NPLG 7.13.23: How OpenAI Onboards 1B+ Users

The best PLG founders, startups, strategies, metrics and community. Every week.

Jul 13, 2023

Current subscribers: 7,593, +81 since last week, +1.1%

Share the PLG love: please forward to colleagues and friends! 🙏

How OpenAI Onboards 1B+ Users

This is a special guest post with Jonathan Anderson at Candu. Candu helps product teams build seamless user onboardings (and every experience featured in this post 😉) without coding. If you’d like to learn more, reach out to Jonathan here. Friends of Notorious PLG can also gain early access to new pay-as-you-go plans starting at $399/month.

OpenAI: How the fastest-growing consumer app, ever, onboards billions

ChatGPT is the fastest-growing consumer app ever, with over 1.5 billion monthly visits and counting. It has skyrocketed to become one of the top 20 websites worldwide.

And that’s just one product. What’s remarkable is that OpenAI offers a diverse product suite, catering to various user personas. From the consumer application ChatGPT to the creative tool DALL-E and the developer-centric OpenAI Platform, each product has radically different uses and targets distinct audiences.

Despite their differences, all three products follow a simple yet effective onboarding framework. The goal is to put users in the right frame of mind to take full advantage of the revolutionary tech.

The onboarding framework is simple:

Set Clear Expectations: Before allowing new users access, put users in the right frame of mind.
Provide examples: Present tangible examples so we can grasp how to use the product, plus draw inspiration for what’s possible.
Explain capabilities and list limitations: Highlight what the product can do and what it can’t.
Monetize Power Users: Each product is free to use at first. Power users are metered with usage-based pricing.

Here, simplicity works wonders.

Let's explore how this framework is applied for ChatGPT, DALL-E, and the OpenAI Platform, supported by visual examples, of course!

ChatGPT: Onboarding for Everyone

ChatGPT, OpenAI's consumer application, wants new users to start offering prompting as soon as possible. However, as they’re still working out the kinks in the AI, the product has to set the right expectations first.

Setting our expectations: ChatGPT employs a thoughtful prompt to set our expectations. Before granting access, it takes a moment to remind users that it is a free research preview (Read: “We’re in beta”). Additionally, ChatGPT transparently explains its data collection practices, addressing our concerns about data privacy. This strategy ensures users approach the product with the appropriate mindset (it won’t kill us, probably, but it will use our data).

Empty state with everything stated: This is one of my favorite empty states ever. When you pull up the interface, users aren’t presented with a blank canvas – they’re given a very clear overview of examples, capabilities, and limitations. When in doubt, make it clear: here’s what you can do, here’s how we do it, and here’s what we can’t.

Pre-built queries: Take a minute to appreciate the choice of the initial inputs here: “Explain quantum computing in simple terms” “Got any creative ideas for a 10-year-old’s birthday?” “How do I make an HTTP request in JavaScript?” Yes, they’re a ‘random’ selection, but they show the breadth of what ChatGPT offers us. These ready-made prompts help users engage with the possible range, sparking creativity.

Immediate push to create content: What makes this homepage brilliant is its simplicity. With just the input field below eagerly awaiting our input, there are no distractions or barriers in our way. It's a seamless transition that propels us straight into engaging with ChatGPT, ready to unleash our ideas.

Monetizing with speed: One notable limitation users may encounter with ChatGPT is delays during peak usage periods. Cleverly, OpenAI flips this problem into an opportunity by introducing the option to upgrade to ChatGPT Plus, which allows users to receive priority access even during busier times.

If you’re going to onboard billions of users, this is how to do it.

DALL-E: Onboarding for Designers

DALL-E, OpenAI's image creation tool, enables designers to transform descriptions into vivid and unique images. The onboarding process for DALL-E focuses on getting us to unleash our creativity.

Setting the context: DALL-E frames itself as a creative copilot (implying that we, not the AI, are in the driver’s seat). The language is clever - “Create an iterate with DALL-E.” This also sets the expectation that the first version might not be quite what you expected (limitations) before clearly explaining the capabilities (creating novel images from text).

A Thoughtful Input Bar: Once in the platform, designers are encouraged to provide precise and detailed descriptions of the images they have in mind. Since a successful DALL-E image depends on a clear prompt, it helps that the help text is a representative query: “An impressionist oil painting of sunflowers in a purple vase.” Smart.

Surprise Me: Besides specific descriptions, DALL-E allows designers to request a random image with the “Surprise Me” optionl This is reminiscent of Google’s “I’m feeling lucky,” throwing bone to serendipity.

Monetizing with more: On the free option, users are limited by the number of images they can generate. OpenAI offers the option to purchase more credits, allowing users to continue creating without limitations.

OpenAI Platform: Onboarding for Developer

The OpenAI Platform caters to developers, offering APIs and tools for integrating OpenAI's technology into their applications. The onboarding process for developers emphasizes practical examples, comprehensive documentation, and a playground for testing and experimentation. Sound familiar?

Documentation: As a developer tool, OpenAI delivers detailed documentation. The docs explain the API's functionalities, endpoints, and available parameters, giving developers a comprehensive resource to understand the platform's capabilities and limitations.

Quickstart Guide: To expedite development, OpenAI provides a Quickstart Guide. This resource offers step-by-step instructions and code snippets, enabling developers to set up their development environments and make their first API calls.

Example Applications: Like ChatGPTs query params and DALL-E’s help text, OpenAI’s Example Applications help demonstrate its capabilities (Question & answer, Grammar correction, SQL Translate, etc.). The subhead says it all: “Explore what’s possible.”

Playground: The OpenAI Playground serves as a sandbox where developers can build a sample application to test the functionalities and limitations of the platform. This interactive interface allows developers to gain hands-on experience. Notice that the ‘Get Started’ context provides not just instructions but also some of the limitations.

Monetization with more: Like DALL-E, the OpenAI Platform operates on a pay-as-you-go model. As developers use more credits, they pay accordingly. The usage-based monetization approach ensures scalability. If it ain’t broke, why fix it?

Conclusion

How do you onboard billions of users with vastly different needs? You keep it simple.

OpenAI's consistent framework of setting expectations, providing examples, highlighting capabilities, and listing limitations has proven to be effective across ChatGPT, DALL-E, and the OpenAI Platform.

As product builders, there’s much to learn from OpenAI's approach. By embracing this framework when designing our own onboarding processes, we can set the right context, ignite creativity, and get users to value at scale.

Want to have one of the experiences featured for your own product? Ping Jonathan here. Friends of Notorious PLG can get early access to the new pay-as-you-go plans starting at $399/month.

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).

Conversion rate (website → free user):

Best: 10%
Good: 5%

Activation rate (free user → activated user):

Best: 60%
Good: 30%

Paid conversion rate (free user → paid user):

Best: 8%
Good: 4%

Enterprise conversion rate (free user → enterprise plan):

Best: 4%
Good: 2%

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

Best: 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:

Outverse, a developer of a full-stack, AI-powered community management platform for software companies, has raised $6M. The round was led by Wing VC, with participation from Notion Capital, Seedcamp, Connect Ventures and Tiny VC.
Infisical, a developer of an open-source platform designed to securely sync secrets and configures across the team, devices, and infrastructure, has raised $2.8M. The round was led by Gradient Ventures, with participation from Twenty Two Ventures and Y Combinator.
Lamini, an operator of an information technology company intended to outperform general-purpose large language models, has raised an undisclosed amount from First Round Capital.
Narya.ai, a developer of automated bug-hunting engine intended for building Web3 applications, has raised $4M. The round was led by Lightspeed Venture Partners, with participation from Canonical Crypto and Superscrypt.

Weflow, a developer of a workflow management platform designed to save time preparing, documenting, and following up, has raised $3.2M. The round was led by Gradient Ventures, with participation from Cherry Ventures and Hello, World!.

Series A:

PixieBrix, a developer of a browser extension designed to customize websites for adding functionality, integrating systems, and automation workflows, has raised $6.9M. The round was led by New Enterprise Associates.