Membership teams have questions about how to build insights from web analytics and data. A few experts explain how membership pros can increase their data visibility and easily spot “dark social” traffic.
In the May/June issue of Associations Now, we took an in-depth look at a few associations that use web analytics to recruit, engage, and retain members long term. And based on what we’ve heard from you since that piece was published, a lot of you are thinking critically about web analytics and data collected from members coming to your website daily.
That’s great to hear, because this traffic can reveal a lot about your members’ mindsets. Take, for instance, the American Occupational Therapy Association, one of the associations featured in our magazine story. After the 2016 election, AOTA kept an eye on site searches by members and noticed a common search term: Trump.
“Our members wanted to know how a Trump presidency would impact things like healthcare reform, Medicare, and Medicaid,” says Stephanie Yamkovenko, AOTA’s digital editor. “But for a while our policy was to steer clear of using Trump’s name in articles simply because of the shock and awe factor.”
That spike in Trump-related search queries armed Yamkovenko with the data she needed to persuade AOTA’s public affairs team to change the policy to ensure that members could find the content they were looking for. The association quickly retitled and renamed content to match search term queries.
“Monitoring search can tell you a lot about your membership needs and frustrations,” Yamkovenko says. “You might make a decision or rule internally that you think makes sense, but then when you analyze your users, you’re able to see that you need to do it differently.”
If you’re just getting acquainted with your web analytics, a closer look at search-term queries can be a great starting point, especially if you don’t have a lot of resources or staff devoted to your website.
But let’s say you have a traffic analyst, audience growth editor, or outside partner, like AOTA does. In that case, you can get a bit savvier with your web analytics, linking online behaviors to the membership database.
Right now, AOTA is in the process of creating Tableau charts to map out how content performs and to get staff comfortable using a dashboard depicting both web analytics and membership data.
“We are pulling information from Google Analytics, our CMS, and our membership database to provide deeper context,” Yamkovenko says. “We can spot trends in groups of membership while maintaining privacy for the individual user.”
The underlying idea for the dashboard is to see beneath the surface. Not every piece of content that AOTA produces is meant for every member, and so success metrics can vary. With the new dashboard in place, Yamkovenko can break down page views or downloads based on a member’s category, career, age, or geographic location, among other characteristics.
“Let’s say we’re aiming for a small group of school-based practitioners with a single piece of content. If we got only 1,000 page views or downloads, but there’s 5,000 members total, then that’s a pretty great return,” she says.
Check Your Traffic Blind Spots
While you’re using analytics to see your members more clearly, it’s also important to be constantly aware of your blind spots. For starters, Yamkovenko says associations need to see their site through a mobile lens.
“You need someone on your staff to do a quick gut check, and say, ‘You know what? Last week 60 percent of people accessed our site through a mobile phone or tablet, so we need to change the way we post this content.’”
Another big blind spot is traffic that is commonly known as “dark social”—visits to your site without an identifiable referral source.
Typically, when a user enters your site, their referral sources tell you where they are coming from—maybe it’s from a Google search or from a social network like Facebook or Twitter.
But not every visit has a referral source. Specifically, if your membership content goes viral, you may start to see a rise in direct traffic referrals.
No, these aren’t people typing in a lengthy web URL to reach your content. More likely, it’s people coming to you from an unidentified traffic source—like direct messaging, links being shared in someone else’s newsletter, or mobile applications.
“There’s not a good solution for dark social. It’s more that you need to be aware of it,” says Conor Sibley, chief technology officer at Higher Logic. “When people take content from other sources and reshare the link, there’s the double problem that your traffic may not be identified or that it might be attributed to a faulty referrer.” Dark social is a common problem especially for apps and mail clients, he says.
Really, when it comes to identifying traffic referrals, analysts need a healthy degree of skepticism.
“For example, you can’t assume that one single source, like Twitter, is the main referrer driving the majority of conference registrations,” Sibley says. “Maybe someone copied that link from Twitter and pasted it into a newsletter. In that case, the traffic says it’s from Twitter even though it originated from the newsletter.”
What dark social comes down to is training, he says. Association staff need to be able to spot and understand good versus bad data. He suggests comparing performance to historical data or setting up automatic alerts that identify data irregularities early.
“You need someone or something to raise a flag inside your analytics system if one of your channels starts to perform disproportionately,” Sibley says. “And you need to always be ready to investigate in order to understand why there’s a higher percentage of unknown traffic.”