The average time spent on page is the casino of content marketing: Everyone plays to win, few hit the jackpot, and the games feel rigged. Why? If you ask three data analysts to measure time spent on the same content, you’ll receive three different results.
One of them might pull numbers from Google Analytics. Another from Adobe Omniture. The third from an in-house platform (Globe Content Studio, for example, uses Sophi.io, an analytics programme developed by parent company The Globe and Mail).
All of the analysts would agree on the definition of time spent. None of them would use a universally accepted measurement because it doesn’t exist.
Digital marketers have been ruled by pageviews since the early days of the Internet. Reach was the goal. The more impressions, the more click-throughs. The more click-throughs, the greater the chances of landing customers. With the emergence and growth of content marketing, engagement has become increasingly important, and time spent is the leading indicator.
The challenge is two-fold: A click is a click. However, not only is time spent on a page measured in different ways, but few marketers are providing (sell-side) or demanding (buy-side) details on how it is generated. Will a single source or methodology ever realistically be adopted? Not without a fundamental shift in the industry. That’s why transparency in the calculations is key, which means providing metrics but also explaining where and how they were calculated.
As Hubspot has pointed out, “average time on page is contextual. What’s ‘good’ depends on the type of Web site you have, the industry you’re in, and the Web page you’re tracking, among many other factors.” (As a side note, content format or design can also impact time spent.)
These factors make benchmarks tricky — not just internally but also when they’re measured against the competition. This can’t be done apples-to-apples unless you know exactly how all sides arrived at their figures.
Data analysts at most organisations are not involved in setting up their data inputs, or they are using third-party platforms. They have a set of tools to work with that typically fall outside their control, and data scientists, even if they’re asked to change an approach, often don’t see the need or they may not agree with proposed changes.
From a big-picture perspective, Google Analytics is a great example. Users will tell you they “know” how Google Analytics measures time spent, but unless you are an engineer at Google, it’s likely you only know what you’ve read online, and Google has not posted the formula. It remains a secret sauce. Should there be more transparency? Absolutely. Is it coming any time soon? No.
Distribution channels such as social media platforms have their own forms of measurement with the same challenges for users.
So, what’s a marketer to do? Whether you’re using an in-house or third-party data platform, ask questions about the methodology for determining time spent. If you’re a content buyer, find out which data sources are being used to supply campaign performance and demand to know how the numbers are calculated.
A logical next step is to evolve beyond pageviews and time spent as the be all and end all for content marketing performance.
Let’s imagine the majority of people who clicked through to an article on your Web site actually read most of it and logged an average time spent of more than three minutes. Why does that matter? Did they buy anything? Did they take any action? Do they remember what they read? Did they form a positive association with your brand? Did they share the article?
That’s the next frontier: Content marketing is not typically a bottom-funnel tactic, but ultimately companies spend their advertising dollars to move products, sell services, prompt downloads of white papers, or otherwise extract value from potential clients.
Through the course of a day, users open apps, launch multiple browser tabs, and scroll through miles of social media posts — all while navigating a sea of “hands” waving for their attention.
A wider mix of metrics to measure success, which could include ways of capturing the value of both short and long attention spans, including any actions resulting from those engagements, could be the way forward. Mutually agreed upon, out-of-the-box universal algorithms that could be tweaked to fit the needs of any organisation would be an ideal starting point, and it would be up to individual marketers to provide or demand any changes made to the formula.
Time spent, like impressions or clicks, is a holdover metric that pre-dates smartphones, changing user habits, and other digital developments since the start of the millennium. Measurement models have yet to catch up.
They say it takes a village. This one needs to be built by marketers and data teams.