(2023-10-24) Cagan The Product Model At Spotify
Martin Cagan and Joakim Sunden: The Product Model at Spotify. I don’t think they get the credit in the product community they deserve. I believe that’s mostly because people that think they know “The Spotify Model” are focused on the wrong things, and not what has made them such a strong, long-term competitor
By 2014, the service had amassed 60 million active users, and the fight had now shifted to another battleground. Many new competitors, including Google, Amazon, and Apple were getting ready to enter the fight with their own subscription streaming services.
When we discuss the product operating model, at the high level we are looking at three major dimensions:
The first is how the company decides the most important problems to solve – the product strategy. The second is how they solve those problems and discover solutions worth building – product discovery. And the third is how they build, test and deliver those solutions to their customers – product delivery.
How You Decide Which Problems To Solve – Product Strategy
We believe the most important thing we can do to maximize our potential is to increase our differentiation compared to other services
Spotify’s product strategy was shaped by insights on how their audience segmented. Spotify knew that they essentially had two main types of users. Those that knew the music they wanted to listen to, which they referred to as “lean-forward” listeners. And those that didn’t really know the artists or the albums and they just wanted the service to help them discover music that they would love, which they referred to as “lean-back” listeners. (persona)
Another strategic insight was that more and more users were discovering music through what Spotify called Moments, such as “studying”, “running”, or “dinner-party”, rather than by seeking out specific genres or artists.
Spotify had already started a shift from the model where the user does the work by following people and playlists to build their music library, to a recommendations-based model, where the service does the work based on what the user has listened to in the past.
Realizing that recommendations needed to become a core part of the product strategy, Spotify had recently acquired Massachusetts-based start-up The Echo Nest.
So Spotify leadership gathered up their product teams and explained that they needed to focus on understanding why the service was not performing as well as it should in the lean-back use case, and try to solve this.
This focus meant saying no to many other potential opportunities, and postponing or discontinuing others.*
For example, they shut down a big initiative around video streaming
How You Solve Problems – Product Discovery
certain industry pundits argued that lean-back users simply weren’t interested in exploring new music.
However, a couple of the machine learning engineers that were working on recommendations didn’t believe this to be true. They believed there must be a way to reduce the friction for users
what if we could create a playlist like this, and just update it more frequently? This was the seed of the idea that would become known as Discover Weekly.
First up was value risk: would users choose to use it? And most importantly, if they did use it, would they find enough value to continue to use it?
Next up was usability risk: could users figure out how to use it?
Next was feasibility risk: could the engineers leverage existing systems for this, or would they need to build new systems, likely at high cost?
The team began quietly experimenting with a live-data prototype, which they subtly rolled out to all employees without any formal announcement. Monitoring the metrics, they observed the feature’s viral spread among their colleagues.
This gave the team enough confidence to do a proper employee release (affectionately known as “dogfooding” in many product companies)
the product team understood that Spotify’s employees were not a predictive test, especially for the lean-back case. But now they had the confidence to try to answer the question of whether actual users would feel the same
The team decided to roll it out to 1.5% (1,000,000 users), watching closely as data began to trickle in
feasibility was still a question.
as the user count swelled, it became clear that the existing playlist system would not scale, just as the senior Spotify engineers had predicted
But now Spotify had the evidence they needed to show that reconstructing the playlist system to accommodate the requisite scale would be worth the investment (this is what we refer to as a high-integrity commitment business case).
How You Build – Product Delivery
Since Spotify’s skills in product delivery are fairly well known in the industry, we won’t spend much time on that here. However, it is critical to realize that these investments are what enable Spotify’s empowered product teams to deliver outcomes, and not just output.
This delivery infrastructure paved the way for Discover Weekly and countless other Spotify innovations, large and small.
The Results
The launch was a resounding success, with 1 billion tracks streamed within the initial 10 weeks. Remarkably, 71% of listeners added at least one song to their personal playlists
Product Teams and Product Culture
One of the reasons that this Discover Weekly example is so illustrative is because Daniel was openly skeptical about the product idea, and shared his concerns with the product team.
Great leaders understand the necessity of creating an environment where empowered product teams can exercise their creativity, discovering and delivering innovative solutions that not only customers love, but also drive business success.
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