Em Kuntze

Conversion, when readers make the leap from being casual consumers of content to paying customers, is a hot topic. It’s easy to see why. A subscription model offers hope to a struggling publishing industry – dangling a potential for growth that doesn’t rely on diminishing advertising revenue. At first glance, the figures may look unconvincing, with subscription conversions only accounting for between 1.5 and 4 percent of readership, according to most studies. Here’s the kicker, though: those small percentages are very, very valuable to publications. Subscribers are worth 160x more than anonymous users, says Danuta Bregola of @gazeta_wyborcza at #DME18 pic.twitter.com/Ap6HjgGxYU — Content Insights (@InsightsPeople) 10 April 2018 Last April in Copenhagen, Danuta Bregula of Gazeta Wyborcza shared the above slide. Subscribers, she said, were worth 160 times more to the publication than those who didn’t pay. It wasn’t just that they had invested in the enterprise, it was that they funded the publication because they were invested in it. Those figures are striking: a subscriber reads 20 times more articles; consumes 20 times more advertisements (which are five times more expensive); shares links; promotes the brand; engages in discussions, and so on... So, her experience bears out something we’ve been wondering for a while now: with all of this in mind, and taking into account the fact that advertising is in decline, isn’t it worth spending a bit more time thinking about what loyalty means in a publishing context? Optimization: energy goes where your focus lies There’s a principle in yoga which states that energy flows in the areas you give your attention. The same is true with publishing. Our editorial energy has long been directed to where and how our businesses were optimized, and, for many, this was organized around an advertising model that necessitated volume. If newsrooms start optimizing for subscriptions, their culture, output and focus is very likely to shift on its axis. If newsrooms start monitoring and measuring ‘success’ based on this approach, there’s a very real chance that this 2 percent could grow to 3 percent – a 50 percent increase – or even to 4 percent, doubling income. That’s food for thought, right? So, here’s the million dollar question: just how do you grow that seemingly modest sector of your readership to deliver the kind of growth needed right now? Getting data-literate, becoming data-informed Publishers need to be looking more closely at their content – and at how they monitor its success. Those who run newsrooms know all of this. Of course they do. It would be too simplistic – and, frankly, patronizing – to suggest they’ve been blind to analytics and metrics of quality all this time. Many have – quite understandably – been dictated to by the needs of a business model driven by advertising revenue. But, let’s be absolutely clear, that doesn’t necessarily mean all journalistic integrity had flown out of the window. No, the difference was that the newsroom (or publishing outlet) optimized itself around whichever metrics were deemed most financially important. Publishers must, after all, publish. Volume-driven articles may not have been ideal, but, for a while there, we were all doing the best we could. That was then, and this is now. Newsrooms are becoming more data-literate. Sit in on any media conference and you’re likely to hear case studies of newsrooms that have made the successful move towards being more data-informed. We know it’s necessary – and beneficial. The trouble is, despite this growing realization, there’s still a knowledge gap – not to mention a skills one. In understanding that data-informed approaches should form the core of newsroom culture, many are incorporating these practices wherever they can. Sometimes these practices are innovative, exciting and productive. Sometimes they’re not. An example of the latter is the idea that tracking conversions by identifying which articles prompted payment was something worth monitoring. Yes, there’s data involved here. Yes, it’s great that publishers acknowledge that analytics input is valuable. But not all data is useful. Not all data is relevant. Not all data tells the whole truth. In the case of tracking conversions through specific articles, it’s a case of barking up not just the wrong tree, but the wrong forest. Here’s why. Through the lens of three audience behaviors When you’re looking at article performance, there are essentially three valuable behaviors. These three behaviours form the lens through which you apply the metrics you deem relevant to your organisation – and each serves a different purpose. First you have volume – the quantity that’s being consumed. Next you have engagement – that is, looking at how your reader is reading. Lastly, there’s loyalty, which seeks to explain the relationship between readers who’ve formed a sustained habit around your publication and what they’re doing on your site. The key type of user behavior which needs to be studied in the context of subscriptions, memberships and reader revenue is loyalty. With exposure and engagement, you’re talking about actions attributable to a specific piece – how many people opened it, how long they spent on it, how far they read through it – which means they can easily relate to a single article. Loyalty, on the other hand, requires an additional stage of analytical study. That’s because loyalty isn’t really about the article at all – it’s about human behavior. With loyalty, you need to first define who your loyal readers are. Once you’ve done that, you’re able to use that reader base to map loyal behaviour. Everything then becomes filtered through the human, not the article. Recency, frequency and volume are three things commonly used to describe mapping and tracking loyalty, and they’re all great places to start. But they are just that: the start. These metrics are measurable in different ways – and each way presents its own set of problems. At CI Labs, the Head of Data Science, Ognjen Zelenbabić, puts it this way: “If you calculate frequency, do you calculate it on session cookies or user-lifetime cookies, or what does it mean? How do you treat users who come several times during the day? Do you calculate them once, or every time they come? You have a bunch of different approaches just for frequency and also for recency. How do you combine them? What does it mean for you?” What’s the link between loyalty and reader revenue? So if that’s how these things should be calculated, what about the why? Good question. Glad you asked. It should be simple, really. Loyal users – those who are routinely highly engaged in your publication – are more likely to subscribe than random users. Consider your own experience: if you subscribe to something, two things are likely to hold true. Firstly, if you’ve taken out a subscription (and no doubt you have) it’s more likely you’ve made the leap after a period of getting to know the publication, reading the content and deciding it’s worth your money. Secondly, if you’ve retained or renewed that subscription, it’s likely that it’s something you’ve engaged with habitually. Publications spend a fortune luring new readers to pay for subscriptions and membership, but the real success comes in the retention of those subscribers – not necessarily in the acquisition of them. Free gifts or enticements of branded loot may catch some, but, if you’re thinking about lifelong value, the real gift is a reader who actually uses the product in question. If the reader isn’t quite there yet, then it pays to further engage them with the publication through informal newsletters and suggested reading before triggering subscription notifications and invitations. If the reader isn’t quite ready, give them time. So, what’s this about a ‘conversion fallacy’, then? We know we should use data to inform us of why and how subscriptions are working. How this is being done at present isn’t optimal, though. Most of the conferences we attended in 2018 featured at least one speaker talking about how they monitored which articles were acting as a trigger for subscriptions. It’s important to talk about this for a moment, because it’s a fallacy and it’s misleading. If you understand that low-churn rates are more likely to be associated with higher levels of reader loyalty and engagement, the idea that a single article should be lauded for converting a curious reader into a satisfied subscriber should set off warning bells. Especially given what we’ve just said about measuring loyalty itself. Why? Well, consider the following: Metered paywalls let you read a certain number of articles before the gates slam and you’re required to reach for your credit card. If the threshold is five, you’ve been enjoying the content and will feel moved to subscribe anyway, the 6th article is almost arbitrary. If you’ve built up a relationship with your reader base, understanding the sum total of that experience is more valuable than pinpointing a single article’s contribution to it. Higher-value subscribers – that is, those who’ve built up a sustained relationship with the publication and are likely to be a good, solid long-term (hopefully lifelong) paying readers – are of value when they’re assessed in the context of ‘loyal’. Now, while there’s absolutely value in working out how loyal users behave and what they read (and, for that matter how they read), looking at the correlation between single articles and subscription rates as a way to identify conversion isn’t so useful. There’s considerable complexity involved in this process. The thing that drives people to become loyal readers is trust. Even though a certain reader may have converted on a particular piece, the decision to do so came from previous experience with the publication. Readers only decide to pay once they’re sure they’ll be getting their money's worth. Publishers need to understand that they’re not in the business of selling separate items, but rather the whole box. Once they start to look at loyalty from a different perspective and measure it accordingly, they’ll be able to actually nurture their paying audience and help it to grow.

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