6 SEO Analytics That Improve Your Customer Journey on Search Channels

Great marketing points to excellent customer experience and the moment you start delving into the realm of customer experience, it'll lead you to a customer journey map.

The customer's journey is comprised of behavioral or experiential data generated using data-driven and anecdotal research. Mapping the customer journey forces organizations to look outside-in -- instead of inside-out -- to become more customer-centric. Companies need to reconfigure the way they do things to truly embody being customer-forward, especially if they wish to entice first-time customers.

Some customer journeys consider search activity as one of its stages -- a subset if you will. The reality, however, is that search behavior fills a huge bucket in any customer journey because humans are seekers of information -- especially now when information is almost instantaneously available whenever users demand it. The graphic below highlights this relationship between search activity and the customer journey.

As search engine optimization (SEO) experts, we have gone far, in terms of our scope. But, it's clear that growing traffic is no longer enough. We've shifted from using SEO to grow traffic to using it to grow conversion and revenue. So, for SEO experts, it's worth zooming into search activities to find out which stages can be optimized to improve the customer journey.

Journey-Focused SEO Optimization

Google has evolved from a mere Q&A form into a journey-focused search engine. Your recent search activity, current location, voice and audio recordings, activities from partner sites, and interactions with other Google products are used to predict which stage of the buyer's journey you're in. And, Google tells you this upfront with the copy highlighted below.

Additionally, Google has found that no two user journeys are exactly alike. Search results now change based on user intent, which depends on many factors like user behavior, previous searches, seasonality, location, and what we might call "search sentiment" -- how search engines use your query to interpret your attitude or feeling toward a particular topic. This non-linear search behavior is evident in several of Google's latest core algorithm updates, such as Hummingbird, RankBrain, and BERT.

These updates make it easier for users to find information through Google Search. They have different machine learning features that analyze user intent and display results that are most relevant to the user's search. That way, you're not just getting SERPs that match your keyword, you're getting SERPs that match the keyword and the context behind it.

And, this personalization affects how Google's users are searching for and finding information. Think With Google uncovered these interesting statistics that describe how people are now using this popular search engine.

• 82% of smartphone users consult their phones while deciding which product to buy. One in 10 end up buying a different product than they had planned.
• 31% fewer customer touchpoints are included in the customer journey when people begin their research with a search engine.
• Almost 60% of shopping queries on Google Search are upper-funnel searches, in which users seek inspiration to narrow their options from a broad category to a specific product.
• 39% of purchasers were influenced by a relevant search.

So, how can SEO experts leverage this information? Let's explore a few ways in the section below.

SEO Analytics That Improve Customer Journey

SEO professionals need to "crack the code" on understanding context, user intent, and the searcher's journey stage to create content that matches their level of interest at each stage. Addressing those micro-moments of truth is key to your success in Google Search.

To do that, you need to have the right SEO resources available to optimize for the customer journey. Let's look at a few of those core metrics below.

1. Intent-Based Keyword Research Data

There are many ways to determine user intent, such as using a guide to understand search intent, creating your own machine learning program, or doing it at scale via existing SEO platforms. For example, you can use a keyword tracking tool to categorize keywords by top-ranking SERPs. This will help you determine the terminology you should use to attract the most visitors.

For machine learning, there are tools that can categorize a list of keywords by user intent. An API script, for example, can analyze thousands of keywords at once and highlight different types of user intent. This can save you a great deal of time, especially when the results are color-coded, similar to the graph below.

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You can classify keywords into three different types of user intent: Informational, Navigational (including local intent), and Transactional intent. Let's look closer at each type in the subsection below.

Classifications of User Intent

1. Informational Intent - The user looks for specific information and answers queries on a particular subject.
2. Navigational Intent - The user searches for a certain location or shop, wants to go somewhere, or visit a specific website. You can include local intent here.
3. Transactional Intent - The user wants to transact, purchase a product, use a service, or compare items with commercial purposes now or in the future.

After identifying your user's level of intent, map it to specific keywords and target pages -- both existing pages and those you want to create. When you first audit your existing content, you can see if those pages make sense for the user's intent, or if the content should be updated or repurposed.

The idea is to produce pages that address every relevant stage of your customers' journey -- and find gaps in that journey that you can fill with new content

You may have to do a cost-benefit analysis to determine if it's worth producing those types of content and features, to serve potential customers based on their intent. For this, you may want to look into customer lifetime value (CLV).

2. Click-Through Rate (CTR)

This isn't considered a ranking factor, according to Google -- though its effects on page performance are hotly debated -- but CTR does provide you some compelling reasons why you'd want to improve metadata and generate more click-throughs. CTR is at least indirectly tied to your page's search ranking position. You can, however, use some benchmark data on organic CTR to know if your pages are performing well -- or at least within striking distance -- based on the intent-based CTR standards.

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To accomplish this, you can use Google Search Console to pull your Search Performance Report. Start with choosing a filter by date range and search type. I usually use 28 days and "Web" options, respectively.

While on the "Queries" tab, you can further filter the results by Position and CTR. I normally choose "less than 6 positions," so you get the top 5 ranking queries, then set the CTR based on the industry-standard using the lowest CTR among the search intent.

Next, select specific queries on the filtered results, and click on the "Pages" tab. The result will provide you actionable insights on how your pages are performing.

Using the illustration above, there are opportunities that can be taken to improve your page title and meta description. More importantly, you can go further in auditing and consolidating pages based on the content-to-user-intent fit. Over time, these pages with low to zero CTRs (if left alone) would eventually drop in position, or stop ranking for certain keywords altogether.

The only possible consideration to retain those pages with super low CTRs would be if they're serving users as navigational pages to help them find what they're looking for. But be careful; they could be deemed "thin content" and penalize you if they don't provide enough value to the visitor. Check the Google Analytics Users Flow or your favorite heatmap tool to accomplish this.

3. Dwell Time, Bounce Rate, Average Session Duration

Dwell time measures how long a user spends on a page before clicking back to the SERPs.

Web pages' dwell time can provide you a glimpse into how users coming from organic search interpret the relevancy and quality of your web pages. The one challenge here is that the dwell time is a search engines' guarded data. Zipped, private, and difficult to access.

So, what's the next best SEO data to look at?

The answer would be bounce rate, pages per session, average session duration and UX test data. Bounce rate and average session duration are indicators of how your website is being used when visitors find value from it. For this specific data, you can use Google Analytics' benchmarking feature to find out how you compared to your competitors.

If you've enabled your benchmarking capability on your Google Analytics before September 2019, you can access your past data. See the figure below.

As the saying goes, "You cannot manage what you cannot measure". This is true with dwell time, but you can use other metrics like average session duration, bounce rate, pages/session, and behavioral data. Such information can provide you useful ideas on how you can improve your web pages' stickiness.

So, don't get obsessed with dwell time. Rather, apply UX best practices and check out how your metrics improve versus your competitors. You can also set a minimum target for your bounce rate and average session duration, and work to improve it.

4. User-Centric Performance Metrics

Improving page speed is, without a doubt, one of the key SEO activities that can enhance a customer's experience on your website. And, it's a ranking factor. So, if you want a sitrep on your page speed, fire up your Google PageSpeed Insights tool, and investigate which elements are affecting your load time.

However, you shouldn't only be testing for page speed. User-centric performance metrics can give you better context into page performance as a whole.

So, which SEO analytics data should you be concerned about, in terms of page performance? Here are a few user-centric performance metrics to consider.

You can also open Chrome DevTools by simply inspecting your browser with your web page loaded. Click on "Inspect" and jump to the "Elements" panel, if you want to view your page in DOM or CSS. You may want to navigate further on the "Console" panel to see how the page's JavaScript and other assets are affecting its load time, adding page weight, addressing unnecessary resource requests by the browser, and how CPU load is affecting total performance.

The other tools you can use are WebPageTest,Lighthouse, and GTMetrix, which detect similar issues affecting web page performance.

5. Site Architecture, Information Architecture, and Internal Linking

Site architecture helps with navigation and how search engines crawl your website.

For SEO, good internal linking and categorization matter because they help distribute page authority (sometimes called "link juice"), value, and PageRank within your website. Links, both from external pages and those within your domain, give search engines signals on which pages are most trusted on certain topics, which pages are related to other pages, and which are less important. It's all about the interconnection and findability of your pages.

On the other hand, information architecture also organizes the content flow of your website, making it easily digestible by a user through proper information structure. Your content should lead customers to the next steps that you want them to take, matching their intent with the pages they want to consume.

More often, any bad content organization on your website will result in frustration among users, making them leave your site and never go back. Broken links, confusing taxonomy, infinite redirects, 404 errors, and similar interruptions can result in crawling delays or link equity issues -- if you have multiple URLs for the same content, inbound links may point to more than one place. Since inbound links are a ranking factor, this impacts your content's visibility on search engines.

There are many ways to gather the SEO data related to your site and information architecture. Try using Screaming Frog to visualize the site architecture and internal linking structure of your website if it's under 10,000 pages.

At times, the data you can export from your favorite crawling tool into a good old spreadsheet is enough to do the trick.

Below is a classic example of problematic site architecture: the big red dot is not indexable. But, you can't easily see this problem using the table-format on the left; however through the Screaming Frog visualization on the right, the issue becomes more obvious. Since the red dot isn't indexable, all of the content linking to it is difficult to crawl as well.

Even if the page may have a strong PageRank, the distribution of its "link juice" will be divided into potentially hundreds of pages, if not thousands of pages reducing its link's strength. Also, from a customer's standpoint, there's only one entry point for them to visit a broad set of pages. Potentially, it could get too deep to navigate.

You can also put more SEO data into the diagram such as link score, and data from Ahrefs, Moz, Majestic, Google Search Console (GSC), Google Analytics (GA), and more.

Below is another visualization of the website using a tree diagram. Pay attention to the orange and red dots, respectively. When minimized, the website looked in good shape, but when they were "bubble burst", it became apparent that a large number of pages somehow got cut off from the website.

6. Audience Data and Segmentation

When you deal with SEO analytics and the customer journey, you can't help but dig deeper into the trackers you use. Google Analytics, for one, provides a huge advantage for SEO experts wanting to understand their audience profiles.

If you've set up your Google Analytics properly, you may have accumulated enough data to understand your audience's Affinity Categories, In-market Segments, Cohorts, Gender, Age, Geolocation, New vs. Returning Users, and more.

I particularly like to use Cohort Analysis, to help you understand churn in between date ranges such as by day, by week, and by month when you segment the cohort sizes. You can set up the custom segment to "Organic Traffic" or whatever parameters you would like, as long as you are segmenting your traffic source. Set your "Medium" to "organic"; and, if you want to be more particular with Google organic traffic, you can further set up the source to "Google".

The data on the right side gets more interesting once you start plugging in parameters like Behavior and Demographics data.

In the above illustrations, we wanted to find out the profile of our audience who are relatively sticky, having greater than or equal to three sessions, and a session duration of three and above. We also set up the Affinity Category to "Banking and Finance and Investors" to see if those are actually our "sticky audience".

You have the liberty to define your own "sticky audience" based on your industry, your minimum set benchmark or target. There are many combinations you can do with the custom segment capability of Google Analytics. As long as you set your "Medium" to "organic" and set up your "Source", then you're good to go.

The data above provides you an in-depth walkthrough for how you can implement SEO analytics with your customer journey. It should provide you with all the details you need to optimize your site and create a better user experience.

So, before we conclude, let's wrap things up by summarizing how you can leverage this information with your SEO and customer service teams.

SEO Analytics and Customer Journey Best Practices

1. If you turn every relevant search query into a meaningful experience on your website, you'll bring your customers to the next stage of their journey almost effortlessly. It should be deliberate, by design.
2. Don't mind dwell time so much. Instead, look at your site's bounce rate, average session duration, page/session, and user-centric performance metrics to improve user experience. Aim at being sticky to your audience.
3. Better internal linking distributes PageRank to your website, while excellent site architecture lets search engines categorize your website properly. Most importantly, they help improve the navigational experience of your customers.
4. Business and marketing executives' strategies should seriously bake in SEO, given that search activities happen online, no matter how unique they are.
5. Behavioral data is of great importance to understanding the customer journey on search.

For more tips on improving the customer journey, read how HubSpot created its customer journey map.