The job of most websites is to provide sufficient information to answer the visitor’s questions and compel them to do something. In higher ed, the action we want them to take is tied to enrollment – a business objective. The problem is, prospective students don’t visit a university website and apply as if they were buying a shirt. Their journey to that decision often travels a convoluted path. They may speak with a recruiter at a college fair, visit our website and those of other schools dozens of times, email back and forth with admissions, engage the university via social media, etc. It’s very difficult to accurately track the entire sales funnel for every prospect. So how then do we measure the effectiveness of a university website? I think we need to do it by creating a yardstick we know and trust – the KPI.
I’ve seen people use metrics (pageviews, sessions, time on page, etc) as if they were KPIs (Key Performance Indicators), which is not a good idea. While we can define a KPI any way we like, metrics are just numbers reported by analytics. Yes they have their use but they’re too granular and lack context to tell a story. It’s unwise to make adjustments to a website based solely on analytics. The number of pageviews, for example, cannot tell us the reason the users viewed the page, their intent or whether the users were bots or people. To get the full story – or at least get closer to it – we derive KPIs from at least two metrics compared against each other. Sales per session or clicks per impression for example.
The idea of a KPI is to provide a yardstick we can measure by and what we should measure is our progress toward meeting a business objective. The data provided by KPIs is often unique to each organization because each school has a unique blend of information architecture, content strategy, tools and tactics. But as long as the KPI is aligned with a business objective it will work fine.
… it’s not the KPI itself that matters but rather the baseline it provides
I believe the key is to realize it’s not the KPI itself that matters but rather the baseline it provides. For example, we know we can’t get a simple conversion rate like the number of visits it took to get an enrollment (if you can, I’d sure like to hear about it). So we need to choose metrics that help tell the story of the website’s effectiveness. How you create and interpret them largely depends on the details of the website. I had intended to build and prove this model at American University but I was unable to finish the work. So I’ll share the plan and my reasoning with you in hopes it will help.
I chose to focus on program content first because on average programs are the most important factor in a prospect’s decision of which school to attend. I reasoned that as prospects do their research and compare programs and schools, sooner or later they will apply if they’re interested and some of those applications will come from a visit to the website. For those that apply by following a link to the application from our website, we can track the content they viewed during the session that led them there. It doesn’t matter if this was their 10th or 100th time on the website because we’re interested in patterns of choice across many visitors. There will always be exceptions and user behaviors that don’t make sense at first glance but when we look at the aggregate behavior of all the users that did what we wanted over time, we will see a pattern to how the majority use our content and can begin to suss out what content compels them to act.
The metrics I chose to use for a KPI were the pageviews and click events on Calls To Action (CTAs) within the pages that provided a specific program’s information.
- Pageviews for ALL pages directly related to the program (overview, requirements, courses) whatever is included within the /program-name/
- Click events on Apply, Request Info, and Visit
The KPI was expressed in the form of a ratio: #clicks/#pageviews.
The fact that the KPI isn’t perfect doesn’t matter as long as it’s aligned with the objective. After a year of collecting data I expected to have a trend baseline to compare month to month and year over year. Of course I would have to be mindful of and account for the admissions and marketing cycles as well as other factors that may have an effect on the KPIs. Having the baseline would have allowed me to refine the program pages to improve their effectiveness and provide a way to measure the value of the changes. And because the creation and editing of content is distributed at AU, this would have also allowed me and the folks that managed the websites for a larger unit like a school or college – to keep an eye out for changes to content that may have a negative impact on the KPI.
It’s also important to note that KPIs for program related content are only one part of the picture for a university website. In order to get a more complete story of how our target audience uses the website, we need to create and consider the KPIs from other important content areas. I don’t mean ALL of the content on the website but only the content considered by prospects to make their decision to apply. Campus Life pages (pageviews against a Campus Tour CTA) and Financial Aid pages (pageviews against Request for FA Info) for example. Once we have the KPIs and the baselines for at least 3 months, we will begin to see patterns and can make adjustments accordingly. The important point is KPIs don’t need to be perfect. All we need to do is to create measuring sticks that are somewhat aligned with the objective of the content, gather and compare data over time, and be mindful of other factors that influence the data. Hopefully, I will get another opportunity to build the model and share what I learn.