You can also see the episode transcript and April’s references.

April’s background ▶

April didn’t study marketing but engineering at school and worked at a startup when they were still called “small companies.” She ended up working for a “loser product” in a marketing role that she helped reposition and that took off. Her boss quit, so she became the VP of Marketing, which made her discover positioning as a fundamental concept in marketing that actually didn’t have a methodology. She is, today, talking about this methodology in her book, specifically for B2B SAAS growth stage/scale-ups.

An interesting or unusual client? Bluelight Analytics helps dentistry instruments work better; she learned so much about the industry and is scared of visiting her dentist now.

Defining positioning, and when you know you have a positioning problem ▶

Positioning as a concept is not new; it defines how your product is the best in the world at delivering some value that a well-defined set of companies care a lot about.

It's hard to measure bad or weak positioning, but you can feel a sluggishness (e.g. the lightbulb does not come on with a customer unless they have an extra sales call). So how do you assess positioning?

1. Hang out with Sales. You’ll get to listen to customers who are like, “Back up and pitch it to me again. Can you say that again?” Sometimes they’d say, “Oh, you are like Salesforce” or “I can do this on a spreadsheet; why do I need you?” And in this confusion lies your positioning problem.

2. Alignment across the founding team, marketing, sales, customer success, marketing: each function of the company says something different about the product!

3. Sometimes the C-folks get together and say, “Okay, so why does everybody love our stuff?” This is a terrible way to go about positioning, because what you'll get is just opinions and you’ll not know a way to measure if it’s good or not.

With her client Postman, which is “a platform for building and using APIs,” they didn’t know what to call themselves three years ago, and that took work to go through her positioning exercises.

Company misalignment vs. positioning issues ▶

Most cases April has dealt with are misalignment problems within the org and not positioning problems. The founder often has the positioning story done right with their early customer calls, but their C-level team “is not doing or getting it right.” Or the market conditions have changed (e.g. during Covid), where positioning needs a re-evaluation and Product or Marketing has to convince the founders.

The essential five steps to figuring out your product’s positioning ▶

1. Competitive alternatives: What do we have to position against? It’s like saying, who do you have to beat in order to win a deal?

2. You often have a status quo alternative, like Zendesk, that is easy to ignore, but you shouldn’t because in B2B you lose about 40% of deals to “no decision,” which actually means you lost to the spreadsheet, you lost to pen and paper, you lost to interns. And if you’re not positioning well against that product, you’re never going to get the customer to come off that.

3. Key unique attributes: What makes you different? These are key product capabilities or feature functions that the alternatives don’t have.

4. Translate into value: The above unique attributes often bucket into themes of value that are differentiated.

5. Customers who care are your target customers: What are the characteristics of a target account that make them really, really care a lot about that value?

6. Market you win: What’s the context I position this thing in that makes my value obvious to the people I’m going after?

Help Scout’s positioning process ▶

April helped Help Scout figure out its differentiation, which was in its philosophy of customer service, where they treat their customers as humans, not a number, and a chatbot convo happens only when there is a human. Offering a high level of service, their value became the amazing service to customers, not pushing them to a low-cost channel.

And then you ask yourself, “Well, who cares a lot about that?" Not everybody, but a lot of direct-to-consumer brands or e-commerce brands do, where they see customer service as a way to really drive growth through customer loyalty.

The difference between positioning, messaging, and branding ▶

• These concepts are distinct, because positioning is a fundamental precursor to messaging. By messaging, people mean “This is the text on the homepage.” You can’t write that until you understand the value for whom.

• You can’t figure out what the “brand” stands for until you know the target buyer and the differentiation for the brand to be distinct.

• Examples:

  • Magic Leap: Magic Leap is a VR headset, but April was like, so what? What am I actually going to do with that? She helped them pivot to selling B2B for manufacturing companies.

  • Segway: Segway’s founder pitched “Revolution in human transport.” And people were getting so excited because they believed it was a flying car. And then when they saw the actual product, they were disappointed because they saw a moped and didn’t know what to compare it to.

How should early-stage companies think about positioning? ▶

1. The actual 5-step exercise above takes a week and depends on how contentious the existing alignment is.

2. For an early-stage company trying to find PMF, the positioning makes less sense, because there is a lot of validation of the product hypothesis first. Allow the market and customers to pull you as opposed to nailing positioning. For example, if you are selling fish nets—if your thesis is that it’s only for tuna, if it fails, it fails hard. In the beginning, you can just use it for all kinds of big fish and let’s see where it goes. Maybe it’s good for grouper, and this you figure out by being flexible.

3. You feel the need for nailing positioning when you start seeing common patterns with the customers, e.g. they all have Zendesk, are 50-people strong, and are yet to hire their COO.

What’s the difference between segmentation and personas? ▶

• In B2B, you first segment your customers via firmographics, i.e. things like how many employees, revenue, geography, etc. Then, a more actionable segmentation is: “three-member or more creative agencies that follow a specific firmographic profile and have a budget of 20K and they use Notion.” Often in enterprise B2B decision-making, there are between five and seven people involved, so the tighter your segment, the more effective your marketing team is.

• After segmentation, personas come to know who the internal champion of the prospective buyer is. For example, this could be John, who is the head of Sales Ops, and it’s his responsibility to build consensus and galvanize the deal, including their boss, who’s the actual check writer. John becomes the gatekeeper and the most important persona, and if your product is not differentiated, you don’t get on John’s shortlist.

This is a human edited summary of the podcast episode with April, by Gaurav Chandrashekar (@cggaurav, productscale.xyz). To listen to the full episode, go here. 

Marily Nika’s AI Product Newsletter

Weekly AI & Product Management content by Marily Nika, one of the world's top AI Product Leaders with 12+ years @ Google & @ Meta. Opportunities, exclusive templates, course discounts and tools that will transform your career.

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You can also see the episode transcript and Marily’s references.

Staying informed on AI developments ▶

• Sources for AI news: Marily recommends following experts on Twitter and subscribing to any tech-focused newsletters, like the MIT Technology Review. “All tech newsletters would write AI-focused content going forward anyway.”

• AI is both overhyped and under-hyped: She thinks writers complaining writing is dying because of ChatGPT is overhyping and misunderstanding it. “AI is enhancing us, not stealing from us.” She thinks there is more to AI than just ChatGPT. Something that she found under-hyped in AI was news about how AI can now detect lies.

Using ChatGPT for work ▶

1. Writing mission statements that are readable by all stakeholders: Marily uses ChatGPT with a prompt of “Rewrite this mission statement for me,” and it produces something much better even on the first try, because it helps orient the words such that even kids and all stakeholders can understand and not just other PMs.

2. Creating user personas and framing the prompt: It provides her with user segments that you might not even think of, while providing motivations, pain points, etc. To frame a persona prompt, she mentions an example: if you were responsible for creating a fitness band that doesn’t have a screen, you can ask something like “Who would be interested in a fitness band that doesn’t have a screen?” and it provides a list, like people who don’t want to charge it often, among others.

3. Providing AI-enhanced ideas: She doesn’t make it do her job for her, but when she already has an issue in her hand, she asks it to improve it with a lot of ideas.

Why all PMs will be AI PMs ▶

• All PMs will be AI PMs because she sees all products needing to have personalized experiences and recommender systems, and even to make technological advancements, you need to have an AI-centric view.

• PMs should get comfortable with having research scientists on their teams. A lot of PMs are very used to saying, “Okay, I’m going to do XYZ on launch” and don’t know how to approach researchers. Whereas when you’re working with research, it’s more like: we’re going to try this, and then in a year if it doesn’t work out, we’re going to shut the whole thing down.

• Find the intersection of something that’s desirable by users, something that is going to be a viable business, and something that is going to be feasible from a research-scientist and technical perspective.

How to get started using AI ▶

• Think twice before you use AI for your MVP. If you need to just get buy-in for an idea that may use AI in the future, just create a Figma prototype and a demo of what the experience is going to be like.

• Anything where you can get data behind the behavior with users can be improved with AI. For every product you ship, you can always ask yourself if it can be made smarter, e.g. enhancing it with fraud detection; if it’s in health-care you can make it faster or more accurate, etc. Leverage the data that is just sitting around.

• Don’t fall for the “shiny object trap.” Make sure there is a problem and pain point that needs to be solved in a smart way. Once you figure that out, only then figure out how to implement it (by hiring a data science intern or some other way). Only use AI when you already have some data, or data from an adjacent product.

How much data you need for AI to work

• If you’re trying to do classification (like a photo being of a cat or a dog), even 20 labeled photos might work, but if you’re making complicated NLP products or voice recognizers, etc., you might need thousands of data.

When to build your own model vs. use a ready-made model ▶

• A model is like a 3-year-old kid’s brain: You will end up training your kid’s brain by repeating the same information again. Saying, “Here’s what the rhino looks like, here’s what an elephant looks like,” etc., repeatedly. And once you’ve done this enough times, then your kid will see the animal and they’ll be able to recognize it. This is how models work as well.

• Most impactful AI demo she saw: Google demonstrated the power of AI by translating a conversation between two people speaking different languages in real time via Google Glass.

• Build tools only if existing ones don’t meet your needs: Companies should consider developing their own AI tools when off-the-shelf solutions don’t meet their specific needs or when they have a competitive advantage in doing so. This would probably be more relevant for larger companies.

• Most startups also don’t have enough data to build their own models and should rely on using off-the-shelf models more.

• An AI PM role is to decide when the recognition level is good enough to launch the product. Big tech companies should use diverse data to train their model to get better-quality than competitors’.

How to become a strong AI PM ▶

• AI will let PMs focus on some things more than others: AI augments PM capabilities, making them more efficient and effective. PMs should focus less on areas that can be managed/handled with machine learning/AI and more on building their skill sets to understand the underlying mechanisms; e.g., for Marily, having GPT write for her across projects lets her focus her time on more strategic things.

• AI PMs should learn how to code. Even though ChatGPT etc. can help code, learning it gives you a different mindset and confidence, knowing how things work; e.g. in learning to play the piano, Marily hated that she had to learn classical music first, but she understood from her teacher that she needed to learn fundamentals that would help her later.

• Where to learn: Marily recommends her AI PM Bootcamp or AI PM 101 or Advanced course but also courses on Coursera like Intro to AI, CareerFoundry, General Assembly, and Coding Dojo. If your company already has AI projects, talk to people on those teams. PMs should also read papers on Arxiv. Lenny recommended Tyler Cowen’s blog, called Marginal Revolution, to read research paper insights.

• Strong AI PM qualities: To become a strong AI PM, one should have a good understanding of AI, be able to work with data scientists, and possess excellent communication skills. Marily has a course on this for PMs and aspiring PMs.

• Ask yourself “Is there a problem that can be solved with a smart solution?” but make sure you start from the problem itself.

4 main challenges for AI PMs ▶

1. Dealing with uncertainty: With your given hypothesis, when you actually train the model, the results you may be getting may not be answering the questions or the hypothesis that you actually had in mind.

2. Leadership support: You might have to pivot, so leading that change can be difficult, and you need to be prepared.

3. Getting good data is hard, so be willing to do everything: You may need to figure out creative ways to get the data, e.g. maybe going to the street and asking people to contribute data for you.

4. Career trajectory for AI PMs is not defined by launches: Usually PMs get ahead the more they launch. So AI PMs need to clarify with hiring managers early on what progress means and how you will be assessed in research work.

Getting leadership buy-in for investing in AI ▶

• Use examples of successful adjacent products. Marily reminds the leadership about how a previous project in the same space (adjacent product) sounded crazy at the time but has worked out well.

• Provide contingency and rollback plans. In case the project doesn’t work out, have the rollback plan and mention the maximum downside we could have in doing the project.

• PMs need to actually figure out ways to also monetize the ideas of research scientists, e.g. there was a willingness-to-pay survey for ChatGPT to try to monetize it and PMs have to come bridge that gap.

Marily’s AI course and AutoML ▶

• Marily’s three-week AI course covers the product development lifecycle, idea generation, production, and career paths in AI. Students learn coding fundamentals and no-code tools while developing their own AI products. Some students have even raised funding for their creations. People have built a tool to diagnose a patient based on an x-ray in three weeks and managed to raise funding after the course as well.

• AutoML as a no-code AI tool: AutoML is a tool offered by Google Cloud that allows for the training of custom machine learning models with minimal effort. A renewable-energy company was able to use AutoML to reduce their turbine maintenance procedure from three weeks to a few hours using AutoML.

• Marily treated her course like a product, e.g. the first version was directed toward software engineers, but she later pivoted to a less technical audience based on market reception. She continually updates and modifies her course based on feedback and new developments in the AI field.

The importance of creating your own course

• Course creation: Marily built her course using her experience in AI and product management, as well as feedback from students and industry professionals.

• Why create a course: She believes that creating a course is a great way to share knowledge, improve one’s own understanding, and help others learn about a topic.

• Her favorite interview question is “explaining complex concepts”: In interviews, Marily likes to ask candidates how they would explain a database to a 3-year-old.

Resources

• Marily recommends ChatGPT and the Lensa app, which allows users to transform their photos into fantastical images.

This is a human edited summary of the podcast episode with Marily, by Gaurav Chandrashekar (@cggaurav, productscale.xyz). To listen to the full episode, go here.

If I drill down what makes companies fail, it’s quite simple. It’s just like they don’t talk to users, which means they don’t find product-market fit. And if they don’t find product-market fit, nothing else really matters. What mistakes  people make is all about that. It’s all about talking to customers and learning that you’re building something that’s actually useful. YC Slack headline is “Make things people want,” and it’s still true and it’s always going to be true.

You can also see the episode transcript and Gustaf’s references.

What made Airbnb so special? ▶️

• Airbnb felt like a group of friends with a special bond working on a project rather than a job. Folks were diverse, including former founders and people outside the technology industry, which contributed to better decision-making and a YC-like mindset.

• The most important thing Airbnb looked for in early hires is how excited they were to be there. The second thing was to understand their true motivations and make sure they mapped to the company’s core values. Airbnb did this through “culture interviews.”

https://twitter.com/gustaf/status/1580330162725347330

Motivations for starting companies ▶️

• “I disagree with Elad Gil that starting up is an act of desperation; most founders start from a positive place.”

• Motivations can be diverse: solving technical problems, proving oneself, having a grand mission, or simply wanting to be successful. Motivation doesn’t necessarily determine success, and we have seen motivations change over time, e.g. just running the company and enjoying the process of building something big, even if the idea is not grand or shiny.

• Being clear on the motivations also improves conflict resolution and self-awareness among co-founders.

• Don’t start a company as a career step: If you’re successful, it will most likely be your entire career, and if it’s not successful, that’s not something you generally aspire to.

• Consider personal constraints: Startups are hard, so don’t do it if you have financial, family, or relationship constraints that are more important.

The magic that happens at YC Office Hours ▶️

YC Office Hours come in two types: Regular Office Hours (one-on-one) and Group Office Hours (with multiple startups).

Regular Office Hours key question: “What’s holding you back from moving faster?”

Group Office Hours key question: “What are your goals for the next two weeks and what were your goals for the last two weeks? Did you hit the goals? If not, what came in the way of hitting the goals?”

• Addresses the loneliness of the founders by allowing them to lean on others who share similar problems and anxieties.

• Creates accountability by having founders share their goals and progress every two weeks.

Founders in coworking spaces should schedule time to talk, because by default they end up working by themselves with headphones on and no time for interaction. YC’s best experiences were in person, with everyone paying attention to each other without distractions.

Common reasons startups fail ▶️

1. Failing to find product-market fit because they don’t talk to customers:

Often because they think software is the solution to everything, or because they’re afraid of rejection. Ninety percent of customers are not early adopters, so they’re not incentivized to take risks and try something new, and you need to reach out to 10 customers to be able to find that one.

External validation (e.g. investments, praise) is often confused with product-market fit, leading to neglect of customer input. One of the most important moments in Airbnb history was Paul Graham asking the founders of Airbnb, “Where are your customers?,” to which they said, “Oh, they’re in New York,” and Graham responded, “So why are you talking to me and not in New York right now talking to them?”

2.  Lacking technical knowledge: Startups need technical founders who can build the first prototype.

Key advice: Talk to customers, learn what they want, and build products that address their needs.

The importance of solving pain points and why you should watch users ▶️

• Founders fear that users will try their product and hate it, but the most common thing that happens is the user is indifferent. So if you make improvements and come back after a while, they’ll always give you a second chance. Airbnb started with air mattresses and iterated from there, and Brian Chesky continues to do that today.

• Don’t ask users if something is working—watch them do it. That will give you a much better sense of their pain points.

The value of having a technical co-founder ▶️

• Having an idea and trying to find technical co-founder to build it is like having an idea for a song and looking for a musician to make it. Engineering is really hard and valuable.

• Start by asking the best technical people you know if they’re interested in starting a company with you, or ask for introductions to others. Many successful startup founders also learn how to code.

• Contracting an engineering team to build the product doesn’t really work because you can’t spec your way to a great product; you have to be part of the iterations.

Calendly’s success story: A Ukrainian dev team built their first product and drove initial growth by using it within their firm and spreading it to others.

Attributes of the most successful founders ▶️

• They’re determined to win and don’t give up when things get hard.

• They’re generally technical.

• They figure out how to talk to users and make progress, not waiting for permission.

• They have excellent communication and storytelling skills.

YC is not very good at predicting which startups will be the monster hits, but they’re good at identifying what failure looks like and advising against it. One good indicator, though, is if every Office Hours there are new things to talk about (progress on a weekly timescale).

Are successful founders more focused on...?

Speed vs. quality: It’s a false choice. If you know what the customer wants, you’ll come up with something that’s high-quality and move fast.

Confidence vs. humility: Successful founders need both to motivate and attract employees, investors, and customers.

Execution and tactics vs. strategy: Execution is most important pre-product-market fit, while strategy comes into play afterward, where multiple tasks can be tackled simultaneously.

Autocratic vs. collaboration-driven: In early-stage startups with small teams, autocratic decision-making is not feasible. Be willing to adhere to the agreed-upon process.

Cares more about product vs. distribution: Early-stage founders should care more about product (from the user’s perspective, not the founder’s), but the growth mindset is very useful when something is working.

On climate tech ▶️

• Gustaf and David Rusenko (CEO of Weebly) wrote a request for startups in climate tech with a detailed list of ideas and areas of opportunity, and have invested in over 130 companies. It’s not just about doing good for the world; it has strong economic incentives as well, Tesla being a good example.

• Software founders are realizing their skills are relevant in addressing climate change. What’s needed are core PM and engineering skills, not necessarily deep scientific knowledge or domain expertise.

• Decarbonization and carbon removal require changes in transportation, energy, and home heating.

• In shipping, Seabound focuses on carbon capture and removal for ships, while Fleetzero builds electric ships. Carbon accounting and recommendation systems help companies track and reduce emissions like Unravel Carbon (Singapore), Carbon Chain (U.K.), and Sinai (Bay Area). Enode is building a software platform for EV chargers and home energy systems, similar to Plaid. Statiq is the Airbnb for EV charging in India, creating a bottom-up EV charging system and platform. Aviation startups include Heart Aerospace and Right Electric, which focus on battery electric planes for commercial aviation.

• Climate tech is a profitable market, with battery prices and solar costs decreasing and wind power increasing. In the past 12 months: 1. Political change: In the U.S., the Inflation Reduction Act supports green energy and onshoring supply chains for the green economy. 2. Corporations as customers: Fortune 100 companies now invest in decarbonization solutions due to pressure from shareholders, governments, and public promises.

Lightning round ▶️

1. Favorite book? The 100% Solution, by Solomon Goldstein-Rose for climate change. Also, Without a Doubt, by Surbhi Sarna.

2. Favorite movie/show? Emily in Paris and Everything Everywhere All at Once.

3. Favorite interview question with YC? “What have you done since you applied to YC for your product?”

4. Most out-there wild startups you have funded? Heart Aerospace.

5. What’s a pro tip for applying to YC? Watch YouTube videos about hacking the application from other founders and reach out to them.

6. What’s one pro tip for visiting Sweden? Go during summer, explore the wild nature, and be prepared for a different social vibe compared to the U.S.

This is a human edited summary of the podcast episode with Gustaf, by Gaurav Chandrashekar (@cggaurav, productscale.xyz). To listen to the full episode, go here.

You can also see the episode transcript and Hila’s references.

What PLG is and why it’s so popular ▶️

PLG is popular due to the shift from sales-driven B2B business models to user-focused, try-before-you-buy tactics: Consumers have become accustomed to testing products before committing, which has led to increased demand for similar experiences in the B2B space. Even if you think of Facebook, there is no one selling it to you to use it, its PLG in motion where your friend invites you.

Why companies should have PLG and sales ▶️

The question is not either or but both and a matter of sequencing. PLG is perfect for lowering the barrier for more people to try the product and broaden the reach. Sales motion is for a very targeted list of big customer for big orders and having a clear hit list for revenue targets.

If you are in a sales motion dominated traditional B2B software industry, you’ll will need to add PLG because competitors will be adding it and gaining an advantage. It is easier to have PLG from early on rather than trying to add it to a pure sales-led company

What makes a company product - led with Zoom as an eg ▶️

• Low barrier to entry: PLG products like Zoom often have a free version or free trial, making it easy for people to start using them without needing approval from their bosses or even knowing much about the product beforehand.

• Self-service checkout flow: PLG products allow users to upgrade to paid plans or access more advanced features on their own, without needing help from a sales team.

• Product spreads on its own: The nature of PLG products encourages organic growth and word of mouth, as people who find value in the free version are likely to share it with others, expanding its user base."

Common pitfalls in adding a PLG motion ▶️ 

• Make your product more accessible: A big pitfall for many B2B companies is that the entry point to product-led growth (PLG) is often cut off. Their "biggest CTA is called book demo," which means you have to submit a form before even getting a taste of the product.

  • The first step is you need to either have a free product, free trial, some sort of a low barrier entry for anyone who stumble upon this product to give it a try.

• Commit to the process: Some companies may think a simple three-month free trial will bring in leads and conversions, but that's not the case.

  • They think the leads will come, conversion will come, self-service revenue will come. It's not that easy.

  • PLG is a complete motion that requires commitment and a well-thought-out roadmap, potentially spanning a year or more.

• Don't just go 'free', go 'data-led': Companies that want to do PLG but lack usage data are setting themselves up for failure. When offering a free product, the two returns you want are broader reach and user data. Without that you're basically giving away your product for nothing.

The spectrum of when PLG makes sense ▶️

• Don't equate launching a free version or trial with PLG: Many companies assume that "PLG equals launch of free version or launch of free trial." It's not enough to just open a free trial, you must also consider how to activate users, design an upgrade path, and how this growth team will collaborate with sales and marketing.

• Have a dedicated team: If you're serious about PLG, then a dedicated team is necessary. Assigning just one person to manage all the different stakeholders and parts of PLG won't cut it. Hila notes, "The person needs to be a magician in order to be successful."

• Consider the fit for your business: It's essential to contemplate if PLG is actually a good fit for your type of business. For example, if your product requires extensive customization for the customer to see value, or if you are targeting only a handful of large companies, then PLG may not be the best approach.

  • …Or defense companies, only three target customer exist in the entire world, you don't probably want to do PLG.

• Remember, PLG is a spectrum: Not every company needs to add a PLG piece, it's a spectrum. However, the majority of B2B software companies fall somewhere in the middle of this spectrum and can benefit from integrating elements of PLG into their growth strategy.

What you need to be successful in a product-led growth strategy ▶️

• Have a Vehicle: A company needs to have a free version, a free trial, an open-source product, or a realistic experience for their product to successfully utilize a PLG strategy. This is the vehicle that will help your product reach potential users and give them a taste of what your product can offer.

• Time to Value: You also need to think about how to provide value to your users quickly. Give users a warm start and helping them get started with your product as soon as possible. This could mean offering sample content or tutorials to help users get started.

• Data Foundation: With the data, you can design a user journey in the product, via email, or through other tools to guide the user to the next step.

The first step to adding a PLG motion ▶️

The first step in understanding the difference between the PLG funnel and the sales-led funnel (SLG)

Sales-Led Funnel (SLG): The sales-led funnel begins with the marketing team attracting visitors and turning them into leads. Leads are assessed based on how much they interact with marketing campaigns, like opening emails or attending webinars. A scoring system is employed, and those who reach a certain score become marketing-qualified leads and are handed over to the sales team.

Product-Led Funnel (PLG): This approach mirrors the B2C model more closely. Visitors sign up for a free version, account, or trial of the product, and the aim is to encourage product usage. This becomes the primary success indicator for PLG. Usage can lead to two conversion paths: a self-service purchase or sales team involvement.

• In the self-service purchase route, if the product isn't very expensive, customers may decide to buy it online without interacting with the sales team.

• In the sales team involvement route, if the customer fits the ideal customer profile (like being from a Fortune 500 company), the sales or customer success team may reach out to them to provide personalized service, potentially leading to a larger deal.

Once you understand PLG and SLG funnels, think about the user journey your product needs to have to enable successful conversion in the PLG funnel. Establish the steps necessary for users to convert, utilize the product optimally, and create a revenue-generating pathway.

What GitLab does and how the sales funnel and PLG funnel work there ▶️

Sales-Led Funnel: GitLab's marketing team works on attracting visitors to their website and getting them to sign up for free trials or free accounts. These sign-ups undergo a lead nurturing and scoring process, and the ones that score high are given to the sales team. The sales team, which is divided into SMB, mid-market, and enterprise, then works on closing the deals, which convert into revenue.

Product-Led Funnel:

• An individual, such as a developer, might hear about GitLab, visit their website, and sign up for a free account to use for personal projects. They may use GitLab independently of their company's current solution.

• The company can then sign up for a free trial to test GitLab's more advanced features and use that period to conduct a proof of concept. If they only need a few seats, they might choose to go to the pricing page and buy the product directly.

• However, if this is a large company, the sales team might receive data indicating this company's interest, and reach out to start a sales conversation, potentially leading to a contract.

Hence, the product-led funnel is user-driven and has a more organic growth path, starting with personal use and possibly expanding to enterprise-level usage.

Mapping out the funnel ▶️

Start by mapping out the major steps of how users would interact with your product-led growth motion, such as marketing site, free version, and checkout flow.

1. Marketing Site: This is where potential users first learn about the product. The messaging on the marketing site should be designed to encourage free sign-ups.

2. Free Version: The product should have a free version that gives users a taste of what it can do. The UX should guide users towards the product's three most important features.

3. Checkout Flow: The checkout flow should be smooth and offer various payment options to accommodate customers from all regions.

After mapping out these broad components, the team should then dive deeper to identify the specific details that need to be optimized or maximized in each step of the funnel.

Finding leverage and other next steps ▶️

1. Establish the Fundamental Components: After mapping out the product-led growth (PLG) funnel, the first step is to build the foundational components, such as a clear marketing site, a free version or trial of the product, and a smooth checkout process.

2. Identify the Starting Point: Choose a part of your funnel to focus on first that will drive the most significant impact. This should ideally be an area where a small investment could yield substantial results.

3. Conduct a Full Funnel Audit: Run through the entire user journey from a customer's perspective to understand where potential bottlenecks and pain points exist. This includes the initial website visit, the sign-up process, the initial product use, and finally, the purchasing process.

4. Address Pain Points: Be proactive in identifying and addressing issues within the customer journey. Common problems may include confusing checkout forms or unclear paths to reach the product's 'aha moment'.

5. Prioritize User Onboarding: Ensure users can quickly reach their 'aha moment' where they realize the value of your product. This crucial step should be a significant focus to prevent user drop-off due to confusion or frustration during the initial product use.

What an aha moment is and conducting an audit ▶️

• Data Analysis: Pair the audit with data on how many people are on your website, how many go through the signup process, how many reach the 'aha' moment, and how many are successful in self-checkout. This combination of data and user experience will help identify the most significant areas of opportunity, often activation and conversion.

• Understand your Product’s ‘Aha Moment’: The 'aha' moment refers to the first time a user experiences value from your product. This concept originated from Facebook's early growth strategy where if a user added 10 friends within 7 days, they were more likely to continue using the platform.

  • GitLab defined their 'aha' moment as "two users using two features within 14 days". This indicates that the initial user found value in the product and was confident enough to invite a coworker, demonstrating the platform's collaborative nature.

• Validate Your Aha Moment with Experiments: Correlation doesn't imply causation. Just because users who perform a certain action are more likely to convert doesn't mean they will.

  • You just saw people who are doing this are more likely to convert. But it doesn't mean if you get people to do that, they will convert.

• Audit Your Product’s User Experience: Audit your product by assessing the excitement it generates on the landing page, its usability, and if the user can get to the 'Aha Moment' and purchase the product all by themselves. Look at the initial emails sent to the user as well.

• Use Data to Identify Opportunities for Growth: By mapping out the user's journey and analyzing data at each step, you can spot areas that have the biggest opportunities for improvement. Usually, areas like activation (users taking meaningful action in your product) and conversion are common starting places for growth.

  • Obtain data on website traffic, sign-up rates, aha moment achievement, and self-checkout success to spot the biggest opportunities for growth

Activation and conversion ▶️

• Focus on activation if users are confused on their first interaction with the product: Identify the ideal aha moment metric and design a product experience that leads users towards that goal. Use warm starts by providing templates or samples to reduce friction and engage them immediately.

• Focus on activation: If you're finding that people are initially entering your product but don't know what to do next, then you have an activation problem. To solve this, you need to identify your "aha moment metric and then, design a product experience to help more people together."

• Improve conversion if the checkout process has friction: If your activation is in good shape but your conversion is low, it could be that the checkout process is too difficult or confusing. It could be that users can't even find where to buy your product or they encounter issues during the checkout process that are specific to their region.

• Explore product-led acquisition for collaboration software: If your product is something that encourages collaboration, you could leverage this to help spread the word about your product. Think about how companies like Airtable or Figma encourage users to invite their team members to join the platform.

Why you should start with activation, and who is doing it well ▶️

• Start with activation: Historically, B2B software hasn't been designed for quick use, but that's changing with successful PLG companies. The speed at which a user can go from signing up to actually using the product (time-to-value) is critical.

  • "Think about Miro, as an example. If you go through their activation experience and sign up to usage, they ask very limited questions, very targeted... they quickly gave you templates to get started."

• Improve the conversion process: This means making the self-checkout flow as smooth and easy as possible. The goal is to make sure your users don't get confused about pricing or where to find things.

  • "You can actually go to any E-commerce website, like, I don't know, go to Lululemon, go to Amazon, make your conversion process as easy as theirs."

• Invest in PQL/PQA after establishing activation and self-checkout: This is a more complex process and you might want to wait until you have a reasonable number of users and a well-functioning activation and self-checkout process before you invest time and resources into this area.

• Leverage product-led acquisition if your product encourages collaboration: If your product has inherent, internal viral components (i.e., the product encourages users to invite others to use it as well), investing in product-led acquisition is a smart move.

  • "Think about Figma, think about Calendly even, right? It can spread. This product is so easy. You can build something to allow it to spread on its own."

How Hila made an impact on retention at Acorns

• Focus on activation for retention improvement: Analyze features users need to experience early on for better retention. Hila Qu identified recurring investment as a high correlation with retention at Acorns and experimented with getting more users to set it up

• Adding Higher-Frequency Use Cases: Add features with higher frequency to increase engagements, thus improving retention. For instance, they introduced an Individual Retirement Account (IRA) and a spending account with a debit card. These features inherently encouraged more frequent usage, leading to better retention.

The two buckets of data

• Product Usage Data: It involves tracking and analyzing user behaviors, feature usage, and other similar details. In traditional B2B software sales (primarily sales-led), granular usage data hasn't historically been as crucial. However, in a product-led growth approach, this data is essential for understanding what drives user engagement, retention, and eventually, conversion.

• Customer 360 Database: This refers to a comprehensive view of customer information that integrates data from different sources. It includes not only product usage data but also data from marketing campaigns, customer relationship management (CRM) systems, sales data, etc. The idea is to form a complete, 360-degree picture of the customer journey, from the initial point of contact, through the user's engagement with the product, to eventual conversion.

Tools for implementing a PLG motion ▶️

In terms of tool recommendations for setting up an initial stack for product-led growth, Hila Qu mentions several key pieces: [Add links]

Infrastructure Tools:

• Data Collection/Hub Tool: A tool like Segment allows you to collect, clean, and control your customer data.

• Product Analytics Tool: This is used for understanding how users are interacting with your product. Examples include Amplitude, PostHog (an open-source tool), Mixpanel, and Pandle.

• Experimentation Tool: These tools are used for A/B testing and other forms of experimentation to improve your product based on user behavior. Examples include Optimizely, and Eppo, or Amplitude which has an experimentation component.

• Lifecycle Marketing Tool: These tools are crucial for personalizing your engagement with customers based on their behavior in your product. This is different from lead nurturing tools, which are more focused on engagement with marketing materials, not the product itself.

Additional Tools for Specific Product-Led Growth Areas:

• Data Enrichment Tool: These tools, like ZoomInfo or Clearbit, are particularly important in B2B settings because they provide additional data about the user's company, not just the user themselves.

• Onboarding Tools: Tools like Appcues and User-Led allow for quick and easy creation of onboarding flows without needing substantial engineering resources. These are beneficial for creating and testing different onboarding experiences.

• Conversion Tools: For B2B companies looking to convert product qualified leads or product qualified accounts, tools like Endgame, Pocus, Toplyne, and Pace could be useful. They provide insights and automation capabilities to help improve conversion rates.

Tips to get started, and why you need to have good data first ▶️

1. Start with a Product Analytics Tool and a Data Hub: Start with a product analytics tool as it's hard to get it wrong completely. Also, consider adding a data hub, such as Segment, which allows easy integration with many different tools. The flexibility of a data hub allows for trial and error without significant commitment.

2. Garbage In, Garbage Out: The effectiveness of a product analytics tool depends on the quality of the data input. If the data input is incorrect or irrelevant, the output will also be flawed.

3. Audit Your Data Situation: Do an audit of their data instrumentation situation before implementing a tool. This involves understanding what key actions are in place, if the data formats are correct, and identifying any gaps. This may involve re-instrumentation or reformatting to make the data more useful for product analytics.

How to do a data audit ▶️

• Establish a data dictionary for product analytics: Identify key actions in your product experience and matching these to your data instrumentation to find gaps. Eventually, the goal is to establish a data dictionary that contains all key actions, event names, properties, etc. to standardize understanding and interpretation across the team.

• Data Warehouse: When a business starts gaining data users, it's time to consider setting up a data warehouse and an ETL (Extract, Transform, Load) solution. Early stage companies can get by with basic tools like Google Analytics or Amplitude, but as the business grows, a more robust solution is necessary to avoid fragility and inconsistencies. AWS Redshift is a common and best practice option.

The overarching theme is that businesses need to be serious about investing in their data infrastructure. Data is a key asset in a product-led growth strategy, and a well-structured data infrastructure can ensure this asset is leveraged effectively.

Building a PLG team ▶️

• Tiger Team vs Dedicated Team: There are two different ways to start a growth team. The most common one is to create a dedicated team with a head of growth and resources to support the growth initiatives. However, she also mentions a "tiger team," a cross-functional group assembled for a specific purpose for a period of time. A tiger team may be useful when the initial focus area involves multiple departments, like Product Qualified Leads (PQLs) which involve sales, marketing, and data teams.

• Team Evolution: After the initial growth team is established and has achieved some early wins, it's time to extend and formalize. You need to move from just a PLG team to a PLG organization. This involves having a head of growth product, a head of growth marketing, and a head of product-led sales, each managing different parts of the PLG motion.

• PLG Metrics: Once the PLG organization is established, it is crucial to determine the metrics that each team will own. For example, the head of growth product might focus on usage and activation metrics, whereas the head of product-led sales might focus on conversion rates and revenue.

The core growth squad ▶️

• Initial Team Roles: The most critical role for an MVP PLG team is the growth PM (Product Manager) who leads the team. A growth PM is similar to a traditional PM but is more focused on analytics, experimentation, and data-driven decisions.

  • In addition to the growth PM, she recommends hiring a data analyst as one of the very first hires for the team.

  • Engineers and designers are also necessary, although designers may not need to be dedicated full time in the early days.

• Internal vs External Hiring: Hire internally if possible, as individuals already within the company might have a better understanding of its systems, culture, and products. This could be a PM who wants to focus on growth, an analyst who wants a more product-oriented role, or even someone from a different department who has strong analytical skills.

  • If internal hiring isn't feasible, she suggests finding an external hire with experience related to the company's initial growth focus area, be it activation, conversion, or acquisition.

Lightning round ▶️

• Recommended Books: 

  • "The Almanack of Naval," which she found life-changing and helped her understand the importance of leverage in life and business.

  • "How Women Rise," which she found very educational and often gifts to her female team members.

  • The last one is her own book, currently only available in Chinese, which is reported to boost email campaign conversion rates just by its presence.

• Favorite Movie or TV Show: A Chinese sci-fi movie, "The Wandering Earth 2," written by Cixin Liu, the author of the "Three Body Problem" series.

• Favorite Interview Question: When interviewing growth PMs or analysts, she likes to ask, "What is an experiment you launched that had a very unexpected result? And what did you do after that?" The answers to this question reveal the depth of their thinking, their understanding of customers, and their approach to failure or unexpected results.

• Favorite products: ChatGPT and Lululemon yoga pants.

• Product dev process improvement: Adding a section in the ticket stack where PMs write the success metric ahead of time and specify which growth lever the feature will help. This forces them to think deeply about the purpose of the feature.

• Favorite children’s books: "Someday" is her favorite children's book.

• Favorite growth concept: North Star Metric. This concept helps her think long term and evaluate what's valuable not just in her work, but in personal areas such as career and child upbringing.

This is a human edited summary of the podcast episode with Hila, by Gaurav Chandrashekar (@cggaurav, productscale.xyz). To listen to the full episode, go here. 

What do MasterClass, Medium, and Upwork have in common? 

They’re hugely successful companies that knew search engines like Google and Bing could play a significant role in their growth — and they all turned to search engine optimization (SEO) guru Ethan Smith to make it happen.

Good SEO increases a website’s visibility to bring in more organic traffic. And the more users entering a business’s sales funnel, the greater their revenue. It’s a concept most companies understand, at least at a surface level. But putting the idea into practice can feel more like a dark art than a learnable skill.

Enter Graphite, the boutique growth agency Ethan co-founded to assist companies with programmatic SEO, content strategy, and growth design. Lenny welcomed Ethan to the podcast for an in-depth conversation about all things SEO, including one of its most essential yet overlooked aspects: internal linking.

What’s internal linking?

There are three main types of SEO:

• Programmatic SEO. The production of product pages, landing pages, and other web pages automatically generated from a database of information.

• Editorial SEO. Articles, guides, and other content generated manually (written by a person) instead of automatically.

• Technical SEO. A website’s infrastructure, including site architecture, internal link architecture, category pages, tags, redirects, and page speed.

Internal links are part of both editorial and technical SEO. As the name suggests, they connect one web page to another page or resource on the same website, internally, via hyperlink. Your site may also include external links, or backlinks, which connect a page on your site to a high-quality resource outside of your domain. 

A site’s internal linking structure is one of Graphite’s key focuses when conducting SEO, says Ethan. “Consistently, we'll see [that] if you don't have good link spread, fixing it has significant opportunity.”

 “Of anything that I can recommend to companies, as the quick win, the thing to do at the start, it's this.”

The different types of internal links

You can use two types of internal links on your website:

• Contextual links. Hyperlinks within the body of a website’s content, such as blog posts, that lead to another page on the same site are contexual, driving deeper engagement by encouraging visitors to explore related topics and spend more time on your site. These links are more valuable for SEO because they connect pages and deepen context.

• Navigational links. Menu links in a website’s header, footer, or sidebar that allow users to quickly find to other pages are for navigation. These links help users easily move through your website to find the content they seek. 

Including both types of links in your internal linking strategy allows you to create a website that’s informative, easy to navigate, and optimized for Google and other search engines.

The power of internal linking in SEO

In SEO, internal links are an often underappreciated lever for growth — a tool Ethan estimates more than 90% of websites aren’t utilizing. “Google is crawling the web and your site through links,” says Ethan. “And if you don’t have links, then Google doesn’t have paths to find all of your pages.”

So not only do internal links help SEO, but they’re actually make-or-break if you want your site to rank higher on search engine results pages (SERPs). Here’s what links do

• Teach search engines about your website’s structure. Internal links allow search engine crawlers to index your site’s pages more effectively by showing how your content is interconnected. This helps the search engines understand the hierarchy of your content.

• Distribute link equity. When you link out to another internal page, you pass some of the authority and credibility of the original page to the linked resource. This is how you distribute link equity (or “link juice”) throughout your site.

• Improve the user experience. Internal links help users navigate your site more easily, improving the user experience and enticing visitors to stick around longer. In turn, a high-quality experience increases engagement, social shares, and backlinks to your website.

• Help target specific keywords. By linking to pages that target a specific keyword, you signal to search engines which pages on your site are most relevant for search queries containing that keyword. Engines prioritize credibility and relevance in content, putting stronger content on SERPs, in turn generating more traffic and visibility for your site.

Ethan’s 4-step guide to building an internal linking strategy 

If you’re looking to optimize your website but don’t have the human or budgetary resources to devote to highly specialized programmatic SEO, focus your efforts on the editorial side of things — that’s where internal linking really comes into play. 

Here are the four steps Ethan recommends to build your internal linking strategy:

1. Perform a site audit 

Using a program like Screaming Frog, crawl your site to pull data for an internal link audit. You’ll learn the total number of internal links, find any broken links that take visitors to an error page, and gain performance metrics that show you which pages are most in need of improvement. 

2. Identify your best-performing pages

Your audit is likely to show that a small percentage of pages are bringing in the most traffic. Low-traffic pages generally benefit from additional internal links to pages that already rank well and earning significant clicks. 

These high-authority and popular pages, called “crawl points,” are locations where Google enters your site. And a page’s proximity to a crawl point influences its share of the link juice. “You want the shortest path from a crawl point,” says Ethan.

3. Identify related content.

Look for pieces of content that are relevant to your best-performing pages, whether existing or new. These internal resources can benefit one another thanks to the power of linking.

4. Link related content to the best-performing pages. 

Use internal links to connect pages — the more, the better. (Ethan recommends at least 5–10 links per page.) Just be sure to use descriptive anchor text that’s relevant to the content it’s linked to.

The importance of human-generated content

Don’t underestimate the power of the written word — according to Ethan, editorial SEO has become more effective at driving traffic than programmatic SEO. “The way that you grow is with programmatic and with editorial SEO,” he says. “And I think editorial SEO, and by that I mean articles and content, manually written content, is underappreciated.”

Whether you’re updating existing content or creating new material for your website as part of your digital marketing and internal linking strategies, you might be tempted to save time and resources by using an AI tool like ChatGPT. But although Ethan believes AI is useful for the parts of the content creation workflow that lead up to writing — such as extracting structure, identifying topics and subtopics, and performing keyword research — he cautions against using it for the writing itself.

“A lot of times, it’s indistinguishable from a human,” he says. “The problem is that you want the sentence to be factual.” And because GPT-3 works by crawling very large data sets and generating sentences similar to those it finds, the sentences it produces may or may not be accurate.

Google’s algorithm places a higher value on pages with quality, relevant content, so inaccuracies can have a negative impact on your site’s performance. And, more importantly, unreliable information can harm your users. “If I have cancer, and I’m researching cancer options, and this AI content suggests some treatment that isn’t a good treatment, that’s a big problem,” Ethan says. 

Power up your SEO strategy

Lenny’s Podcast features interviews with world-class product leaders and growth experts to uncover concrete and actionable advice and empower you to launch your own product. Listen to the full interview with Ethan Smith for a comprehensive breakdown of internal linking best practices to improve your website’s search rankings and help Google drive more traffic to your business.

For answers to reader questions about product and career growth, subscribe to Lenny’s Newsletter. And be sure to explore the full podcast archive for valuable conversations on topics such as:

• Building a cult-like brand

• Techno-optimism

• Product-led sales

• Defining your ideal customer profile

• When to quit your job