and identifying their strengths and weaknesses, you gain a competitive edge that can put your website and content on top.
When you apply SEO data science to competitor analysis, you can:
Consider using competitor data analysis for link building, for example. Once you identify good-quality links on competitor websites, you can predict their impact on your SERP rankings to see if they’re worth going after yourself.
SEO data science is an excellent approach to making data-driven decisions about your SEO strategy. However, it isn’t a one-and-done deal.
With technology and trends constantly changing, you need to constantly collect, analyze, and interpret data to find out what is and isn’t working for your business — and try new strategies to achieve your SEO goals.
Data, as with all things, is likely to change over time. The most successful content marketers know they’ll need to change to continue optimizing content right along with it.
