Pitch & data room — tell it in numbers, prove it in files
🎯 Goal: Tell the startup's story in ~10 slides backed by NUMBERS, and prepare a tidy, consistent "data room" for investor due diligence.
A pitch isn't a feature showcase — it's telling a coherent story: a big problem → a convincing solution → a wide-enough market → growth evidence → a capable team → a clear ask. The standard is about 10 slides. Once investors are interested, they do "due diligence" via a data room — a tidy store proving every number is real. The survival rule: pitch numbers and data-room numbers must MATCH — clashing numbers kill a deal faster than anything. You'll leave with a 10-slide template and a ready data-room checklist.
Lesson content
🔍
Tell a story, don't list features. Investors hear hundreds of pitches; they remember the story, not a list of buttons. A good pitch flows: "here's a big pain → here's how we solve it → here's how wide the market is → and here's evidence it's already working (traction)". Keep ~10 slides, one clear point each, real numbers, no wall of text. The strongest slide is usually not the prettiest, but the one with a number that speaks.
📊
TAM/SAM/SOM — size the market in numbers. Investors always ask "how big is the market": • TAM (total market): everyone who could theoretically buy. • SAM (serviceable market): the part you actually reach with your current product/channels. • SOM (obtainable market): what you realistically win over the next few years. A "bottom-up" estimate is more credible: customers × spend per customer/year. Illustrative example: 500,000 target customers × 300,000₫/year = TAM ~150bn/year; at 3% share → SOM ~4.5bn/year. Numbers must come from real behaviour, not wishes.
🧰
TOOL: The 10-slide pitch template. A standard structure for a fundraising deck — each slide has one job:
Slide
Core content (one sentence)
1. Problem
A big, specific pain — who suffers and how badly
2. Solution
How you solve it, why it beats the old way
3. Market
TAM/SAM/SOM in numbers, why it's big enough
4. Product
Demo/screenshots, the core differentiator
5. Revenue model
How you make money, unit price, margins
6. Traction
Real numbers: revenue, users, repeat rate
7. Team
Why THIS team (founder–market fit)
8. Competitors
The competitive picture & your advantage
9. Use of funds
How much you raise, what for, which milestone
10. The Ask
The amount + a clear invitation
Slide 6 (Traction) is the heart of the deck once you have revenue — it's evidence, not a promise.
🗂️
Data room — the proof store. A folder (usually in the cloud) holding documents for due diligence: • Legal papers (business registration, shareholder list, charter). • Financial statements & the cap table. • Growth data (monthly revenue, users, repeat rate). • Major contracts, team info. Rule: keep it tidy and CONSISTENT with what you pitch. Numbers that "match" build trust; numbers that "clash" kill the deal. If the slide says "500m/month revenue", the data-room report must show exactly that.
🌏
VN–SEA fundraising specifics (step by step). 1) Early rounds rely heavily on relationships and warm intros over cold applications — a trusted intro opens doors faster than a cold email. 2) Regional investors scrutinize unit economics: is one sale profitable, how much to acquire a customer. 3) They assess the ability to scale across the region (not just one city/province). 4) Funds like Do Ventures, 500 Global, VinVentures, Access Ventures, Vertex Ventures are active; Coolmate is an example that raised across multiple rounds with such funds.
⚠️
Pitch & diligence traps: • Cramming features, losing the story: investors forget instantly. • A blank or faked Traction slide: fakes get caught in the data room → trust lost, deal dead. • Pitch numbers clashing with the data room: even a small gap makes investors doubt every other number. • Fake TAM: summing everyone "in theory" instead of estimating from real behaviour. Content is for LEARNING only, not financial/legal advice.
✅
Checklist before meeting a fund: ① Does the 10-slide deck tell one storyline? ② Does the Traction slide have real numbers (revenue, users, repeat rate)? ③ Is TAM/SAM/SOM computed "bottom-up" (customers × spend)? ④ Does every slide number have proof in the data room? ⑤ Do pitch and data-room numbers match? ⑥ Do you have a warm intro to the fund?
Practice exercise
🔬 APPLIED EXERCISE: (1) Draft a 10-slide deck for your idea using the template — one core sentence per slide. (2) On slide 3, estimate TAM/SAM/SOM in numbers via "customers × spend/year". (3) List 5 documents you'd put in a data room to prove the Traction slide. Mark which slide/document still LACKS real numbers — that's the work to do before you pitch.
Worked template: FILLED EXAMPLE: Slide 3 — 500,000 customers × 300,000₫/year = TAM ~150bn; SOM 3% ~4.5bn. Slide 6 (Traction) is blank because there are no paying customers → action: sell to your first 10 for real numbers. Data room needs: (1) business registration, (2) cap table, (3) revenue statement, (4) user metrics, (5) supplier contracts — currently missing (3) and (4).
Quick quiz
1. What is the goal of a good pitch?
→ Tell a coherent story: problem → solution → market → evidence
A good pitch tells a coherent story (problem → solution → market → evidence), not a feature list.
2. What are TAM, SAM, SOM, in order?
→ Total theoretical market → serviceable part → obtainable part
TAM/SAM/SOM = total theoretical market → serviceable part → obtainable part.
3. A more credible way to estimate the market is:
→ "Bottom-up": real customers × spend per customer/year
A credible market estimate is "bottom-up": real customers × spend per customer/year.
4. What should the "Traction" slide contain?
→ Real numbers: revenue, users, repeat rate
The Traction slide needs real numbers: revenue, users, repeat rate.
5. What is a "data room" for?
→ Holding documents for investors to run due diligence on the numbers you claim
A data room is the document store for investors to run due diligence on your claims.
6. Why must the numbers in the pitch and the data room "match"?
→ Because clashing numbers destroy trust and can kill the deal
Pitch and data-room numbers that clash destroy trust and can kill the deal.
Advanced
A deeper framework
At an advanced level, understand that at a revenue-stage round investors trust evidence over promises. So among the 10 slides, the two that carry valuation are Traction (really working) and Unit economics (each order sustainably profitable). A "huge" market slide without traction is usually seen as dreaming.
A data room isn't just "storage" — it's a consistency test. Investors cross-check: does slide revenue match the bank statement, does the cap table match the shareholder list, do user numbers match the analytics. One small "clash" makes them doubt everything — so preparing a data room means making every number defend the others.
Unit economics decides whether the traction story is durable
Average revenue per order
300,000₫
Cost of goods + operations per order
210,000₫
Gross profit per order
90,000₫ (30%)
Customer acquisition cost (CAC)
180,000₫ → paid back after 2 orders
"Rising" traction is DURABLE only when gross profit per order is positive and CAC pays back fast. If each order loses money, growth is just "burning cash to buy revenue".
Common trap: Flaunting "hot growth" while hiding negative unit economics. Revenue rising on loss-making orders is a trap: the more you sell the more you lose, and good investors immediately ask gross profit per order and CAC. Traction persuades only alongside healthy unit economics.
Advanced questions
1. At a revenue-stage round, if you could highlight only ONE slide, which and why?
→ "Traction", because real growth evidence is most convincing and best for valuation once you have revenue
At a revenue stage, investors trust evidence over promises. The Traction slide (rising revenue, returning customers) shows the model really works — the strongest lever for persuasion and valuation.
2. Why isn't "hot growth" necessarily good news?
→ Because if unit economics are negative (each order loses money), the more you sell the more you lose — growth is just burning cash
Traction is durable only when each order has positive gross profit and reasonable CAC payback. Growth built on loss-making orders collapses when the cash stops; good investors always probe unit economics.
3. What is the data room's real role in diligence?
→ A CONSISTENCY test: cross-checking every pitch number against evidence; one clash casts doubt on all
Investors cross-check revenue vs statements, cap table vs shareholder list, users vs analytics. A solid data room is where every number defends the others; one small clash can break trust entirely.
🎯 Real-life mission
REAL-LIFE MISSION: Draft a 10-slide pitch for your idea using the template, ONE core sentence per slide, and on slide 3 compute TAM/SAM/SOM in numbers. Then list 5 documents you'd put in a data room to prove the Traction slide's numbers are real. Mark which documents you don't yet have.