Recurring revenue is pretty much the holy grail for any business — which is exactly why Apple has geared up to be almost as much a services company as it is a hardware company, with 20% of its revenue now coming from Apple TV+, Apple Music, iCloud, among a host of other subscription and non-subscription services.
The cost of acquiring new customers also has is said to increase by more than 200% over the past decade, which highlights the importance of predictable revenue streams. However, there are inherent challenges with subscription-based business models – not only do companies have to focus on increasing the number of people willing to pay for a given service, but they also have to be careful to retain the ones they already have. Reducing churn is the name of the game.
This is something that the newly formed Danish startup Subtotals aims to help companies succeed, with an AI-enabled platform designed to “bridge the retention gap in the subscription industry.”
Decipherable
Subsets, which was founded by Copenhagen in 2022, relies on so-called “explainable artificial intelligence” to tell companies which current subscribers might switch, and offers “experiments” to find the best way to entice them to stay.
Explainable AI is a concept that describes the ability of artificial intelligence to “explain” or justify any decisions and ideas it provides in a way that humans can analyze, and has emerged as one of the cornerstones of a broader societal push to make artificial intelligence more reliable. of the major providers of large language models (LLM) are trying to appease critics by addressing the much-maligned “black box” problem.
Six months after its launch, Subsets has already claimed some decent clients, including The Athletic and Denmark’s New York Times-owned Børsen. However, the company is now looking to double down on that recent traction with new $1.65 million in pre-seed funding led by Nordic early-stage VC Upfin and Y Combinator (YC), following Subsets’ participation in YC’s Summer ’23 schedule.
The media business
While subsets could be applied to any subscription business, it currently focuses on the digital media industry.
“We’re limiting the use case to digital media for now — these include digital publishers, streaming [platforms]subscription applications and telecommunications”, co-founder and CEO of Subsets Martin Johnson he told TechCrunch. “Subsets can be applied more broadly to consumer digital subscriptions later — I see us expanding into, for example, mobility, banking and food delivery. Even more offline membership categories as everything goes more digital.”
Companies connect Subsets to their various internal systems such as CRM (customer relationship management), CMS (content management system), billing, data warehouse, and so on to collect subscriber data points. a specific piece of content (eg hours, category preferences) and any other relevant information relating to the product and how the customer interacts with it.
On the front end, subsets serve a web application through which commercial teams can delve into “disruptive audiences” through easy-to-understand visuals and natural language. For example, it can highlight thousands of subscribers who used to engage with a myriad of different titles under a particular media brand, but are now showing signs of losing interest.
Subsets: Audience Discovery Image credits: Subsets
Subsets allow non-technical teams to run retention “experiments” on subsets (hence the company’s name) of their subscriber base to see what actions might lead a customer to stay onboard. These experiments might be a series of push or email notifications offering a subscription discount or perhaps a free upgrade to unlock new features. The specifics of these “retention flows” can be modified by each customer.
Subsets: Experiment Image credits: Subsets
Whatever steps are found to have reduced churn in the experimentation phase are presented in the form of results that show what worked — designed to take at least some of the guesswork out of a company’s retention efforts and allow the company to “automate what works.”
“Some of these experiments will do very well in subscriber retention — the experiments that do well are automated,” Johnsen said. “Because an audience is defined by specific subscriber behavior that drives churn, these audiences are typically dynamic, and new subscribers will flow in and out of an audience. All subscribers who flow into an audience receive the streams that have been proven to deliver good results.”
Subtotals: Results Image credits: Subsets
Connections
With a background in mathematical modeling and computer training, Johnsen tells TechCrunch that the company has developed its own AI algorithms using “gradient boosting models with time-series methods.” Gradient boosting essentially combines multiple “weak” predictive models to create a single stronger predictive model, while time-sequencing incorporates time-related features into the modeling process. The subsets then use frameworks from Elon Musk’s xAI to make sense of “driving behavior” as Johnsen puts it.
While Subsets isn’t using any of OpenAI’s GPT.x models at the moment, Johnsen said they’re working on building some additional “downstream functionality” into their product using the same fundamental model that powers ChatGPT.
In a social media post This week, YC president and CEO Garry Tan said that about half of YC’s companies “use LLMs in some way,” which certainly aligns with its latest investment in Subsets. Securing YC as an early backer is also proving fruitful for Subsets’ growth plans, given YC’s historical connections — indeed, Subsets client Athletic is also a YC alumnus, having graduated from the summer ’16 program six years before it was bought by the New York Times.
“YC has an incredibly strong network, which has given us some exciting opportunities,” said Johnsen.
In addition to top backers Upfin and YC, Subsets’ pre-seed round included investment from a host of institutional and angel investors, including Cuesta Labs. Sandhill Markets; and Peakon founder Phillip Chambers.
