📄 Article
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India
Free
Intermediate
Why we picked it
Blume's annual report is the single best data-grounded read on what is actually happening in Indian internet and consumption, not what is trending on VC Twitter in San Francisco. It shows you adoption curves (UPI, quick commerce, ONDC, how few households actually shop online) so you can pressure-test whether a hyped trend has the demand base to land here. Treat it as a starting map of Indian reality, then judge your specific trend against it.
From
Blume Ventures
by Sajith Pai, Anurag Pagaria and team (Blume Ventures)
~180 charts
- Grounds trend-spotting in real Indian adoption data (income distribution, online-shopping penetration, UPI-native monetization) instead of imported hype.
- Indian startups are building a distinct playbook (micro-subscriptions on UPI Autopay, DPI rails) that has no clean US analogue, so copying a US trend directly often misses the real opportunity.
- A trend can be huge in raw numbers yet thin in monetizable demand: the report repeatedly separates users from paying users.
Open
blume.vc →
✍️ Essay
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India
Free
Intermediate
Why we picked it
Before you optimize a byte, you need to know who you are building for, and Pai's India1, India2, India3 framing is the clearest map of the Indian market you will find. He explains the English tax and why the vernacular, low trust, price sensitive India2 user behaves so differently from the metro user founders usually resemble. This is the market context that makes the technical advice matter.
From
SajithPai.com
by Sajith Pai
Long read
- India is several distinct markets, and India2 is not a smaller India1
- Language and trust barriers can matter more than raw speed
- Design in the user's own language rather than translating English later
Open
sajithpai.com →
✍️ Essay
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India
Free
Intermediate
Why we picked it
Essential reading for anyone sizing an Indian market. Pai shows that India's billion people are not one payable market: roughly a hundred million strong India1 is the real paying base for most startups, not the headline population. It is the sharpest correction to the huge TAM trap in an Indian context, and helps you size the segment that will actually transact.
From
Sajith Pai
by Sajith Pai
- India1, around a hundred million people, is the real paying market for most startups
- A billion population is not a billion paying customers
- Size the segment that can actually transact, not the whole country
Open
sajithpai.com →
📄 Article
✓ Link checked
India
Free
Intermediate
Why we picked it
Before you build for a home market outside the big startup hubs, you need the real economics, and this is the essay that maps them most honestly. Sajith Pai separates the roughly 100 million affluent, English-first consumers from the much larger vernacular India coming online, and shows why the second group needs different distribution, different pricing, and often a full-stack model. It is a starting point for pricing a Bharat idea without kidding yourself about willingness to pay.
From
Sajith Pai (Blume Ventures)
by Sajith Pai
~20 min read
- The affluent English-first India and the larger emerging vernacular India rarely share one product or business model, so build for one deliberately.
- Lower incomes push monetization away from ads and subscriptions toward transaction-based and full-stack models where you control the value chain.
- Search-based ecommerce underserves the emerging segment, social and content commerce reduce the real friction of reaching it.
Open
sajithpai.medium.com →
✍️ Essay
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India
Free
Advanced
Why we picked it
This is the deep dive on why the 'next 200 million' users are real but hard to monetize, which is exactly the trap that inflates Indian TAMs. It shows how ad-based and subscription models behave very differently across the India stack. Read it when you are tempted to count non-English, low-ARPU users as full-value market.
From
sajithpai.com
by Sajith Pai
20 min read
- Adding users is easy in India, extracting revenue from them is not
- ARPU collapses as you move from India1 to India2 to India3
- Model the revenue per segment separately, never blend it
Open
sajithpai.com →
📄 Article
✓ Link checked
India
Free
Intermediate
Why we picked it
Redseer gives you an independent view of the internet-to-transacting funnel to cross-check Blume's household numbers. It quantifies how many people actually shop online today versus the much larger connected base. Use these figures as a bottom-up sanity layer when a national number feels too round.
From
Redseer Strategy Consultants
by Mukesh Kumar, Redseer
10 min read
- Online transacting users are a fraction of India's 780 million internet users
- Most internet users come from Tier 2 and smaller cities, but transacting demand is narrower
- Cross-check any TAM against real transacting-user counts
Open
redseer.com →
📖 Book
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Paid
Beginner
Why we picked it
The single best thing ever written on customer conversations. It teaches you to ask about the customer's life and past behaviour, not your idea, so you can't be lied to. If a founder reads one thing before talking to a single customer, it's this.
From
momtestbook.com
by Rob Fitzpatrick
~130 pages
- Talk about their life, not your idea.
- Ask about specifics in the past, not opinions about the future.
- 'That's so cool, I'd totally buy it' is a compliment, not data, dig for commitment and evidence.
Open
momtestbook.com →
✍️ Essay
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Free
Intermediate
Why we picked it
When there is no category report to point at, you have to build the number yourself, and this is the essay that teaches you how. It walks through bottoms-up sizing (start from your actual customer, their willingness to pay, and how you will reach them) and shows why the top-down 'we just need 1 percent of a huge market' story falls apart. Treat it as the method for a defensible estimate, not a promise about how big you will get.
From
Andreessen Horowitz
by Anu Hariharan, Frank Chen, Jeff Jordan
~20 min read
- Build TAM from the bottom up: real customer profile times realistic price times how many you can actually reach and sell to.
- Top-down percentages inflate the number and hide the hard part, which is distribution and go to market.
- Some of the best companies (eBay, Airbnb) started against a market that looked small, then expanded the use case, so a modest starting number is not a dealbreaker.
Open
a16z.com →
✍️ Essay
✓ Link checked
Free
Advanced
Why we picked it
Before you sweat which side to seed, Gurley helps you judge whether your marketplace is even structurally worth building. He lays out ten factors (fragmentation, frequency, payment flow, network effects) that separate marketplaces that snowball from ones that stay empty. It is the investor lens on why some two sided ideas never reach liquidity no matter how hard you push.
From
Above the Crowd
by Bill Gurley
20 min read
- Great marketplaces enhance a market, they do not just aggregate it
- High fragmentation on both sides makes a marketplace more defensible
- Being in the payment flow is far stronger than sitting outside it
Open
abovethecrowd.com →
✍️ Essay
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Free
Intermediate
Why we picked it
The essay that put 'product-market fit' into the startup vocabulary. Read it for the gut-level description of what PMF feels like when it's happening vs when it isn't, the intuition behind the metrics.
From
pmarchive.com
by Marc Andreessen
~15 min read
- Market matters most; a great market pulls product out of a startup.
- You can feel PMF, customers buy as fast as you can ship.
- Before PMF, do whatever it takes to get there; nothing else counts.
Open
pmarchive.com →
✍️ Essay
✓ Link checked
Free
Intermediate
Why we picked it
Most market sizing advice online is generic TAM SAM SOM filler. This one is written by an investor, backed by a survey of 30 VCs, and it is honest about the thing that matters: a big number pulled from an industry report proves nothing. It walks you through building the number bottom up (customers times what they pay you per year), which forces you to confront whether real people will actually pay, and that is the honest test of whether an idea can grow past a niche.
From
Pear VC
by Ian Taylor
~15 min read
- Size the market bottom up (count of real customers times annual revenue per customer), not by claiming a percent of some giant top down figure.
- TAM, SAM, and SOM are used loosely across the industry, so state your assumptions plainly instead of hiding behind the acronyms.
- Project the market out five or more years and include how you would actually reach and acquire customers, since a market you cannot serve is not your market.
Open
pear.vc →
📄 Article
✓ Link checked
Free
Beginner
Why we picked it
A clean definition of the three market layers with the key distinction spelled out: TAM is the whole opportunity, SAM is what you can realistically serve, and SOM is what you will actually win. If the vocabulary still confuses you, this untangles it fast and shows why the SOM, your real near term slice, is the number that matters most.
From
Forum Ventures
by Forum Ventures
- TAM is the whole market, SAM what you can serve, SOM what you win
- SOM, your realistic near term slice, is what investors stress test
- Present both top down and bottom up to be credible
Open
forumvc.com →
📄 Article
✓ Link checked
Free
Intermediate
Why we picked it
This one focuses squarely on the method your short answer champions, building TAM up from real customer counts and pricing rather than slicing a giant number down. It is a good deep dive once you accept that bottom-up is the way and want the mechanics. Practical on ICP counts, adoption assumptions, and unit economics.
From
Qubit Capital
by Qubit Capital
- Build from your ideal customer profile count times annual value
- Ground adoption rates and pricing in observable segments
- Bottom-up assumptions can be tested, top-down percentages cannot
Open
qubit.capital →
📄 Article
✓ Link checked
Free
Intermediate
Why we picked it
A side-by-side of both methods that makes clear why you use bottom-up as your primary number and top-down only as a rough check. That distinction is exactly what protects you when the top-down Indian data is thin. Read it to decide which method to lead with in your deck.
From
Waveup
by Waveup
14 min read
- Bottom-up is defensible, top-down is only a directional check
- Use both and reconcile them against each other
- Lead with the method your data can actually support
Open
waveup.com →
