If you’ve been around the world of service management in recent years, you have no doubt become increasingly familiar with the concept of shift left, a strategy for shifting your support services from higher tiers toward lower tiers and from lower-tiers toward prevention and self-service. Many support organizations have taken this methodology to heart and have adopted self-service portals that enable their users to view and consume services and knowledge at the click of a button. But how do we know that our self-service portals are effective, and what are we to make of our ever-growing analytics and telemetry?
How do we know that our self-service portals are effective?
A benefit of many self-service portals is that, as websites, they can provide us with access to analytics data and metrics. But some of those metrics can be a bit confusing. To clear the air, let’s review some popular analytics terminology:
Know the Basics
Users. The people visiting your website. This measure shows you how many unique people or devices are visiting your pages.
Usually the analytics tool will use its own fingerprinting or algorithms to determine how to group a visit to a specific user.
Number of users can be a handy metric to see how many people are visiting your portal. Generally higher is better. Although if your analytics show 50,000 users and your organization only supports 5,000, that may inspire review.
Sessions. A session is one specific browsing period on your website by a user. Sessions are typically separated by a defined period of inactivity between visits to your page.
Sessions are helpful because they can start to show repeat visits and how often users are coming back.
Pageviews. A pageview is perhaps the most recognizable metric for web traffic. This number is the one that used to be counted on the bottom of webpages everywhere. A pageview or impression represents a single visit to a piece of content or endpoint on your page.
Another term used with pageviews is “unique” pageviews. A unique pageview only counts one view for content per session by a user, while the total count of pageviews can include multiple visits to the same page.
Similar to user count, pageviews can be used to see how well utilized your portal is.
Session Duration. This metric shows how long users are spending on your website during a browsing session.
Longer session times tend to be favorable. However, there is likely a “sweet spot” for session duration. If a user is spending too long browsing your content, this may show that they are lost, having trouble finding what they need, or are confused by a piece of content.
Gather Demographics and Location
Location. Location information shows where your users are accessing your content from. This information can be as granular as certain geographic coordinates but is usually more abstract to city.
If your organization operates across multiple locations, you can see if your content is being served to those regions effectively.
User Demographics. Some analytics platforms will provide aggregate demographic information about your users, including sex, age range, language, and more.
Some of this information can be valuable in determining which populations are consuming your content. A university, for example, could look at age ranges and see if both students and staff are using their portal. Identifiers like language can be helpful in determining needs for translation or localization and can help inform content review for inconsistencies that might be lost in translation.
Technology Demographics. Technology demographics include information about how a user is accessing your content. This generally includes information about their web browser, operating system, device type, and resolution / aspect ratio.
This information, similar to the user demographics, is valuable in determining how your users are accessing content. A large benefit here is making sure your content meets the needs of the users that are attempting to use it. If 80% of your traffic is mobile, then it makes sense to invest resources in making your portal mobile-friendly. Conversely, if less than 1% of your browser traffic is using an older version of Internet Explorer, your team might not need to worry about compatibility.
Understand the Value
Content Views. Perhaps the largest value of analytics is being able to slice the results to understand what users are doing on your pages. By looking at how popular certain pieces of content, or features are, you can determine which content to focus more attention on for continual updates and improvements.
This information also lets your team know which content might be obsolete, or hard to find, because the analytics will show which pieces are not being used.
Trends and Correlations. By applying time dimensions to our analytics, we gain the power to assess and expose trends in our data. These trends might be simple, such as the days of the week or times of day that our systems are being used.
These trends might also be linked to external events. We can track a spike in visits to a system outage or to an email we’ve sent. By looking at the shape of our data over time, we gain new insights into how we can best support our users.
Sources. By tracking how a user ended up on a given piece of content, we can learn more about how our portals are being used. This applies to external sources, such as social media or search engines, but also internally within our portals. By looking at the path a user took to get to an article, we can uncover areas for improvement. An indirect path or a longer route might indicate opportunities to streamline our information architecture.
Apply the Insights
Running analytics on our self-service portals is a simple yet powerful way to better understand our users. By understanding the various metrics out of our analytics, we can then improve the quality of our self-service offerings and help enable a further shift-left.
Chris Chagnon is an ITSM application and web developer who designs, develops, and maintains award-winning experiences for managing and carrying out the ITSM process. Chris has a Master of Science in Information Technology, and a bachelor’s degree in Visual Communications. In addition, Chris is a PhD Candidate studying Information Systems with a focus on user and service experience. As one of HDI’s Top 25 Thought Leaders, Chris speaks nationally about the future of ITSM, practical applications of artificial intelligence and machine learning, gamification, continual service improvement, and customer service/experience. Follow Chris on Twitter @Chagn0n .