The Cold Start Problem Part II

Beyond MLB

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A couple weeks ago, I wrote about applying Andrew Chen’s The Cold Start Problem to Reboot Motion.

To recap, Chen’s book delivers a blueprint on how to drive growth by kickstarting and growing any network. And, while he primarily focuses on tech unicorns- AirBnB, Facebook, Google, etc.- the lessons are universal.

My first post was on our core business- Major League Baseball.

At the surface, this may be the least likely market to take advantage of network effects. It is enterprise sales with 30 potential customers who could not be less incentivized tell others about a helpful product.

However, once I realized each club was a network in and of itself, the lessons are the same:

Today, I want to take a different look at Chen’s 6 steps, and see how we can tackle the Cold Start Problem as we move beyond pro baseball and build a biomechanics platform for colleges, private coaches, and tech companies.

Background

Reboot Motion’s vision is to be the world’s best movement analysis platform. When we started in pro baseball, we knew we were simultaneously building tools that 1) moved us towards dominating this specific market, and 2) allowed us to grow beyond it.

From a technical standpoint, we can now eye that expansion. We will soon release our Coaching Dashboard, allowing a few early partners (colleges and private academies) to analyze biomechanics from anywhere.

At the same time, throughout the year we will expose various API endpoints, allowing other sports tech companies to easily enable biomechanics into their offerings.

Having the tech ready to go is a great first step. (And yes, I will admit to our company of mostly engineers, it is the most important one.)

But it is not the only step- we also need to build the network.

Luckily, we have some advantages. We are not building from scratch. Lots of coaches know who we are, and our presence as a trusted partner for multiple MLB clubs helps immensely.

Still, in order to create the adoption we want- and in order for momentum based biomechanics to become the norm- we need to build a network of coaches who believe in our approach, and know that marrying How Data with their coaching expertise is the best way to develop talent.

So how do we do it?

The Cold Start Problem: Private Coaching

Step 1: Killer Product

We start with a killer product.

A killer product is not a list of features. Rather, it is the summation of those features that makes the user’s life better.

Coaches generally have two goals: first and foremost, they want to help their athletes succeed- it is the only logical reason why they got into a profession that generally has long hours and low pay.

Second, they want to grow their career. Whether it is expanding their business or moving up the ranks in college or pro baseball, coaches, like everyone else, want to be recognized for their work.

Our job is to help coaches reach their goals. And everything we build is with that in mind.

Our Coach’s Dashboard obviously needs to allow coaches to upload videos and get back biomechanics reports. But it needs to do so in a way that fits in with the coach’s life.

And our API needs to provide a compelling value proposition to other sports tech companies. But it also needs to be delivered to companies we trust, who have the same north star.

Step 2: The Atomic Network

Baseball is a small world, but we can make it smaller. Once the Dashboard is up, we plan on building out our private coaching network. The initial plan is to start with a few users, and complement it with invite only pitching and hitting slack communities.

Early on, we expect to be the main contributor on the supply side of the network. Over time, more and more coaches will learn the science, mix it with the art they already know, and provide better insights than we could ever imagine.

Again, engagement is key- the size of the network is not.

Step 3: The Tipping Point

Unlike pro baseball, where we have found product market fit, for private coaches we are still firmly in step 1. We are nowhere near the tipping point, but that does not mean we shouldn’t be thinking about what success looks like.

As we grow our Reboot Pitching network, we can use the “land and expand” model. Forward thinking coaches are collaborative by nature, and will be happy to invite friends and share their thoughts.

We also hope the coaches using our product will spread momentum based biomechanics to more and more athletes over time- both as their rosters turn over and their businesses grow. (Yes, we are building for coaches- but that does not mean we won’t benefit from athlete loyalty as well.)

Step 4: Escape Velocity

Step 4 is when positive network effects take over. Again, we we are nowhere near escape velocity. But again, that does not mean we shouldn’t plan for it.

As Chen noted, positive network effects show up in three distinct ways:

1. Engagement effect- the idea that the more the network grows, the more value is created for consumer.
   
   The product getting better for coaches over time is all about education. While we do our best to provide content, nothing will mirror coaches showing how they use momentum based biomechanics to help their athletes. We see the earliest stages of this happening with Rick Strickland- as he builds out his remote coaching business- and Mike McFerran- as he and the rest of the Wake Forest staff bring Reboot’s analyses to the field.

2. Acquisition effect- the idea that getting someone new to join the network gets easier and easier over time.
   
   For us, acquisition costs should come down over time as we provide more and more value. Coaches change roles, their athletes move to the next level, and people want to share the tools that helped them. The more people know about momentum based biomechanics, the quicker new coaches will join the platform. 
   

3. Economic effect- the idea that companies can achieve superior results as they scale. As I mentioned with our MLB business, Reboot views this one a little differently- calling it the innovation effect.
   

   One of the best things about being directly involved with our power users early on is we can see how they use our reports to help their athletes. By being in constant communication, we can use their feedback to start a flywheel where more users → increased data and feedback → innovation → better customer experience → more users.

Step 5: Ceiling

We are nowhere near the ceiling- hell, we’re still building the foundation. However, the key lesson I will remember from Chen’s book is the need to always prioritize power users.

As much as we love working with athletes, we are built for the person behind the scenes. In pro baseball, this is coaches and the R&D team. Everywhere else, it is likely the coach. We want to do what we can to help them succeed.

By prioritizing coaches, we will create the strongest network… and that network will then benefit the most athletes. 

Step 6: Moat

Talking about a moat prior to an official launch may be the height of lunacy.

As I mentioned in part I, our moat today is the backend tech- no one else is doing momentum based biomechanics, and no one is delivering the infrastructure to enable the same biomechanics reporting the pros use from anywhere.

Over time, we expect others to join the party and we welcome it. Competition will force focus, and we need to double down on who we are- an analysis company that constantly builds with the goal of creating leverage for others.

The Takeaway

We are at day 1 for our non-MLB business.

But we know our long-term goal: we want more coaches building businesses, careers, drills, methods, and more on top of our infrastructure. And we want more athletes benefiting from what they build.

If we stay true to our focus and directly help coaches leverage their incredible talent, we will maximize the (indirect) impact we have on countless athletes everywhere.