I wanted to take some time to talk about subscription services. Partly because I'm only just now understanding them, and also because it's the business I've been in for 4 years. Note that this post is meant to be a fairly simple explanation of subscription services, and is more geared towards B2C and media businesses than enterprise SAAS.
I think that the business model of services has some unique characteristics, and I want to make those as simple as possible for you to understand. Mostly, in the case that you find yourself running a subscription service (especially as it pertains to media) - you might understand a bit better about how to make your model sustainable and scalable.
To start, what is a subscription?
To me, the simplest way of putting this is; it's a contract between a company and a customer for an ongoing service that improves over time. We're familiar with our subscriptions to Netflix (or cable).
There are many textures to this ongoing relationship that are fascinating.
Subscriptions aren't static, and improve over time.
More and more, companies are switching to subscription services as it appears to fit more in line with the benefits provided by the internet. Because of how quickly things change, and because of frequent updates to software, buying things online is about signing up not just for a static product, but for one that will improve and change over time. This accounts for the rise in subscriptions. Because products today are fluid, not static.
You don't buy a piece of software as a CD and install it any longer, you purchase a subscription such that it is auto-updated over time.
The reason subscriptions work is becuase benefits of a subscription apply to both the customer and the company, because the company has a more predictable flow of cash, and the customer gets and ever-improving service. This symbiotic relationship works great as an incentive for companies to drive forward progress with their product.
Customers pay less but for better service.
With economies of scale, customers often pay less for the bundled content that a subscription can provide than they would for one off, static purchases.
This, is a drastic change. Think for example, of the subscription service of Spotify, wherein you pay $15/month for Billions of dollars worth of music. The customers, sharing the cost of the content, provide the company with steady income, that isn’t directly tied to usage. In return, they get an incredible amount of value for one low price, as long as they continue to pay it on a monthly or yearly basis.
Meaning, every subscriber will use the service in varying amounts (taking up bandwidth) but also many subscribers who use little of the service help write the checks that improve the service for all users as a whole. The point also seems to be that the larger the group of paying subscribers is, the more content or better service the subscription can often provide.
Cash flows, instead of "lumps".
What makes subscriptions so attractive is that income is fairly predictable. They don't rely so much on sales or seasonal spikes. What makes them so dangerous, is that a single, simple drop in a metric like customer acquisition, has a massive wave of effects on your business for an entire year.
Small scale example:
If you lose 100 more customers this month than normal, all paying $10/month. Not only did you lose $1,000 of revenue this month, but $1,000 of revenue for every month after that. Maybe $12,000 or $24,000. This in turn significantly impacts future investment in the product, and you spin into a downward spiral.
On the other hand, there is an upward spiral, wherein your company is growing and as you’re adding subscribers you’re also investing heavily into new production and value because you have a somewhat predictable runway for investment. This in turn creates happier customers and draws more in. It's a virtuous cycle that leads to a healthy subscription.
The economics are distorted, as customers have varying identities and interests.
One thing that can be really difficult about a B2C subscription is the fact that everyone of your customers pays the same thing, but might have different preferences, use cases, interests, and reasons for purchase.
If we think about Netflix as a subscription, what is the reason you signed up?
For some, it is because of the new hit show, Game of Thrones.
For some, it's because of the library of documentaries.
For some, it's because they love to watch 2 hours a day after work, and they hate commercials.
For some, it's because they want to stay hip, and maybe once or twice a month will binge a show.
For some, they only want to see new nature or crime shows.
And on and on.
As you can see, usage varies, interests vary, the proportion of watching existing shows vs. shows already in the library varies. Some sign up for the new, some sign up for the old.
Some will binge 20 hours per week every week, and they pay the same as someone who watches 20 hours per month.
So how do you win here? This is really tough for media subscriptions to walk the line on. To please the majority of customers, for the long run. Most times, in the example of Netflix, they might have to invest into producing a movie or show 2 years before customers will even receive it. That means that entire investment doesn't know if it will be worth it for awhile. Often in media these subscription businesses need to invest heavily in media to cover the spread of everyone in their audience. Ditto for music licensing.
Data + discovery to the rescue.
The solution to this problem comes from data and discovery.
First, discovery in a large library plays a role because it might be the case that a customer has a deep interest in travel documentaries but hasn't found a movie that, had she seen it, would be a huge hit for her. Her experience is worse on the platform because the media has been "wasted in the shadows" due to poor discovery.
So smart subscription media businesses invest in discovery and recommendation engines.
2nd, by collecting data on subscribers, businesses like Netflix can trend spot to place investments in areas that are more likely to be a hit with subscribers. Famously, data paved the way for House of Cards. So the investment becomes a bit less risky when it comes to paying in advance for new media.
There are more unique characteristics than this, of course, but hopefully that is a solid primer.
There are 3 keys to how a media subscription becomes successful:
- It must continue to provide more value over time. (The subscription value grows the longer you’re with it).
- The subscription provides exclusive, or differentiated products you can’t get anywhere else.
- You have a direct connection with the customer, either through trust or understanding via data.
So the key for a subscription is that it continues to improve and become more valuable over time.
Otherwise, why would I continue paying?
Here's another way of putting that.
- By continuing to increase the value of the subscription (mostly through new content) – customers are incentivized to stick around.
- By selling differentiated, exclusive content, you drive customer acquisition. If your content were simply bundled elsewhere, it might be difficult to get customers to switch. You add and charge for the friction you've created with exclusivity.
- A direct connection with the customer is an overlooked piece that helps you create the ability to service your customers better than anyone else. This can come through data (Think: Netflix data on subscribers helping drive direction for new media production.)
Even though this email list is currently free, it's technically a subscription service.
- I continually show up with new content, that, in theory, is providing value as well as improving over time.
- It's exclusive to this email list,
- I can drive new sign ups with "hit driven posts" that capture larger attention, and I might post them elsewhere which drives sign ups.
- I have a direct line to the reader, and listen to feedback to improve.
I like subscriptions because they're like relationships, they push me to be better and to continually grow.
'House of Cards' Using big Data to