The SEO/data analyst hybrid: Why you should advocate for data-driven decision making in a content-driven field
The digital landscape is continually evolving—and the major search engines regularly roll out new algorithm updates—so SEO specialists have learned to stay flexible and reactive. As the industry inches closer and closer to relying on comprehensive machine learning, data points, SEO professionals must again evolve with the times. Content was king—and in some sense, it still is—but more and more SEO professionals see the writing on the wall and are expanding their skill sets.
Here’s what you need to know to stay prepared and elevate your SEO strategy with data.
Understand the relationship between data and SEO
While the trend toward driven-data marketing may seem intimidating, it’s not necessarily a bad thing. Data-driven decisions are already a large part of the modern SEO’s skillset. Savvy, successful SEOs know to utilise A/B testing strategies, heat mapping, and engagement metrics to evaluate and consistently improve performance in real time.
As the landscape continues to shift, SEO professionals who adopt a data analyst’s mindset will be better equipped and stay more competitive than those who rely too much on older analysis and tactics. As SEOs gain more and more reliable and real-time data about our audiences, we’ll need the ability to get granular in terms of the data we are able to combine, reformulate, and interpret in meaningful ways.
Case study: Data-driven SEO to improve the customer experience
Here’s an example of what I’m talking about. As an SEO manager at Clearlink, I recently worked with a brand that was having some trouble managing all of the calls their customer service department received. The volume was higher than expected, and calls were not converting into meaningful revenue for the company. They knew something had to change, but they weren’t sure what.
To address this, we implemented heat-mapping on their website to determine problem areas for customers. We found certain areas of the website resulted in far more calls than others. This was due to a few specific factors, including prominent placement of a customer service phone number and abrupt ends to user journeys as they engaged with the website. We then looked at the customer service queries for a significant portion of these calls. We found many of the inquiries revolved around the same basic topics: things like company hours, basic pricing, and “troubleshooting products.
Having identified the problem areas of their website, as well as the topics these customers were interested in, we got to work. We modified the placement of the customer service hotline number and featured the sales hotline more prominently. These decisions were based on the data points we gathered from our heat maps, page-level call tracking, sale centre inquiries, and page intent.
We also featured answers to common questions on the website in easily identifiable locations so that customers didn’t have to call to get these questions answered. This addressed the abrupt ends to user journeys and as a result, revenue increased significantly. By the time we finished with this project, most calls were routed correctly between sales and customer service, and a majority of calls no longer referenced the questions we answered on the website.
SEO and UX: Creating intelligent CX
If you’ve been around for a little while, you might be thinking that sounds a lot more like UX and design work than SEO or data analyst work. Ten—or even five—years ago you would be right. But the rise in meaningful data has increased the need for marketers in all areas of a business to make UX decisions based on data.
Today’s SEO decision-makers are depending on what the data says about end results, and that has increased other departments’ dependance on SEOs who know how to interpret data. That trend will continue as data continues to become a bigger part of our professional and personal lives.
As SEO professionals, we come from many different backgrounds, and not all of them are data-centric. Many of us are content creators and use data to determine the success of our efforts. If you’re trying to convince people to start getting granular with their data analysis, you will undoubtedly run into people who don’t seem to care.
Lead by example
Unfortunately, every SEO at some time or another has to work with a team or organisation that don’t seem to value data, or with clients who seem more interested in the CEO’s preferences than our professional recommendations.
To convince others to value our data-driven insights, SEOs have learned to lead by example. But how do we do that when it comes to using data-driven decision-making? I know how much effort you put into it, but if you try to get others engaged in your spreadsheet, you’re going to have a hard time. It’s always much more effective to showcase potential end results to get people interested in your methods.
Where possible, make an impact by sitting down with your colleague or client. Tell them what you can determine about their website based on the data and how it can inform their strategy moving forward. Can you prove that better keyword research would have improved the performance of an article? Maybe you can point to a call to action that seemed clever and relevant but is actually underperforming and should be replaced. Actionable insights are always the best supporting arguments, and they’re the kind of thing that will get others interested in adopting a more data-centric position moving forward.
It’s also helpful to know your audience before you start pitching changes. C-suite team members are less likely to be wowed by your data and your numbers, for example. Instead, try linking your data to revenue impact and other more direct ways to advocate for your position.
Whoever you are, and whoever you’re talking to, give data a bit more credence the next time you’re evaluating your SEO course of action. Remember, as an SEO, you’re responsible for the success of your channel. Your job isn’t done once users hit the site organically. This means your focus must move beyond optimising for the highest intentful search volume. You must make data-infused decisions to maximise your channel’s profit and elevate the customer experience.
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