NPLG 8.10.23: New User Flows for Developers (Modal Labs)

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NPLG Startup of the Week: Modal Labs

Modal Labs is one of the hottest cloud data infrastructure startups in the world. Modal helps developers run code in the cloud - providing the easiest way to access compute without the hassle of managing your own infrastructure. As AI is adopted everywhere for everything, developers need access to CPUs, Memory and most importantly, to GPUs to train and run machine learning models. Modal enables fast and secure cloud compute that is helping enable and scale AI adoption.

This year, Modal Labs was voted to the Enterprise Tech 30 list as one of the most promising technology companies by a panel of 100+ prominent VCs. Modal is supporting high-growth companies as customers like Ramp, Scale and Cohere.

For this edition of Notorious PLG, Modal Labs CEO and Founder Erik Bernhardsson shares his PLG strategy with the Notorious PLG community: 

New User Flows (“NUX”) for Developers

“We think the value of Modal is best understood by trying the product. It's hard to describe it without showing the product, so we try to get people experience the value right away. We think of running code in Modal as the "magic moment" and we need to get developers through this first step. Thus, onboarding becomes a core product, not an account registration process. So the product itself is designed for fast setup and delivering value immediately.

Since Modal is about running everything in the cloud, we make it easy for developers with almost nothing to configure at setup. We take care of the infrastructure for you. Thus, the experience in the onboarding reinforces the value prop of the product itself. It’s worth noting that we still have a waitlist because we're in beta while we're iterating very quickly on the product. Thus, account registration isn't quite yet open to the public, but we hope to go GA soon so stay tuned.

To experience the magic moment, a developer needs to (a) register an account (b) install the modal client (c) set up an API token (d) run code locally. In order to optimize the first step, we went with GitHub signup only. We might add other signup methods later but developers generally have GitHub and GitHub OAuth is super quick and easy.

Once you register, there's a NUX (new user flow) on the start page. However, we were careful to have the NUX not be overly intrusive (in a dialog box etc) as it just shows up when you log in, with a set of checkboxes and accordion sections that expand to the next steps. You can navigate away from the flow and come back at your convenience. We then nudge people to run `pip install modal-client`.  (we ended up buying the `modal` package on pypi because enough people were confused – it's like buying a domain name to keep it easy).

A typical API token setup is that you have to (1) click to generate a token in the website and then (2) copy that into a config file locally. That's a bad experience so we’ve implemented a command `modal token new` which is all you need to run to create an API token - this is faster and simpler. You run it in your terminal, and it leverages the fact that you typically already have an active authenticated web session. Then it launches a magic URL that triggers the backend to push a token to the command running in the CLI (this token flow is quite complex but worth implementing. We’ve seen other startups doing similar things, although another option people often use is that the command line app runs a web server on localhost that the web browser talks to. But this doesn't work for remote initialization.

Once you create a token, we automatically throw confetti in the frontend to keep things fun and reward the user and we mark the section as finished in the NUX, collapse it, and expand the next section to run user code. To get people to run user code, we show them a snippet and ask them to copy it to a local python file and execute it. Once this file executes, we also throw confetti in the frontend.

We are constantly iterating and improving our NUX based on feedback from new users and tracking onboarding metrics. Thank you for reading and we would love to hear from you and support your AI journey.”

I would love feedback. Please hit me up on twitter @zacharydewitt or email me at zach@wing.vc. If you were forwarded this email and are interested in getting a weekly update on the best PLG companies, please join our growing community by subscribing.

PLG Benchmarking (Startups):

I will continue to update these metrics and add new metrics. I would love your feedback on what else I should track (zach@wing.vc).

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior NPLG.

PLG Financial Benchmarking (Public PLG Companies):

Financial data as of previous business day market close.

Best-in-Class PLG Benchmarking:

15 Highest PLG EV / NTM Multiples:

15 Biggest PLG Stock Gainers (1 month):

Complete Notorious PLG Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG Financings (Private Companies):

Seed:

• Wisecut, a developer of AI-based video editing platform designed to make videos more engaging, has raised $1M. The round was led by Tim Draper.

Series A:

• Inworld, a generative AI platform for creating NPCs, has raised $50M at a $510M valuation. The round was led by Lightspeed Venture Partners, with participation from Stanford University, Samsung Next, Microsoft’s M12 fund and First Spark Ventures.

• Language I/O, a developer of communication software designed to allow support teams to communicate with customers in any language, has raised $8M at a $38M valuation. The round was funded by undisclosed investors.

• Lightup, a data quality control startup, has raised $9.0M at a $44.9M valuation. The round was led by Andreessen Horowitz and Newland Ventures, with participation from Spectrum 28 Capital, Shasta Ventures, Vela Partners and Incubate Fund.

• Protect AI, a startup building tools to harden the security around AI systems, has raised $35M. The round was led by Evolution Equity Partners, with participation from Salesforce Ventures, Acrew Capital, boldstart ventures, Knollwood Capital and Pelion Ventures.

• Socket, a startup that provides a scanning tool to detect security vulnerabilities in open-source code, has raised $20M at a $110M valuation. The round was led by Andreessen Horowitz, with Abstract Ventures, Wndrco and Unusual Ventures joining.

Series B:

• Neon, a startup that’s building a serverless open-source database, has raised $46M. Menlo VC led the round, with participation from Snowflake Ventures, Databricks, Khosla Ventures, General Catalyst, Founders Fund and GGV Capital.