The post below was written by Paco Darcey, a Business Analyst at Clutch where he leads research on BI and data analytics.
Search engine optimization (SEO) is now search experience optimization, where the goal is not just to optimize websites and keywords to funnel visitors to specific webpages, but instead to optimize the entire experience of getting there. And even beyond that: optimizing the experience from search to “landing” on the website, to consuming content and finally converting.
Reader engagement has been a hot topic in the past few years, especially as content marketing and the value of user experiences in general have come under the spotlight. Furthermore, both the number of search queries and the amount of online content has exploded in recent years. In 2014 Google recorded over four million searches every minute.
The SEO industry has followed this trend and many SEO experts now focus on the bigger picture: not just SERP rankings and traffic, but also the entire search experience and what users do after landing on their websites. So optimization has extended from reader engagement up to conversion.
Looking at the Metrics
So what sort of metrics within Analytics should you be looking at to measure reader engagement? What can these metrics tell you about your webpage’s capability to provide reader experiences, and what optimization tweaks can you perform to improve?
Take a look at these metrics:
- Bounce rates – In simple terms, bounce rates measure how many of your visitors “bounce” back to search engine results pages (SERPs) after clicking through to your site. This means they didn’t find what they were looking for or weren’t that interested to further engage with your site and read more content.
Bounce rates aren’t that accurate, as it measures a single visitor when they “land” on the site and leave immediately after, or when a visitor “lands,” stays and becomes inactive (like when a reader finishes reading and opens new tabs and does other things on their browser or computer), and then leaves. So, even if the visitor has read through all your content, they could still be registered as a “bounce.”
Still, since bounce rates measure in terms of proportions or percentages, it’s a good barometer metric to gauge, among other things, the efficacy of your keyword targeting. Higher bounce rates might mean you’re targeting the wrong keywords, which means the traffic you’re getting from good SERP positions with your target keywords are people who aren’t interested in the content you’ve optimized. Also, page load times and other on-page elements could chase away your visitors, causing higher bounce rates.
- Page depth – Page depth is the number of webpages within your domain that visitors click through in a single session. For instance, they land on an optimized webpage you’ve been increasing SERP rankings for, then click through to a linked webpage for further reading, then leave your site. That visitor will register a page depth of 2.
Obviously, higher page depth indicates better reader engagement. The more webpages they visit, the more you understand what they’re after (by taking a look at the trail of webpages visited), and the more chances you get of at least increasing chances of brand recall if the trail of visited webpages does not end in conversion. If it does end in conversion, then you can trace the visitors’ mindset as they visit page after page and eventually purchase.
- Average session duration – This is exactly what it sounds like: the average time visitors spend going through your website. The longer they’re there, the better engaged they usually are. However, this metric suffers from the same issue as bounce rates when visitors become inactive during their visiting session.
A solution to this is using a tool like Woopra to configure a custom idle timeout setting. By default, Woopra tracks website movements such as mouse movements or keyboard strokes to know if a visitor is active. However, if you have a lot of video or lengthy content on your site, you might want to adjust the session duration to a longer period of time. This ensures that you’re appropriately tracking the session duration of your visitors based on your website content.
When combined with page depth, average time spent can really give you a solid indicator of whether you’re giving your readers quality content to digest.
These three are just typical examples of engagement metrics that can help tell you when and where to optimize. Analytics can show you patterns beyond traffic and visits to show you what else you can optimize. Furthermore, using top analytics software tools to monitor, display and investigate these patterns can be highly beneficial as well.
Adjusting SEO Based on Engagement Data
The examples of engagement metrics we discussed before is just the tip of the iceberg. When things like mobile SEO come in, the game becomes a little different, especially as Google gets further along its plans to create a separate mobile index from the universal index used for desktops.
So reader engagement metrics are here to stay, but what does this mean for your SEO efforts aside from wanting to always optimize pages for better reader experiences?
The first thing to remember is the entire evolutionary stage of SEO we are currently experiencing – from individual mobile indexes to artificial intelligence algorithms – all point towards the death of black hat tactics. There is simply no gain left from focusing wholesale on small, shady tactics that can potentially cause permanent penalties to your domain. That’s no longer an investment in optimization that’s worth the time and risk.
The second thing to remember is the flipside of the coin: the worthwhile SEO investments are ones that take a while to reap rewards and are rather labor-intensive and exhaustive in terms of contributing to improving the user experience.
Adjusting your SEO based on engagement data is already the norm, but keep an eye out for industry changes that reflect more of the same in terms of a holistic approach to SEO.
Paco Darcey is a Business Analyst at Clutch where he leads research on BI and data analytics. Before joining Clutch, he studied Mathematical Economics at the University of Richmond. Paco enjoys keeping up with the latest in data science, in everything from business to sports and board games.