A Product Market Fit Show | Startup Podcast for Founders

Douglas has been in media and PR for over two decades. He’s the founder of Betakit Inc and has been running Betakit, Canada’s TechCrunch, for nearly 10 years. He understands what startups need to do to leverage PR, and how PR can help startups hire, fundraise and sell.  

On this episode, we get tactical and go deep on exactly when it makes sense to use PR and how founders can get the most from it.

Why you should listen

• Why you should treat PR like a subset of inbound marketing
• PR is all about telling the right stories to the right audiences
• How to conduct media profiling to find the right journalists in the right channels so you can get other people to write about you

Keywords

PR, media strategies, startups, business goals, target audiences, media storytelling, marketing initiatives, traction, leads, stories, funding announcements, product launches, media profiling, channels, audiences, founder, pitch, media, framing, storytelling, target audience, channels, journalists, PR, origin story, company values, thought leadership, customer stories, employee stories

Timestamps:
(00:00:00) Intro
(00:05:19) The 101 of Media PR
(00:06:04) Three Questions
(00:08:40) An Operational Lens for Media Engagement
(00:12:16) Understanding the Target Audience
(00:19:55) Inbound Marketing
(00:25:20) A Super Important Caveat
(00:29:08) Roam Auto as an Example
(00:34:00) The Right Channel
(00:36:40) Treating Media Pitching Like Investor Pitching
(00:43:04) Be Professionally Interested
(00:44:49) Putting a Human Face on Your Company

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In this episode, I sit down with Nick Frosst, Co-Founder of Cohere, the $5.5B AI startup that’s targeting the enterprise landscape. 

We go through the origin story of Cohere, the challenges of building foundational models, and why he believes large language models (LLMs) won’t lead to artificial general intelligence (AGI). We also explore the fierce competition in AI, what sets Cohere apart, and Nick’s advice for founders building in AI today. 


Why you should listen

• LLMs are powerful but have clear limitations and won't lead to AGI.
•  Why AI startups need to start with real problems vs leveraging AI for its own sake
• Why ChatGPT was as much of a UI/UX revolution than a technological one
• What tech founders need to do to win in AI

Timestamps:

(00:00:00) Intro
(00:03:21) AI Expectations
(00:06:05)  A Unique and New Moment
(00:09:38)  Resource Intensive Industry
(00:12:03)  Zero to One
(00:15:07)  Base Language Model to Chat Model
(00:17:15)  Carving Out a Niche
(00:21:03)  Open Source
(00:24:00)  The Limits of LLMs
(00:26:18)  Agents
(00:29:30)  AGI
(00:34:04)  A Little Bit of Data
(00:39:05)  Speed of Development
(00:40:47) Finding True Product Market Fit
(00:43:37) One Piece of Advice

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Even if founders do everything right, they may still fail to find PMF. That's why even repeat founders have only 1.5% chance of building a unicorn.

We talk about product-market fit constantly in this podcast. Hopefully, we learn from what others did and improve our chances of finding PMF. But there is only one way to guarantee that one day you will find product market fit. We explore that in this episode.

**Got sick this week so re-releasing one of the most downloaded short episodes from last season that was originally published exactly a year ago today.**

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Don co-founded Vena & was CEO for 8 years. Last month, Vena became a Centaur crossing $100M in ARR.

Don & his team launched Vena in a crowded market, where everyone else was trying to replace excel. So they built a budgeting and planning (FP&A) solution that instead leveraged excel. As Don says, they "disrupted the disruptors".

Don knew the problem, he knew the space, he knew the customers— that’s why he grew from 0 to $1M in ARR in 18 months.

Here's exactly how he did it.

Why you should listen

•  How to close the first few customers
• How to close 6-figure deals without any proof points
• Having knowledge and a network in the industry you're entering makes it easier to find success as a founder.
• In crowded markets, a differentiated approach and the ability to solve pain points for customers are key to standing out.
• Why there's no feeling like the satisfaction of taking an idea and product to market, working with great people, and seeing others succeed.

Keywords
startup, scaling, Vena Solutions, network, crowded markets, budgeting and planning, differentiation, pain points, revenue intelligence, SaaS, founders, startups, entrepreneurship, entrepreneur, venture capital

Timestamps:
(00:00:00) Intro
(00:02:36) The Beginning of Vena Solutions
(00:06:06) Step 1 of Vena
(00:09:35) First Conversations
(00:11:09)The Market in Planning
(00:17:50) The Market in Workflow
(00:20:02) Wealth Fargo
(00:22:23) Getting to a Million
(00:26:05) The Biggest ROI
(00:29:03) Una
(00:34:33) Not Retiring
(00:35:55) Finding Product Market Fit
(00:38:29)One Piece of Advice

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It's the first time I see a candidate BS his way through interviews with multiple people, impress each one of them, and ultimately end up being a complete fraud. But the biggest learning wasn't that you should watch out for fraud-- it was that you shouldn't trust interviews nearly as much as you'd think.

While fake candidates are rare, candidates who are 10x better at interviewing than they are at the job are quite common. In fact, the only thing you know about candidates with great logos is that they know how to interview. Otherwise, they wouldn't have worked at Google in the first place.

What you don't know is if they're truly great. Here's how to find out.

Takeaways

• Don't rely solely on interviews when hiring
• Hire based on referrals and conduct thorough reference checks
• Former founders are often the best hires
• Logos and impressive resumes don't mean as much as you think

Keywords
founder, hiring, fraud, interview skills, backdoor reference checks, referrals, former founders

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Ashutosh is one of those rare founders who founded not just one, but two unicorns. He worked at Google for 4 years, left and started Bloomreach, which was last valued at $2.2B.  

Halfway through that journey, he left to do it all over again.  He started Eightfold AI which is the one we're talking about today. In 2021, he raised $220M from Softbank at a $2.1B valuation. 

When he left Bloomreach, he didn't even have a clear idea of what he was going to build. He just knew he wanted to have more impact and go from 0 to 1 again.

It took him about 2 years to figure it out— then he grew from $1M ARR to $3M ARR in a year & to $12M ARR the year after that. 

Why you should listen

• Why founders need to validate ideas with an open mind to not have tunnel vision.
• Why even unicorn founders don't get it right and often need to pivot to success. 
• How to address problems that are not just today problems, but likely to be problems for a long time. 

Keywords

unicorn founder, Bloomreach, Eightfold, product-market fit, pivot, HR space, digital marketers, talent, hiring, market need, scaling

Timestamps:
(00:00:00) Intro
(00:01:41) His first unicorn - Bloomreach
(00:05:22) Starting Eightfold AI
(00:08:50) Not Marrying Yourself to One Idea
(00:11:55) Finding real customer problems
(00:14:46) Solving Today's Problems vs Future Problems
(00:16:47) Hiring From Already Rejected Candidates
(00:22:50) Fundraising
(00:24:40) Building a V1
(00:27:00) Pivoting and then Reverting Back
(00:30:43) First Customers
(00:32:59) Finding Product Market Fit
(00:35:04) One Piece of Advice

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Carta is the backbone of most venture-backed startups. They have access to specific information about every single round, not just what's reported in TechCrunch. 

Today, Peter Walker, Carta's Head of Insights joins us to share the findings from Carta's Q2 reports. We go deep into data from pre-seed, seed and Series A rounds. We cover median valuations, time between rounds, graduation rates between rounds, the AI and repeat-founder premiums, and much more.

VCs know most of this data. Founders need to be equally well-informed. You won't want to miss this episode.

Why you should listen:

• What are the typical pre-seed, seed and Series A rounds.
• Why stacking SAFEs is very dangerous.
• How to minimize dilution in the early-stages
• What is standard founder ownership, founder equity splits and ESOP sizes.
• Why the graduation from Seed to Series A is so low and the bar for Series A so high.
• Many more data points for pre-seed to Series A Venture Capital and Startup data.

Keywords

startup ecosystem, fundraising trends, total fundraising, down rounds, bridge rounds, company shutdowns, pre-seed funding, seed funding, series A funding, valuations, round sizes, dilution, founder equity, early employees, equity compensation, seed round size, series A

Timestamps:
(00:00:00) Intro
(00:01:35)Findings from the Q2 Report
(00:06:12)Typical Pre-Seed Round
(00:07:29) Post Money Safe vs Pre-Money Safe
(00:11:54) AI and Repeat Founder Premiums
(00:15:03) Typical Seed Round
(00:17:07) Time & Graduation Rates Between Rounds
(00:22:08) Typical Series A
(00:28:14) Equity Splits
(00:35:02) Founder Ownership

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Last quarter, Sanish raised a $50M Series D. His company has raised over $130M. They have enterprise customers across 14 countries including Dollar General, Aldo, and CircleK. 

It all started because Sanish was working out of coffee shops. He wasn't looking for a startup idea. But after a few casual conversations with employees, he noticed several problems retail workers and managers faced. He decided to build Legion to solve them.

He partnered with one local coffee chain, worked as a barista for a week, and developed the product with them for a year. He didn't sell to other customers, he stayed heads down until the local chain adopted the product across their entire organization. By the time they went to sell to other enterprises, they knew the product worked.

Why you should listen

• Why listening with an open mind is a common way to identify customer problems.
• Why providing clear and immediate ROI is a must-have for enterprise customers
• How to perfect your product with design partners that are heavily invested 
• How to raise a Series A without meaningful revenue.

Keywords

Legion, workforce management, enterprise software, problem validation, value proposition, scaling, pricing model, ROI

Timestamps:
(00:00:00) Intro
(00:01:35) The Origin Story of Legion
(00:04:53) The Mindset of Most Frontline Workers
(00:11:05) Gathering Data
(00:20:00) Building an MVP
(00:24:30) Insights from Customers Using V1 Products
(00:30:15) Series A
(00:32:13) Legions Core ROI
(00:36:15) Scaling Legion
(00:39:47) Finding Product Market Fit
(00:41:19) One Piece of Advice

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Sean Ellis created THE test for PMF. He led growth teams at Dropbox, Eventbrite and LogMeIn, which sold for $4.3B. He coined the term Growth Hacking and wrote the best-selling book Hacking Growth. 

Today we go deep and tactical with him. He takes us through how to use the Sean Ellis test to perfectly measure and understand product market fit.

He takes us to case studies of things that he did at LogMeIn and Dropbox to dramatically increase growth. And he shares exactly what you can do to drive more referrals for your startup. 

Why you should listen:

• Why the Sean Ellis test is THE product-market fit test every founder should use. How to implement it today and use it to get closer to PMF.
• Why a great first-time user experience is the key for growth and referrals.
• How to optimize each growth levers, such as acquisition, activation, engagement, retention, and referrals.
• How to build a data-driven culture that is focused on measuring and improving PMF.

Keywords
product-market fit, Sean Ellis test, growth hacking, referrals, first-time user experience, optimization

Timestamps:
(00:00:00) Intro
(00:1:55) The Origin of the Sean Ellis Test
(00:13:13) Finding Product Market Fit Using the Test
(00:18:21) Focus on "Must Have" Users
(00:21:38) Growth Vs Marketing
(00:25:38) Old School vs New School Marketing
(00:30:17) 4 steps to growth
(00:36:24) Improving Sign ups to Usage
(00:41:37) The impact of Referrals
(0045:31) One Piece of Advice

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Daniel's been building robots for 20 years. He's sold 100s of AI robots-as-a-service to Walmart, FedEx, & DHL amongst others. Last month, he raised a $40M round.

6 years ago, he realized  why robots weren't getting massively adopted. Builders like him were trying to build perfect robots that always worked. But every situation has edge cases. What if you designed robots to work only 80% of the time and use humans for the other 20%?

That one unique insight changed everything and was the reason he started Vecna. His robots can tell when they need help and ask humans to assist in real-time. 

Like most capital-intensive startups, Daniel played on hard-mode. Here's how he built hardware, robotics and AI, sold enterprise contracts, and grew to $10s of millions in revenue.

Takeaways

• Why as a founder you need to trust your gut and stick to your convictions.
• How to be objective and create an accurate model of the world to predict the future and make informed decisions.
• How to bootstrap even a capital intensive company in robotics

Keywords

Vecna Robotics, robotics, warehouse industry, automated forklifts, reliability, safety, customer adoption

(00:00:00) Intro
(00:02:05) The Beginning of Early Robotics
(00:06:00) Edge Cases in Robotics
(00:08:15) Robots Shouldn't be Perfect and AI Isn't Intelligent
(00:14:05) Technology Empowers Humans
(00:18:19) When Robots Need Help
(00:21:29) The First Pilot and Customers
(00:29:49) Covid Slowed Everything
(00:33:52) Finding Product Market Fit
(00:34:45)One Piece of Advice

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