This post originally appeared on the Umbel blog. The Umbel Marketing team had a major role in editing, redrafting, and refining the original content.
“There are 4,448 active sessions on my website right now. Earlier, I had 1,502 active sessions. Currently, 65% are returning and 35% are new. Coincidentally, 35% of the audience is also coming from mobile right now, and since my site cookies don’t work on mobile, it’s safe to say that I actually have fewer new visitors than my analytics is showing.
OK – the NBA Finals GIF appears to be popular, as is the US-Ghana piece, though it doesn’t look like the traffic now is consuming as much content as the afternoon traffic usually does.”
This is a typical editor’s thought process and afternoon analysis on site content, and it’s a critical step to optimizing a website on which revenue depends largely on ad impressions. Unfortunately for this particular editor, the morning didn’t go so well.
“The higher-ups won’t be happy – we were supposed to have 5,500 uniques this morning alone, and an average pages per visit of 3.4. This will certainly impact our ad revenue for the morning. I can make a few adjustments to the copy and imagery on the page, but it is unlikely to make a huge impact, especially since its been a couple hours since publication.
I was relying on Taboola to help target the content to unique viewers or even find my regular visitors and pull them back to the site from wherever they are on the web, but their recommendation engine never works as well as I would like. The promised five pages per visit obviously isn’t stacking up against my current reality.”
What’s an editor to do?
There’s a Serious Disconnect Here
For all the “big data” about consumers and their digitized habits, those working in the digital media industry know surprisingly little when it comes to the people interacting on websites, playing games in mobile apps, reading content and purchasing products. The industry has gotten very good at quantifying the impact of what users are doing, but it continues to fail to create better in-property (website, app, etc.) experiences that get those users to come back – and come back often.
And a lot of that is because on the back-end, editors and managers aren’t using the data to tell a story. They are using the data to supplant a story – and that’s where the problem lies.
Audience Analytics Aren’t Enough Because People Aren’t Numbers
For most digital publications, the most important part of an analytics platform is the returning versus unique visitors metric. “Returning visitors” tells you how many people visiting your site now have visited your site before. You can add another filter to show where those users came from, tracking their cookies generally without their explicit consent, but the metrics make it difficult to understand their true motivations. It’s just numbers and landing pages – and with that, it’s nearly impossible to tell a story that explains what they are doing on your site to begin with.
See, all you know about your user at this point, whether they are new or returning, is that they are here. Some have been here before (though you have very little information on exactly what they were doing the first time they were here) and, if they like what they see, you can assume that they will come back again. Others are better analyzed through bounce rates, for which you’ll need both timely and evergreen articles to help balance out.
Yes, analytics gets you all of that data, and it’s certainly valuable information, especially when presented to the management team. It’s why analytics are great for reporting. Analytics are also great for understanding on-site or in-app behaviors on scale, and are a fantastic way to understand how your audience is finding you, how much time they are spending with certain content and where they are navigating next.
But analytics platforms have a fatal flaw – and it can’t be fixed with more analytics. See, analytics don’t tell a story. They don’t even let you build your own story. Sure, the best analytics packages are easy to implement, easy to use and easy to understand well enough to do significant levels of dashboard customization for differing departments, but they still don’t tell the story of who is coming and why. Only when you know those details, which makeup the basis of any well-written story, can you begin to understand how to optimize the narrative to make for an ending everyone wants to read again.
Storytelling Breeds Engagement, Engagement Breeds ROI
OK, OK – you may be saying to yourself, “Well, of course I have a story!” After all, you have a DMP that delivers content and ads to all of your users. You have an ad network that pads the CPMs on your remnant inventory. You have an expensive recommendation engine that surfaces relevant information at the bottom of every page. Isn’t that enough? Isn’t that my story?
Not exactly. What you have is a fragmented plethora of experiences that serve a limited purpose. A story ties all of those touch points together, creating an holistic experience that serves a long term purpose past a catch and release strategy. Storytelling via your audience data, rather than touch and go analytics, is a catch and keep opportunity that makes your content the type that services a premium audience. And a premium audience is actively engaged, in your content as well as your ads.
See, it is much more important to know that your uniques dropped this morning because two writers published their stories half an hour later than usual. Traffic was lower across the board, but there was a larger impact in New York City. That geographic audience likes to consume sports content earlier in the day and your site was delayed in providing their morning fix. That is the same of group of people that check back in around noon during their lunch hour to read slightly longer articles, though not always on the same subject. Because of those two writers, you might lose those views today.
Tomorrow, those writers will need to publish on time, not just to makeup for the lowered site traffic, but because you’ve crafted a content consumption story specifically for that New York City audience. Based on the audience data you’ve collected, with their permission, you already knew the New York City audience had a particular affinity for Jack Daniels, especially when you segment that audience down to those users who also read the sports section in the morning. Based on that information, you’ve sold Jack Daniels a premium sponsorship spot in that section, and missing out on those views means not only a drop in promised impressions to the brand, but also a loss of user engagement across multiple brands those users like (your brand and Jack Daniels). You’ll have to make those impressions up later in order to deliver the promised story to the partner brand.
Here, you have a story across multiple channels: that with your internal team, with your users and with your client. And each one of those stories is engaging, surprising and not light on the details, especially when it comes to a resolution that surprises and delights.
Your Story Matters – It Always Has
Stories, and software that allows you to tell those stories, help to make sense of user interactions and behaviors in ways that analytics cannot comprehend. Stories communicate internally and externally the why, who and how behind performance, while giving industry professionals the opportunity to do better next time.
At the end of the day, analytics tools are interchangeable – a number is always going to be a number. Stories, however, are unique and individualized. Stories leaves those whom have interacted with a narrative to share, a point of view to chew on, a meaningful metric about which to brag. Never let your audience, clients or internal team leave without hearing or contributing to the story. It’s the only thing that has kept people engaged since the beginning of humanity – and not even digital media can change that.