The Big Data of the subscription economy

By Maria Terrell

M.Terrell Consulting

Dallas, Texas, USA


Being a blogger for the Satisfying Audiences vertical keeps me firmly focused on asking the question “Is this what our audience wants (or needs)?” as I participate in all things INMA- and news media industry-related. As you all know, the INMA North America division recently completed its INMA Connect: Educate, Engage, Experience event (or E3 for short). This was a new model for INMA with two deep dive-focused days — subscription models and video revenue, respectively.

As I listened to two days of speakers put together by your fellow INMA member peers in North America, I kept the audience satisfaction question top of mind and coffee close at hand. The presentations were timely, engaging, and sparked a lot of questions and discussions — and the most popular theme was the “subscription economy.”

This concept, although not expressly positioned, also rang true on the day focused on video revenue. It is honestly the design-thinking answer to the news media industry’s challenge.

I’ll explain. Quite simply put, the subscription economy is all about freedom.

Subscriptions are not limited to the news industry, as demonstrated at INMA's recent E3 event.
Subscriptions are not limited to the news industry, as demonstrated at INMA's recent E3 event.

On the subscription models day, speaker Monika Saha, general manager of finance product line for Zuora, opened our eyes to what this freedom is about in businesses outside the news media industry. The perspective was a bit mind-blowing.

From Caterpillar (which sells industrial equipment), to Fender (guitars), to GoPro (portable cameras/video), companies have changed their positioning and strategy from “buy my product” to “subscribe to the service/result/item you need.” Imagine … subscribing to dirt moving (via Caterpillar)?

Subscription companies, according to Saha, are growing nine times faster than S&P 500 companies. So, what’s a “subscription company?” What she noted is in the graphic below.

Subscription-based models have similar characteristics, regardless of industry.
Subscription-based models have similar characteristics, regardless of industry.

This simple definition brought to light the horror of the industry’s reality for many of us and the title of this blog post: “The Big Data of the subscription economy.”

Our keynote presenter was Eric Siegel of Predictive Analytics World. He opened the conference talking about Big Data and predictive analytics. It was a great presentation showing how vital understanding your data and using data analytics and predictive analytics are to our future.

It was great, but what’s he got to do with subscription business models? Let’s see, shall we?

The customer is known.

This seems like a simple thing that all of us should have. Honestly, that any business should have. Yet, how many of us are still struggling to get the data behind who’s buying our single copies? Who’s reading our online content? Who’s hitting our site for the “free” articles before the subscription gate? Who’s buying a day or article pass?

The sad truth is many of us are still working at newspapers — where “data analysis” isn’t part of the corporate culture or in the current set of skills for any department. We’ve got data out our noses, all in different databases, departments, silos, or vendors, with no one looking at tying it all together. We don’t know our customer.

Fundamental principle 1 = fail. Big Data need = yes.

The relationship is sticky.

This makes sense. A solid subscription requires people use it. Again, do we even know if people are using their printed product? Are the free products we send out in the market to high value postal codes even being read? What are the readership trends of those coming to your site — subscriber versus visitor? Who’s looking at the data to really say, “Yeah, we’ve got a sticky relationship, and here’s the data to prove it?”

Without data analysis, or data at all, we’re telling ourselves we’re sticky. But are we a fresh-wad-of-chewing-gum-on-the-bottom-of-your-shoe-in-the-summer sticky, or a 10-year-old Post-it note sticky?

Fundamental principle 2 = fail (likely). Big Data need = also yes.

Price is elastic to value.

During the subscription models day, I was happy to see many of us delving into this area. Representatives from The Washington Post shared their views on value elasticity and others chimed in with their elasticity strategies. But how many are in the game is yet to be determined. The bigger challenge is how many are looking at the data to understand their value/price elasticity? Big Data is striking again.

Principle 3 = semi-fail.

Fixed costs are lower.

Well, for 99% of us, this is a total fail out of the gate. Presses, buildings, and huge legacy costs to produce a product (printed newspapers) that we’re only keeping for the declining ad revenues, and justifications of our circulation to justify the ad rate for the declining ad revenues. It’s a circular logic that is painful to admit. We’re losing money to lose money … to slowly lose money?

Blowing up the current model of how we create and distribute our content in a way that is valuable is likely the most painful part of our reality. Most news media companies (at least in North America) will likely need to sell assets (such as buildings and presses), realign work forces (high-paid legacy print journalists for normalised pay multi-media journalists), and enter into partner relationships (such as outsourcing print/distribution and data analysis) to find the model that works in their market.

Sadly, how many newspaper company top brass are willing to make this move versus ride the wave of five to 10 years eeking out what they can from their newspaper before their retirement — and ultimately making this someone else’s problem?

Not a Big Data need, per se, but an objective analysis and honest reinvention of your structure using data? Yes.

Future revenue is highly predictable.

This one is a tougher nut to crack, as we can predict our current decline. So, winning?

But in all seriousness, there will never not be a need for news. People are consuming infinitely more content than in years past, mostly due to the freedom to read it in print, online, via app, or in a myriad of formats. I’ll say, yes, the future revenue is highly predictable, in that there will always be demand for quality journalism and news — just not in our current business models.

Again, this is where Big Data and predictive analytics are key. If you’re not looking at the trends and predictable behaviour of readers and potential readers, you’re not realising your highly predictable future revenues.

Boom. Big Data.

Behavioural data enriches the product/service.

This one is basically a neon sign saying, “Big Data, Baby!” If we’re not capturing and truly analysing behaviour, we’re losing the subscription game. As I said when opening E3 a few weeks ago, the industry that invented subscriptions is now getting its proverbial behind walloped by other industries that are focusing in on the subscriber economy.

Big Data = 1, News media = 0.

If a Caterpillar, a company that makes gigantic, specialised, heavy-duty industrial construction equipment has become a winner in subscriptions, we’re going to be OK. We’ve just got a little dirt of our own to move in the reconstruction of how we operate and what we offer.

About Maria Terrell

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