Data Mining in SEO: How Big Data Conquered Search

Jein Funk Jein Funk January 30, 2018 Category Search Engine Optimization (SEO)

Big Data, data mining, Big Data mining. You’ve probably heard, used, and maybe even overused those buzz words when convincing clients how you can take their business to the next level. However, the terms represent more than just the winning part of your sales pitch. Their sudden ubiquity and resonance are a sign that we’ve entered a new era in the way we approach digital marketing and search engine optimization. In this post, we’ll dive in to unpacking the terms, studying their relevance to SEO, and going over some best practices for telling a data-driven SEO story.

Defining Data Mining and Its Place in Business Decisions

To some extent, Big Data and data mining have become blanket terms that sum up a newfound reality:  all digital behaviors are now both data-driving and data-driven actions. The practice of data mining relies on analyzing large sets of information to detect patterns and qualities that you can then leverage to create optimized efficiencies or new opportunities within an organization.

Google-Mapping your route, posting to Facebook, ordering in from Seamless, streaming your Netflix faves – all of these activities trigger new data streams that their platforms capture, analyze, and utilize to predict your next move, meaning the internet can probably predict your next sushi craving better than you can.

Data mining applications can include:

  • Detecting patterns of waste that lead to cost-cutting measures
  • Predicting purchase behaviors and driving sales with relevant product suggestions
  • Identifying slower periods to properly plan for down time
  • Unveiling new opportunities within a segment of customers

Once the prerogative of computer scientists, quants, or model-risk analysts, data mining techniques are now used by nearly every industry or profession that has access to large sets of data. Like a gold digger during the Klondike Gold Rush, your job is to wade through streams of information in search of a small nugget of data that can actually help you.

A trailblazer in building big databases, Amazon pioneered the way businesses integrate big data collection and analytics into their operations and DNA, offering scalable solutions for data warehousing, clickstream analytics, fraud detection, recommendation engines, event-driven analysis, and more. Their innovation paved the way for businesses to audit their own levels of data access and the marketing possibilities that access presents. Today’s consumers are not only comfortable with having their online behavior documented, but they downright expect the businesses they interact with to be simplifying those interactions through data mining. This predictive ability is now the Holy Grail for many consumer-facing organizations, with the quality of their data analysis being a key component in maintaining a competitive edge in their industry.

With so much information at businesses’ disposal, there’s no excuse for basing decisions on intuition or habit. Internal stakeholders must now band together to not only unearth data patterns but to also advocate their path through bureaucratic hold-ups and into actionable status. Organizations must harness their improved understanding of consumers to drive customer service, product satisfaction, successful marketing, and, ultimately, growth.

Optimizing the Relationship Between Data and Search

Search engines are the ultimate consumer-facing organization, with users having dictated the business model’s evolution since the inception of online search. The mission of Google, Bing, and their counterparts is to deliver relevant answers to their users but, like any other businesses, they have to maintain a profitable model to keep operation going, which in their case relies on driving traffic to the most relevant information possible at the exact moment users need it to make a decision. Google dubs this point the zero moment of truth (ZMOT). Unsurprisingly, this business model is surreptitiously impacting the way we, as digital marketers, approach search engine optimization, as well as the way we analyze data stemming from analytics platforms.

Data Mining SEO activity can be summed up as analyzing large sets of data in order to identify new traffic patterns and unveil niche opportunities. These niche trends are then leveraged to better market a service or a product to a segment of users.

Smart and actionable SEO tactics rely heavily upon data mining, which involves:

  • Pulling data from Google Analytics, Omniture, Webtrends, and other tools
  • Finding abnormalities in traffic, behavior, or conversion patterns
  • Understanding what these abnormalities mean for your clients and their business goals

Abnormalities that you want to look for include sources of traffic, simple and long-tail keywords that drive individuals to your site, and traffic trends over time. For example, year-over-year growth, seasonality, and how all of these factors relate to the sources of traffic.

Once you’ve unveiled underlying trends from large sets of data, you need to switch up your SEO strategy to tell the right story based on the findings. Quality data mining can open up a wealth of storytelling possibilities but, having all those options isn’t always a good thing.

To make sure you’re focused on the right story, you have to:

  • Be specific enough in targeting search terms
  • Have integrity and not tell false or misleading stories
  • Have an end-goal or metric type in mind for your data mining
  • Take control of process and only target patterns when they truly exist, instead of finding dubious connections just for the sake of doing so

To further set yourself up for success, make sure you’ve established Key Performance Indicators (KPIs) to benchmark your performance against goals that matter to your clients and that stay relevant to the realm of organic acquisition. Then, make sure you’re consistently monitoring your progressive and revising strategy when it doesn’t seem to be measuring up.

Stay away from bi-weekly period analysis, or even month-over-month analysis, when studying and reporting on Google Analytics. Unless you want to measure the short-term impact of an on-page change or assess whether seasonality is at play, you should always look at the bigger picture –and thus, the bigger timeframe. That’s when data becomes big enough to be both meaningful and actionable.

Exploring how Data Mining SEO Can Help You

In SEO and business analytics, what matters most in Big Data mining is what comes after:  increasing ROI through smart data utilization.  If you’ve been asking yourself how to achieve that goal but haven’t yet found a satisfying answer, then it’s high time to connect with our team of experienced data miners. For a free consultation about how we can help you use Big Data to generate even bigger results, contact Path Interactive today at (212) 661-8969.

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