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Tactics: Growing a 40,000 person waitlist for your launch đ
Strategy: Building with First Principles, like SpaceX đ
The Startup, Unpacked: Health Apps that Close Feedback Loops đŠââď¸
Secret Weapon: Retool.com đ§đ˝âđť
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Tactics
Growing a 40,000 person waitlist for your launch đ
The 1st app waitlist I signed up for was Robinhood. Their waitlist strategy got them 1M pre-launch signups (case study). Since Robinhoodâs success, the strategy has become a pretty normal way to launch a consumer product.
Building a large waitlist seems effortless when itâs done well. But how does the sausage actually get made?
Levelâs Founder Josh Clemente walked me through how Levels built a 40,000 person waitlist w/o advertising:
Apps that build massive followings pre-launch are built in spaces that people are already excited about!
For example, Levels fits in nicely into an already emerging trend: the decentralization of fitness and health. With Peloton, health is no longer a âgym thingâ.
And now, with Levels, we can go beyond superficial health measurements like heartbeat/step count to a new frontier, molecular-level health monitoring, which used to only be a âdoctorâs office thingâ.
The app functionality creates magic moments that fit nicely into conversations that are somehow already occurring somewhere online.
People talk about health tracking online all the time, and people constantly want better health info about themselves. Levels delivers a new depth of personal health data in a format that creates these magic moments that people want to share.
And you can see those conversations play out on Twitter, where beta users screenshot their Levels data and talk about how what they eat impacts how they feel in this new quantified way.
Every time a beta user Tweets a screenshot of the app, itâs an example of Levels having figured out how to seamlessly fit into every day conversation. The result is free product marketing/advertising for Levelâs waitlist, and you can see Levelâs leveraging that by retweeting nearly every tweet:
Successful waitlist launches look beyond launch day to measure success. Building a 40,000 person waitlist is great, but thereâs a quality aspect too, right?
The whole point of the business is acquiring customers that donât churn later on, so if youâre just pumping your waitlist numbers up for the sake of it, you may not have great retention stats in your waitlist cohort.
To maintain high quality, Levels gated their waitlist with a not-so-short form that has several qualifying questions for each would-be waitlist member:
So, the most amazing thing to me about their 40k person waitlist is that itâs also highly qualified. This effort may have limited the size of their waitlist, but it will undoubtedly lead to higher retention later on.
Strategy
Building with First Principles, like SpaceX đ
Mental models shape how we view the world around us. To some people, rocket science is, well, rocket science- a topic too complex to understand. To other people, rocket science is just a conversation about the cost of aluminum, ultimately arriving at rocket that can safely return itself to earth for a fraction of the cost of traditional space flight.
The difference is a concept called Reasoning from First Principles. Itâs the act of breaking a complex process down to its most fundamental parts that you know are true. Then building up from there.
For any problem, there is the core problem to solve. At SpaceX there were a few core problems, one of which was the cost of space flight, which led to simple questions like, âwell, we know that rockets are expensive if you buy them from a manufacturer, but whatâs the cost of the raw materials, like aluminum?â
This fundamental level of questioning led SpaceX to realize that everything you need to build a rocket costs about 2% of the total cost of a commercially purchased rocket.
So it's very, very simplistic conversation. According to Josh, when you sit in a meeting at SpaceX, essentially anyone, no matter what their background is, would understand the conversation. They may not have specific experience with it, but there are no acronyms. There's no jargon.
It's all about ensuring that anyone who's in the conversation, whether a PhD in aeronautics or astrophysics or a brand new intern who is still working on their bachelor degree, can all contribute to the conversation in the moment, because that's the only way to foster out of the box thinking to open the opportunity up for anyone to contribute if they have a good idea.
At SpaceX there are people who have geology backgrounds who are designing rocket structures. You will learn on the job, and that's the qualification you need. It's the demonstration. It's not a qualification. You don't need that piece of paper to say that you're qualified for the position.
It's more about showing your team what you can do. And thatâs exactly the kind of culture that Josh has carried over to Levels.
The Startup, Unpacked
Health Apps that Close Feedback Loops đŠââď¸
Letâs be clear, the next unicorns will be health tech companies, but getting people to do stuff thatâs good for their health is HARD!
Just because you built an app that helps people lose weight, quit smoking, or control their blood sugar does not mean that people are going to use it.
Actually, itâs more likely that they WONâT use it. Why? Well, for a lot of reasons, but Iâd like to focus on one of them: Open vs Closed-loop Systems.
The three examples above are open-loop systems: where youâre being asked to give up something upfront, in exchange for a benefit in the distant future.
For ex, to quit smoking, youâre giving up that immediate buzz, and not immediately getting any benefit in return. Youâre just doing it for a decreased chance of cancer in the next few decades.
But like, you still might get cancer. So⌠might as well smoke it, right? The feedback loop is âbrokenâ. If you could more quickly visualize the health benefit of skipping that next cig, youâd be more likely to quit.
Thatâs where closed-loop systems come in. Closed-loop systems use feedback from the process to quickly improve it:
For a very dry example (heh!), hereâs an awesome clothes dryer that gets better at drying your clothes with a feedback loop:
The feedback loop shares info with the controller about the actual dryness of your clothes after each drying cycle so that the next load of clothes is more likely to reach the desired level of dryness!
The end result is that the dryer quickly knows that itâs getting better at its job! Itâs a happy little dryer with a higher degree of job satisfaction!
Without the closed-loop system, the dryer could just continue to unknowingly leave you with soggy clothes after each cycle.
Healthcare is FULL of these terrible open-loop systems. Most of the time, we're just making health decisions on the fly. Whatâs happening is weâre giving our bodies a command (eat this sugar, smoke this cigarette), but then we can't measure the output at all- until years later.
Even in the best cases today, you can go to the doctor to get frequent blood work panels done that measure the damage youâve done in the past week or month, which is better, but it isnât really tight closed-loop feedback (itâs also expensive).
Every health decision we make should be influenced by all of the prior decisions we've recently made, which would be possible if we were able to quickly measure the output of each choice.
The way this translates into a health app/product that people actually use is seeing the effect of your decision, perhaps on graphs or push notifications. Immediately after the decision, the app should allow you to have context for what that decision did.
Thatâs what Levels has done. They combined a continuous blood glucose monitor with a beautiful mobile app where you can chart, in near real-time, if the foods youâre eating are keeping your blood sugar in an optimal zone.
And that closed-loop feedback has changed the foods I eat. For example, Iâve traded CLIF Bars for Rx Bars that donât spike my blood sugar.
But this is not where we are today as a society. Today, we develop our lifestyles based on either no data or just a little bit of data, like the bathroom scale, which takes weeks or months to adjust, or the yearly checkup at the doctor, which has absolutely no functionality for picking what to eat for lunch.
The next wave of health tech startups will find new ways of closing these historically open, or long-term feedback loops. Doing it well wonât just drive slight, incremental population health improvements. I believe we will see massive, sudden improvements.
Retool allows you to build custom internal tooling for your dataset.
Basically all of Levelâs operations systems are built with Retool. Yes, theyâre just simple SQL queries, but Retool enables you to build dashboards and visibility systems for operation teams and customer success teams to get into the data set in really meaningful ways without it being an unbelievably intensive process for the engineering team. Instead, Retool can take a few minutes running a query and all the visibility is essentially no-code and built in.
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