In last month’s post we talked about visitor loyalty and how it can help you gain insights around the loyalty of your visitors. Especially for websites with longer buying cycles (like admissions sites), visitor loyalty is essential.
Now let’s talk about visitor recency.
Visitor recency is simply taking your returning visitors and it measures how long it’s been since they’ve come back within a certain date range. In other words – how loyal are your returning visitors within the specified timeframe?
So who cares about visitor recency? How can it help?
Let’s take a couple of scenarios.
Scenario #1: you run a blog (maybe a student, admissions, or alumni blog). What is the goal of the blog? Whatever the goal – engagement, conversion, whatever – you need people to come back, right? We went over visitor loyalty last time. But, you don’t just need people to come back, don’t you want them to check back often? If you post fresh content frequently, you want people to come back frequently to check out your content. For a blog, we want “high” visitor recency. In other words, we want people to come back often within a day or 2 or 3.
High visitor recency looks like the image below – visitors usually come back within a week. Depending on how frequently you update your posts, *high* visitor recency for your blog might be different. For instance, if your blog was updated multiple times a day, you’d want people to come back more frequently than a week. High recency for you might be within 1 or 2 days.
Scenario #2: You run the admissions website. Although you want your visitors to come back, how many visitors are going to research the school, start the application, and submit it all in one visit? Not many.
Unlike the blog, although we want these visitors to come back, they probably won’t come back as soon as the blog visitors. The buying cycle is too long for this crew.
The example below isn’t a perfect low recency example because there is a distribution at the high-end, but pay attention to the distribution at the bottom. Notice how there is a much higher distribution at the bottom than that of the blog (above). The below website has a much lower recency.
Notice also that I filtered out new visitors. If you don’t filter out new visitors, Google Analytics will show new visitors in the first row. The distribution will be different, however. This is because the percentages will be based on all visitors. When you filter out new visitors, the percentages will be based on all returning visitors, not all visitors. This way you’ll get a better idea of the distribution for your returning visitors which is what you’re looking for with Recency.
When should I use Recency as a key performance indicator?
Although I probably wouldn’t use Recency as a KPI for a website whose target audience has a longer buying cycle, I would definitely use it for a blog or other website where the goal is frequent engagement – you not only want people to engage – you want them to engage frequently and often.