Product Growth

100 deep dives a year on how to succeed as a PM, product leader, and aspiring PM.

“The smartest use of your learning & development budget”

2023

Course 1: Mastering the PM Career

Unit 1: The Key Outputs

Product requirements documents
Roadmaps: Advanced techniques
The feature results writeup
The product review bible

Unit 2: Hard Skills

Advanced discovery techniques
How to identify and validate product risk
Advanced customer interview techniques
How to ramp a product team without strategy

Unit 3: Soft Skills

How to say no
Handling conflict as a PM
The Guide to Meetings as a PM
How to bridge the divide between stakeholders and users

Unit 4: Career Skills

The PM Career Ladder: Your Unofficial Guide
How to get a raise in this market
Why politics isn’t a dirty word
Will PMs disappear?

Course 2: Mastering Growth

Unit 1: Lessons From The Greats

How Miro grows
How Canva grows
How Klarna grows
The Story of Runway
The Twitter Algorithm
Anti-patterns from Elon
How did Intel do so Badly?
Everything about Midjourney
What you need to know about Temu

Unit 2: Systematizing Our Learnings

Build a detailed growth model
Gaming growth playbook
When to A/B test
Impact Sizing
Growth loops
How to build a flywheel
How to use Code Interpreter

Unit 3: Success in Specific Product Teams

Information Architecture
Product-led sales
Design Systems
Product Copy
Onboarding
Expansion
Activation

Course 3: Product Leadership

Unit 1: How to set up your product team

How to set up your product team
Do you really need a North Star Metric
Pitch a growth role to senior leadership
How founders think differently from PMs

Unit 2: How to scale your team

Billion-Dollar Execution
Sundar Pichai’s Counter-Intuitive Advice
How to scale a product team from 0 to 15
Reference checks can supercharge your hiring

Unit 3: How to be a great leader

7 currencies of a product leader
The 7 failure patterns of managers
How to Make Your Ideas Stick
Great managers are umbrellas
Product leadership in India

Chief Writer

Apollo.io

Product leader when the company became a unicorn.

I led several product teams, including the growth team, pricing & packaging, activation, expansion, information architecture, acquisition, and engagement.

Raised at a unicorn valuation while I was there.

Ended up leaving to focus full-time on my newsletter.

VP of Product

Affirm

Member of the senior product leadership team. Led growth team when company revenue grew from $300M to $1.2B/year.

Head of Product Growth

Epic Games

Led data driven growth for Fortnite during some it's best performing years, including the Travis Scott Concert and launch of "Chapter 2."

Lead Product Manager

thredUP

Built and led the team's product growth team when it raised its series D.

Director of Growth

Rap to Beats

Developed iOS app Rap to Beats & scaled to 300K monthly active users (MAU). Led team.

Head of Product

TL;DR: I write a newsletter for product managers, product leaders, and aspiring product managers. I focus on actionable and deep tips to improve your career.

The Longer Version:

After a long career in PM - rising to VP of Product at a Unicorn - I have made the shift to writing about it.

In particular, I write about product growth. That is, the art of growing via your product. 

This means I also talk a lot about product-led growth (PLG), the SaaS B2B motion.

My newsletter doesn't just focus on growth though. 

I also break down technology, product management, product leadership, and how to get a PM job. 

It's all the things that make for a great use of your learning & development budget. 

Or even personal spend. 

The math is pretty great. 
↳ $150 for an annual subscription
↳ $211K average PM salary in the US
↳ 0-10% average range of raises offered

If the newsletter helps you get a 0.07% better raise, it pays itself. 
That's 1/142th of your raise range.

It's a pretty smart investment for every level of PM.

http://www.news.aakashg.com

If you aren't learning AI, you're falling behind. 

Luckily, Harvard (4.5% acceptance rate) & Stanford ($78,898 yearly tuition) offer free courses.

No application or fee required. 

Here are 10 courses you don't want to miss:

1. Andrew Ng (of Stanford)'s AI for Everyone

The godfather of AI & CS education, Andrew Ng, is doing a live course on Coursera. It's the ultimate introduction.

And it starts TODAY: https://lnkd.in/g23gC2bk

2. Harvard's CS50

Go from concepts to coding with Python, the lingua franca of AI.

It also starts today: https://lnkd.in/g_JBP42e

3. Stanford's CS224N

Drive forward your understanding of Natural Language Processing (NLP), the basis of how large language models (LLMs) like GPT-4 work.

Get learning: https://lnkd.in/g6vBWu7k

4. Harvard's Data Science: Machine Learning

Apply your skills by getting instructions to build an applied movie recommendation system.

Start building: https://lnkd.in/gggqFJRT

5. Stanford's CS230

Return back to hardcore engineering by now learning about deep learning, once again from the esteemed Andrew Ng.

You can do it: https://lnkd.in/gkh5RXNH

6. Harvard's Fundamentals of TinyML

Begin to learn about how to drive deep learning all to the edge of networks with embedded machine learning.

Jump in: https://lnkd.in/ghVCbZYX

7. Harvard's Applications of TinyML

See TinyML in practice by building Google Assistant on your phone.

Check here: https://lnkd.in/gtHW9PvS

8. Harvard's Deploying TinyML

Take your TinyML application to a real-life situation with TensorFlow Lite.

Deploy: https://lnkd.in/gXD6Mu8w

9. Stanford's CS234

Learn how to build complex reinforcement learning models.

Go deep: https://lnkd.in/gHqBQkZi

10. Stanford's CS330

Conquer the final boss: multi-task and & meta-learning AI.

You got this: https://lnkd.in/grSFRdY5

Bonus: Google ML Certification

Now that you've learned from the best schools in the world, cap it all off with Google's free 15-hour certification.

Get certified: https://lnkd.in/gMcs2CdH

Aakash Gupta

This was the start of Spotify.

$60B of market cap today, just a wireframe at the start.

"We started building the product. That's always what came first for us." 
—Daniel Ek

Let's rewind to get the full context: 

(As Daniel told Stockholm Tech Fest 2015)

2002
Daniel had the idea of Spotify when he experienced the magic of Napster. He loved the concept but hated the business model. He felt, "Holy shit, this is what I want to do." The timing just wasn't right. 

2006
Daniel and his co-founder Martin Lorentzon both had just sold their prior companies. They were figuring out what to build next. They eventually agreed there was a compelling opportunity to make Napster with the right business model.

They started the company with a bunch of people at the KTH Royal Tech Institute in Stockholm. And they communicated a simple vision: "Imagine having all the world's music in your iTunes library." 

2007
One of the people making that vision a reality was lead designer Rasmuss Anderson (who has since gone on to also help design the first version of Figma). Working closely with the team, he created this iconic wireframe that defined the Spotify user experience:

1. Launch app
2. Login to spotify
3. Personalize your homepage experience
4. Discover & play unlimited music

But the Spotify idea didn't start out this perfect. They iterated and iterated until they had something that would not just work, but delight users. The result is these early interactions still define the app we see today.

2008
After two years of iterating on the product, Spotify actually launched in Europe. The team waited until they could "provide the best possible service." And the result was wildfire. Spotify experienced hockey stick growth in Europe, went global in 2011, and public in 2018. 

The key lesson? Iterating on wireframes was done extensively before they ever wrote any code. 

This is a great takeaway for product builders of all types:

Don't skip your wireframes!

What are the (subtle) signs you (might) work in a feature factory?

Sometimes, it’s dead-clear that you’re in a feature factory.  

That's when you’re:

1. Handed solutions, not problems
2. Delivery-focused, with very little discovery work
3. HiPPO’s (highest paid person’s opinion) drive the roadmap

But sometimes, you can sign up for an empowered environment. 

And then, 9 months later... You wake up and find yourself in a covert feature factory.

It looks like this:

1. "Outcomes to rail on PMs only"
↳ PMs are held accountable for outcomes, but it’s window-dressing because outputs are dictated to them.

2. "Research as a license to build"
↳ The vast majority of discovery work is confirmatory, and very few HiPPO ideas are actually disregarded.

3. "HiPPO Control via Product Review"
↳ HiPPO’s inevitably get their way, but more chaotically via product reviews and back-room conversations.

Even if the three main principles aren’t violated, feature factories can manifest as:

"Culture of hand-offs"
↳ This is when sales & customer support share their requests, PM creates the roadmap and shares perfect PRDs, design creates the design, and engineering builds it. It’s modern waterfall or ‘departments as agencies’

"Constant re-organizations"
↳ This is another hidden form of control, where executives keep changing the charter in an effort to dictate what’s built. It's control via the org chart, instead of the features

"Mismatch between planning and validation rigor"
↳ In this scenario, there appears to be planning science and principles. Problems and metrics are shared. But when it comes time to validate and discard HiPPO solutions, that never happens

"Measuring wrong metrics"
↳ This is all about measuring vanity metrics that the team can move, based on what HiPPOs want to build, instead of what the business needs. It's classic confirmation bias instead of first principles strategy

It's almost like “all routes lead to the feature factory.” And it's not untrue. 

For my money, only 1 in 4 PMs work in a fully empowered environment. 

What do you think?

Companies kill their own messaging over time.  
4 bad habits seep in as they grow:

Here's how Anthony Pierri 🎸 described them in the newsletter. 

—

Bad Habit 1 - Speaking to multiple audiences at once

In the world of growth-focused companies, prioritization can be seen as weak. 

But instead of effectively speaking to multiple audiences at once, you end up speaking to none.

In messaging, you must prioritize.

—

Bad Habit 2 — Choosing the Wrong Champion

Most commonly, people aim too senior. This has 2 problems:

1.  There are exponentially fewer CEOs than VPs, directors, & managers
2.  CEOs aren’t buying software

(There is one exception: if you’re targeting a small business.)

—

Bad Habit 3 — Sharing Multi-Order Benefits

The first outcome from using a product is the “1st Order Benefit.”

That may trigger a “2nd Order Benefit,” which can then trigger a “3rd Order Benefit” — and so on.

Most companies land on an Xth order benefit that's revenue.

The only problem?

Talking about revenue doesn't work:

1.  It’s not believable
2.  It hides your product
3.  It deprioritizes differentiation
4.  The audience that cares isn’t shopping for software

—

Bad Habit 4 — Using Vision-Messaging

Messaging lives on a spectrum:

• On one end is the founder's vision
• On the other end is what the product does today

Customers don't care about your vision. They care about your product, its features, & how it addresses their problems.

—

Together, these 4 habits conspire to degrade message clarity over time. 

A strange paradox of growth - one good product and marketing leaders must help their companies avoid. 

Start by calling out the habits. Then correct them.

Let's retire the idea that PMs shouldn't build wireframes.

Of course, there's no need for a PM to always wireframe features. In fact, that's an anti-pattern. But, for big features, I think it's worthwhile. 

Let me explain.

A great wireframe can:

• Convey your entire feature idea in a picture
• Uncover edge user segments you would otherwise discover down the line
• Act as a great tool to use in customer interviews to de-risk your next feature

But you probably already know and agree with that! You don’t wireframe because you believe design should be doing that. 

Here's why PMs should also take part in the process:

1. It brings a greater diversity of ideas to the table

PMs tend to be better experts of what execs and the business wants. Designers tend to be better experts of what users want and the design systems of the larger product. The result is that:

→ PMs tend to create basic, business-driving wireframes
→ Designers tend to create beautiful, user-friendly wireframes

So, having two different people build wireframes increases the total variety of ideas you evaluate. And that's a great thing. It makes it more likely the first solution you ship actually solves the identified problem. 

2. It increases exec involvement in the solutioning process

This is sacrilege, because most idealist PMs don't want to talk about solutions early in the process. But here's my point: a quick rev of wireframes doesn't have to be a commitment to execs. 

Instead, it can be a good way to demonstrate continued progress on a roadmap with execs. And, it uses exec's developed product senses to arrive on a better solution. 

3. It's a great way for the PM to add value to the team

PMs wireframing is part of the "PMs should be full-stack" movement. The point isn't that PMs always wireframe. When a product design expert is available, they should lead the wireframing. 

But, if the designer is out that week, or busy with something else, or new to the team... these are all good reasons for the PM to wireframe. It's also a great way for a PM to summarize a bunch of exec discussions in a PRD for the rest of the team. 

—

As a product leader, I've grappled with whether PMs should wireframe many times over the years:

• On the one hand, PMs have a lot to do
• On the other hand, it might be one of the highest leverage things they could be doing

What do you think of PM's wireframing?

Product leadership isn't a single step. It's a journey.

There are 4 major phases:

I loved how Jennifer Liu put these in Product Faculty's course.

Phase 1: Product

As PMs, we spend the early parts of our career focused on the product:

• PRDs
• Roadmaps
• Strategy and Vision

These are concrete items for us to develop, and their success is easily measured in a quarter or a half. 

But things don't stay that simple. 

Phase 2: Team

As we grow into people leadership roles as PMs, our focus becomes the team:

• 1:1s
• Firing
• Hiring

The skillset changes, but the need for product excellence doesn't. 

Things become less concrete and harder to measure, too. 

Phase 3: Business

As we even further progress up the chain and manage managers, the topic becomes business:

• Revenue
• Market share
• Cross-functional impact

It's yet another skillset to master, and one where some fall into the canyon.

It's relatively common to be excellent at product. It's harder to be excellent at other functions as well.  

Phase 4: Future

In the final phase of product leadership, you become a futurist:

• Headcount planning
• Future financial targets
• Board and investor level storytelling

It's a slow evolution from concrete to ambiguous. 

And the role of influence goes from low to high.

Those are the typical phases of product leadership. 

↳ And the interesting thing is: it's all a spectrum.
↳ Even as an APM, you will do some future.
↳ But the share increases over time.

In PM, leadership is a journey.

What do Facebook Messenger, Gusto, & PostHog all have in common?

They all use humor in their product. 

Humor might just be the missing pillar to your product growth strategy.

Tom Orbach opened my eyes in today's guest post for the newsletter.

Here are 10 places to inject humor into your product:

 1. 404 Pages
 2. Empty States
 3. Easter Eggs
 4. Documentation
 5. Onboarding Flow
 6. User Inputs
 7. Settings
 8. Loading Screen
 9. Feedback Pages
10. Completion Pages

I know what you're saying: "I'm not funny"

You can still do it:

1. Be relatable, not controversial
2. Tell made up stories
3. Crowdscource material
4. Used tried-and-true formulas

It's as simple as that. 

There's no excuse not to be funny. 
You have the locations and methods now.
Go forth and crack some jokes. 

You'll stand out!

How to Grow with Humor

All 30 companies I researched ask PM case questions—from Google to OLA.

(Save this post to be ready for your next PM interview.)

Here's what they're most likely to ask:

1. Product Execution: 29%

• Debugging: Discord comments are down 15% in the last week. What happened?
• Goals/ Metrics: How would you measure success for X Premium?
• Root Cause Analysis: New Notion Docs created are down 5%. How would you identify the root cause?
• Trade-Offs: How many ad slots should be shown at the top of Google search results?

2. Product Strategy: 20%

• Technology Company Strategy: As Canva’s CEO, what are your top 3 priorities?
• Mergers & Acquisitions: How should Palo Alto Networks assess the acquisition of CrowdStrike?
• Real-World Strategy: Create a climate reduction strategy.
• Product Improvement: How would you improve LinkedIn’s Home feed?
• Market Entry: Should Capital One expand into any new developing markets?
• New Tech x Business: Should Spotify enter short-form video?
• Product Monetization: How would you monetize OpenAI’s Sora model?

3. Product Design: 20%

• X for Y: Design a video editing app for the blind.
• Design X: Design a viral consumer social app.
• Redesign X: Redesign Google Maps.
• Real-World Design: Design a digital ordering system for restaurants.

4. Product Sense: 18%

• Product Improvement: How would you improve Photoshop for product designers?
• Product Growth: How would you solve a declining NRR for Snowflake?
• Product Launch: How would you launch a CRM as a PM at Gong?
• Product Design: How would you design paid subscriptions for YouTube?
• Product Pricing: How would you improve the pricing model at Miro?

5. Technical Product: 14%

• Technical Problem: Our website is down. How would you work to bring it back up?
• Reduce Costs: Help decrease infrastructure costs by 30%.
• Improve Performance: Decrease our load time by 15%.
• Improve Developer Experience: How would you deal with developer complaints of experience and speed?
• System Design: Design a scalable system for video streaming at Spotify.

It's official: the case interview for PMs is "everywhere."

P.S. Are there any archetypal questions you'd add?

"I'm in a feature factory. It sucks and I want to quit." Before you do that:

Realize that this is the fate of many a PM. You're not alone. 

And many have parlayed the experience into promotions and better jobs down the line. 

Here's how they do it:

1. Surrender to the Factory

• At first: accept your fate, instead of trying to transform
• Recognize that the empowered world has problems too
• The exception is GPM+, in which case you should drive transformation long-term 

2. Adapt to your Environment

• Triple-click into what your real job is, not the one in books & blogs
• Figure out what your stakeholders & colleagues value
• Overdeliver quality on the tasks your job cares about 

3. Create a Promotion Path

• Get 1:1s with people who were recently promoted
• Do a ‘discovery call’ on the 5 whys of their promotion
• Figure out the patterns at your company, then chart your path 

4. Uplevel Isolated Practices

• Once you have credibility and success as a feature factory PM...
• Prioritize isolated practices that will also help you as a feature factory PM
• Adapt these incrementally to prove out their value

5. Build Your Coalition

• Make the lives of your design & engineering counterparts easier
• Build a coalition that’s finding better ways to work
• Find happiness in doing good work together, even if the situation is less than ideal 

6. Learn to Love It

• As you succeed and have good people to work with, savor it
• You can always find a better place to work, but for now you’re getting valuable execution experience
• That’s a transferrable skill

You don't have to remain miserable.

Turn your lemon of a job into lemonade.

I researched the pricing models of 50 leading consumer software companies. 

These are my top 4 takeaways:

1 — Subscriptions have come to every industry

In every industry, it's worth considering if a subscription makes sense for you.

Recurring revenue, stable cash flow, and higher LTV are all potential prizes. 

But, consumers might be annoyed.

2 — Subscriptions aren't the only game in town

Yes, subscription or “subscription-like” pricing is 56% of this list.

But options like one-time fee, ad-supported, and transaction-based also appear.

And consumers often prefer them.

3 — Industry determines your choice set

If no one is using transaction-based in your industry, you can view it either as: 

• "Not such a good idea" 
• Or an opportunity for counter-positioning

I actually love counter-positioning. Think: 37Signals' ONCE brand vs regular SaaS.

4 — The Yin to Your Models' Yang is your strategy

On top of your model, layer on strategies. Things like:

• Free trials: 52% 
• Freemium: 40%
• Dynamic Pricing: 30% 
• Drip Pricing: 28%
• Reverse Trials: 6%

Too often, the pricing story is simplified into "we have to be subscription." 

Often, it is the right choice. But there's a litany of other options and strategies to consider.

Remember the days of unlimited music skips on Spotify's free tier?

I bet you didn't know removing it increased paid subscribers 25%.

Here's the story:

Unlimited skips on free was a golden age for music lovers. 

→ But, for Spotify, there was less gold than they hoped.
→ So in 2014, Spotify limited skips on the free tier to six per hour.

The headlines were:

• "Spotify’s free tier just got worse"
• "I’m quitting Spotify"
  
But 6 months later, Spotify saw a 25% increase in paid subscribers.

(That's huge!)

And, the cherry on top? 

Churn rate among free users did not go up.

How did they do it? 

• They implemented it as a reverse trial
• Users experience unlimited skips for their first 7 days, then hit the skip limit
• It was classic, "let them try the premium product first"

That’s the power of getting sophisticated with your pricing.

You can solve business problems and drive growth.

Level up your game and bring winning products to market…

Every PM or aspiring product should read this below and repost with your network if you find this useful.

Cc Aakash Gupta

7 Uncommon Signals

For a company founded in 1993, Nvidia's ascent to $2.26T in market cap sure has been quick. How has Nvidia done it?

Chapter 1: Seeing the Future

The story starts all the way back in the early 2000s. That's when Jensen Huang, Nvidia CEO, and the Nvidia team were out meeting researchers using their products.

Most of the researchers were hacking graphics packages to run complex parallel compute. It wasn't great.

So, when the Nvidia team met Phil Buck, who was making GPU kernel operations modifiable via programming, they funded his work. And brought him to Nvidia after his Ph.D. at Stanford.

Chapter 2: CUDA

Phil and his team at Nvidia eventually released CUDA in 2006, Nvidia's Compute Unified Device Architecture. 

CUDA enables developers to use common programming languages like C++ to orchestrate kernel operations on the GPU. 

It has set the basis for widespread industry and researcher adoption of Nvidia chips for AI workloads.

Chapter 3: The First AI Supercomputer 

For the rest of the 2000s, Jensen and the team were using CUDA to develop AI supercomputers for their own purposes: building better GPUs.

Then, in 2012, when the AlexNet moment happened, they got to work specifically on a supercomputer for neural networks being trained by their customers. 

Development got to a point where Jensen shared the story of one of his AI supercomputers at a developer conference. Elon Musk got wind of it, and ordered one for OpenAI. So, in 2016, Jensen hand-delivered the first AI supercomputer to OpenAI and Elon Musk. 

Chapter 4: The Race for Teraflops and Developers

Since delivering that first AI supercomputer, the Nvidia team has continued to innovate on all aspects of training and inference for large neural network AI models. 

Floating point calculations to 16 digit precision have gone from 19 teraflops with the Ampere chips in 2016 to over 5,000 with the latest Blackwell chips Jensen announced on Monday at GTC.

On top of that, Nvidia has been at the bleeding age of software for AI beyond CUDA, including numerous components to allow developers to train their own massive models. 

Chapter 5: Minting Profits

All of that has led to an explosion in Nvidia's profits. It has managed to increase revenue 101% year over year in the last quarter, while only increasing operating expenses 10%. 

All of Nvidia's biggest competitors remain years behind Nvidia in the complete ecosystem. Google has a strong model on its TPUs, Gemini. But other than that, all the best models are on Nvidia. 

Players like AMD, Amazon, and Intel potentially have pathways to challenge Nvidia, along with startups like Groq and Cerebrus. But, for now, Nvidia has a 98% market share in data center GPUs - and doesn't look ready to let up.

news.aakashg.com • 5 min read

Nvidia’s Moat

Subscription companies are taking over the market. Here's why:

The challenge in most public software businesses isn’t continuing a great product. (Like Microsoft Excel or Adobe Photoshop.)

It’s getting your loyal users to keep paying you for it. 

Subscriptions enable that.

Financially, they drive:

1. Increased ARPU and LTV
⤷ Customers tend to monetize more and for longer.

2. Reduced CAC
⤷ You need far less marketing & sales spend to get your loyal customers to pay again.

3. Stable Cash Flow
⤷ Recurring revenue means cash flow becomes more predictable.

But it's not just on the business side. Consumer acceptance is also on the rise.

Continuous updates from product teams have justified the continuous charges.

Both sides of the equation have come together to drive the continued outperformance of subscription businesses. 

Source: Zuora Subscription Economy Index

Your job search doesn’t have to match your friend’s.

(Even if the same principles apply.)

In coaching job search candidates, I consistently find meta-level focus to be the problem getting in their way.

I think I’ve figured out the problem. 

They’re taking advice for people who aren’t in their situation. 

What you should focus on varies by which of the 3 types of job searcher you are:

1. The 1-Hour Job Searcher

Don’t focus on customizing your resume, writing cover letters, and staying on top of every company.

Instead:

• Process Inbound
• Occassionally Apply to Hot Jobs
• Ramp Up Focus When Interviewing

2. The 7-Hour Job Searcher

Don’t suddenly try to create work products, or out-prepare everyone for interviews, or apply to every job.

Instead:

• Proctively apply to 1-3 jobs/week
• Ideally, get referrals where you can
• Do mocks with friends to improve interview skill

3. The 40-Hour Job Searcher

Don’t just drop generic resumes, come to interviews with 2-3 hours prep, and never do cold outreach.

Instead:

• Create an outbound process
• Apply to a lot of jobs regularly
• Outwork everyone with work products and interview prep

It’s about adapting your search to you.

Not the other way around.

Consumers have 4x'd the subscriptions they have since 2014. This is the history of subscriptions taking over consumer software:

Chapter 1 - Early Adopters (1980s - 1990s)

Antivirus programs like Norton and McAffee were the early adopters of the consumer software subscription. They bucked the trend of perpetual licenses, taking their cue from magazines, cable TV, and insurance companies.

Chapter 2 - Annual Upgrade Plans (1990s)

Software like Quicken, Macromedia Director and Grolier’s Multimedia Encyclopedia offered optional subscriptions... Although the primary model for accessing the software was a perpetual license.

Chapter 3 - Subscription Video Arrives (Late 1990s)

In 1997, Netflix launched its consumer video subscription, which was the first purpose-built subscription outside of Antivirus software to gain widespread adoption.

Chapter 4 - Everyone Joins In (2000s)

Inspired by the B2B SaaS revolution, consumer software began going subscription. Flickr launched in 2004. Then, Amazon Prime launched in 2005. In 2008, Evernote, Dropbox, and Spotify all launched as well.

Chapter 5 - Steady Diversification (Late 2000s - Early 2010s)

The launch of the Apple App Store (2008) and Google Play Store (2011) ushered in the era of mobile subscriptions apps. Popular products like VSCO and Peloton took off, as did Birchbox and Dollar Shave Club.

Chapter 6 - Explosion of Subscriptions (Late 2010s - Present)

Now, consumer software subscriptions are exploding. Adobe Creative Cloud (2015) & Microsoft Office (2017) switched over to subscriptions. And players in every industry, from Duolingo to Substack, have followed.

Now, we're stuck with 4x the subscriptions we had a decade ago. 

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