Analytics

Our Analytics Service provides digital business intelligence for NPR stations, answering key questions on audience reach, engagement, content, and monetization. Based on system-wide data, we share key trends, actionable insights, deep analysis, station best practices, and analytics training and support on all of a station's key digital platforms: live streaming, on-demand audio listening, website usage, NPR One, and more. At the core of the service are regular webinars and the custom measurement and dashboards of the Station Analytics System.

Looking for a specific topic from a webinar or blog post? Check out our index of analytics topics.

In the past our analysis has looked at user behavior to try and understand how different users interact with content and what drives them to return. In the September 2017 webinar we took a look at how station strategies play a role in the size of their loyal website audience (users who visit 3 or more times in a month). Here are 3 things we discovered:

Member Station website audience crossed an important threshold in July 2017. For the first time since NPR has been tracking aggregate station web traffic, there were more sessions on mobile devices that on desktop/laptop devices.  

Here's why it matters:

Twice a year we step back and look at the overall digital trends in public media. When we last looked at websites, in the fall of 2016, we saw that station sites were under performing the growth we saw in other local news sites. More recently we see that station sites are experiencing some growth while other local news sites decline, but none of them are seeing the tremendous growth experienced by NPR.org. 

What if you could find out more about how your members use your website? You could learn whether they prefer to read or stream audio content, how they get to your site and what programs they love. You could find out what emails they find most interesting and what types of gifts they want with their membership. If you are already tracking pledges using eCommerce tagging they you can learn how to use segments and standard Google analytics report. If you aren't tracking eCommerce yet, you can find tips and guidance on how to get started.

We spend a lot of time talking about user engagement, how to measure it and how to encourage it. We want to be sure that our content reaches the right audience, but when much of our audience only interacts with a single page how do we know that we are encouraging the right behaviors to build audience and membership? For each page a user sees we have a chance to encourage them to interact with our content but a single page of viewing only gives us one chance to capture their attention.

In an average week, 2.4 million people listen to public radio via NPR stations' live digital streams. Even though that number had been growing steadily over the years, it plateaued in 2014-2015, making us all wonder whether big growth in digital listening was only going to be about podcasts from now on.

Last week was our monthly analytics webinar, where we gather together the top insights across the system on both audience and engagement. 

As you might expect, election coverage was a big focus for the system this month, and we broke down  audience consumption of election coverage, as well as its impact on retention rate. And the results are significant: politics and election coverage had more than double the one-week retention rate of the previous 12 weeks. 

In the fall, when we did our last semi-annual PubMetrics presentation, the news about public radio live streaming wasn't great. After years of steady growth, we saw streaming cume and total listening hours level off.

2016 looks very different. Total listening hours are growing again, up 14% year on year for Q1 when we look at a broad range of 240 station streams. Cume is up 8%. More people are listening, and listening time per session also ticked up in Q1.

What's happening on your website right this second? How many people are there and what are they doing? Are there things you should know right now that could inform what stories you publish or where you invest more time?

For Core Publisher stations, we are launching the next generation of Community Calendar, replacing our old Public Interactive Events platform that we will retire at the end of this summer. We hope that you’ll be able to use the updated events functionality to engage your audience in real life, not just over the air or on your website.

Over the past few years we've used our station analytics data to learn a lot about our digital audience. Recently we've been looking at the characteristics and behavior of our users over a longer timeframe through a Google tool called BigQuery. We call this endeavor our Digital Conversion Study and have previously publish our insights about donors and our insights about repeat users.

In July, the Station Analytics team started an on-going investigation into the long-term site interaction trends that correlate with higher levels of site engagement and donation. Recently we shifted our focus from donors to repeat users of our sites with the goal of better understanding our loyal audience. Here's what we were able to learn about visitors who come to our sites more than once. 

By now you may have heard the news about an exciting collaboration amongst public media partners to develop new guidelines for tracking podcast audience metrics. Below is a bit of background information, details on how the new guidelines are being incorporated into the on-demand audio dashboards in the NPR DS Station Analytics System, and what the change may mean for your own podcasting stats.

New Public Radio Podcast Measurement Guidelines

In July, the Station Analytics team started an on-going investigation into the long-term site interaction trends that correlate with higher levels of site engagement and donation. This project uses Google’s BigQuery tool to load granular Google Analytics data starting from April of 2014 and building into the future. This tool allows us to analyze user data across longer periods of time than what is currently available in the Google Analytics interface and to perform more complicated custom calculations.

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