TrackFuture.ai · Market Validation Strategy v1.0
A pre-launch market validation strategy for TrackFuture.ai. Six structured hypotheses, six two-week experiments, one operating principle — no headcount, no content commitment, no marketing spend is approved until the market signals it will pay for the underlying value.
This is the companion to strategy.html. The strategy doc states what the business intends to become; this doc tests whether the market agrees, before capital is committed.
Most new publications fail because they build content first and hope revenue follows. TrackFuture is doing the opposite: we are testing demand for paid products before we publish a single article.
The four revenue lines in the strategy doc — sponsored profiles, paper-explainer retainers, founding sponsorships, market maps — are each hypotheses. We do not know which will work in the Indian deep-tech market. We do not know whether the proposed prices are right. We do not know whether the proposed buyers are the actual buyers.
The experiments below answer those questions with real conversations and real money — not surveys, not opinions. By the end of 60 days, we know which revenue lines deserve investment and which to drop.
TrackFuture has no published archive yet. We cannot honestly sell a portfolio that does not exist.
What we can do is approach the market as researchers: ask sharp questions, listen carefully, and treat every "yes, I'd pay for that" as a falsified null hypothesis — not a closed deal. The deals follow once the editorial product ships. The intelligence about who will buy is what we capture now.
Sequenced so the cheapest, fastest-feedback experiments run first. The order is deliberate — each experiment either feeds the next or makes the next unnecessary.
Experiment 1 · Weeks 1–2
Hypothesis: Indian deep-tech startups (drones, robotics, AI infra, climate-tech, defence-tech) will pay INR 15–25k for a well-researched 1,500-word technical profile because mainstream outlets cover funding rounds but skip the actual engineering.
Target list
50 Indian deep-tech startups at Series A and below, sourced from Tracxn / Crunchbase / IndianStartupNews / LinkedIn. Mix verticals so the experiment reveals which vertical responds best.
Research script (cold email)
Subject: Quick question on how you tell your engineering story
Hi {{first name}},
I'm researching how Indian deep-tech founders explain their actual
engineering work to customers, recruits and partners. Most coverage
stays at the funding/PR layer — not the build.
We're launching TrackFuture.ai, a publication focused on the technical
substance of Indian deep-tech. Before we lock the content format, I'm
collecting input from 50 founders.
Would you be open to 15 minutes this week? Two questions:
1. Is a deep technical profile (1,500 words, written by an engineer
not a PR person) something you would commission for hiring/sales?
2. What would a fair price look like for that?
Honestly research — no pitch.
Thanks,
{{your name}}
TrackFuture.ai
Signals of demand
Success criteria
Kill criterion
<3% reply rate AND zero "hot" signals after 50 emails. The format, the price, or the buyer is wrong — iterate the message before sending the next 50.
Experiment 2 · Weeks 3–4
Hypothesis: Indian deep-tech VCs and corporate R&D teams will pay INR 25k/month for a service that turns 1–2 arXiv papers per month into plain-English explainers their team can read in 10 minutes.
Target list
20 Indian VCs (Blume, Peak XV, 100x.VC, Inflection Point, Speciale Invest, Pi Ventures, Endiya, Kalaari, Prime Venture) and 10 corporate R&D groups (Tata Elxsi, Infosys Research, L&T, Mahindra AFS, Reliance Jio AI, Ola Krutrim). Target the associate / principal level, not partners.
Research script (LinkedIn DM)
Hi {{first name}},
Quick research question — I'm scoping a service for VC associates
who need to read deep-tech arXiv papers fast.
The concept: you forward one paper per month, we send back a 1,200-word
plain-English explainer your team can read over coffee. Written by a
technical editor, not a generic content shop.
Before we build it I'd love 15 minutes to ask:
- Is reading frontier papers a real pain point in your week?
- Would something like this be worth INR 25k/month to your team?
Honestly trying to figure out if this is real.
Thanks,
{{your name}}
Signals of demand
Success criteria
Kill criterion
5 conversations with no one asking for a sample = the buyer doesn't feel the pain. Repackage as a free lead-magnet (a weekly paper brief) and revisit later.
Experiment 3 · Weeks 5–6
Hypothesis: 6 Indian deep-tech tool/SaaS companies will pay INR 7,500 each to be a "Founding Sponsor" of TrackFuture's first six newsletter issues — even before subscriber numbers exist — because the brand association is worth more to them than the CPM.
Target list
30 Indian deep-tech tools companies whose customers are TrackFuture's intended audience: Sarvam, Krutrim, Mindgrove, Detect Technologies, ideaForge, Garuda Aerospace, Tonbo Imaging, Yulu, Ather, Log9, Wingman AI, Cropin, plus relevant cloud/devtools resellers. Approach founder or head of marketing.
Research script (email, founder-to-founder tone)
Subject: Founding Sponsor of TrackFuture — six slots, one for you?
Hi {{first name}},
We're launching TrackFuture.ai, a publication for Indian deep-tech
builders. Newsletter goes out weekly to a hand-picked launch audience
across LeadingIndia.ai, AlgorithmGuru.in, and IIT/IISc research
groups.
We're offering 6 Founding Sponsor slots, one per issue, at INR 7,500
each. You get:
- Top-of-newsletter placement (one issue)
- A 60-word custom message we write with you
- "Founding Sponsor" credit on the site for 12 months
- First right of refusal on bigger sponsorships once we cross 10k subs
We're not selling on CPM — we don't have one yet. We're selling
association with a publication our audience will trust. Five slots
left.
Open to a 15-minute call this week?
Thanks,
{{your name}}
TrackFuture.ai
Signals of demand
Success criteria
Kill criterion
30 emails, zero "send the invoice" responses, all replies are "come back later" = no perceived pre-audience value. Pause and revisit after the first 500 newsletter subscribers are real.
Experiment 4 · Weeks 7–8
Hypothesis: 50 Indian engineering students and early-career engineers will pay INR 299–499 for a 2-hour live workshop with the founder (e.g., "How to read an LLM paper in 30 minutes" or "Build a sub-INR 15k FPV drone"). This validates whether the target audience will spend money before being asked to subscribe.
Distribution channel
Co-promote via LeadingIndia.ai and AlgorithmGuru.in newsletters + 5 college Telegram / WhatsApp groups. Razorpay payment link. Zoom delivery.
Execution
Success criteria
Kill criterion
<15 paid signups after 7 days of promotion = the topic doesn't pull. Try one different topic before concluding workshops don't work.
Experiment 5 · Weeks 9–10
Hypothesis: One Indian VC will pay INR 40k for a 50-company market map in a single deep-tech vertical (drones, AI infra, defence-tech, or climate-tech) because building it in-house costs an associate three weeks.
Build the sample first
A polished 1-page PDF: "The Top 10 Indian Drone Startups, 2026 — What They Build, Who Funds Them, What's Next." Built using Tracxn / Crunchbase / LinkedIn + a short founder review. This sample becomes the pitch.
Research script (LinkedIn DM)
Hi {{first name}},
We're putting together a "Top 50 Indian Drone Startups, 2026" market
map — engineering, funding, regulatory status, customer wins.
Attached is the first 10 as a sample.
The full 50-company version is INR 40k as a one-time deliverable, or
free if you're willing to introduce us to 3 portfolio companies for
profile features.
Useful to your team?
Thanks,
{{your name}}
Success criteria
Kill criterion
15 pitches, zero traction = associates aren't the buyer; partners are, and they don't take cold outreach. Park until the founder secures warm intros.
Experiment 6 · Ongoing throughout
Hypothesis: 50 unhurried 30-minute conversations with deep-tech founders, run across 60 days, will surface 5–10 future revenue opportunities once TrackFuture's content library exists. Not direct revenue today — a structured way to map who the future customers actually are.
Execution
The three discovery asks (founder makes them on the call)
Success criteria
By Day 60: 50 founders met, 30 logged in CRM as warm, 10 logged as hot, 3 conversions to Experiments 1, 2, or 3.
Every Friday: one page in this format. It is the artifact that captures what the market is teaching us — the most valuable output of the entire program.
TRACKFUTURE — MARKET VALIDATION FIELD NOTE
Week of {{date}}
Prepared by: {{your name}}
ACTIVE EXPERIMENTS
- Experiment 1: Sponsored Startup Profile — Week 2 of 2
- Experiment 6: Founder Coffee Chats — Ongoing
OUTREACH THIS WEEK
- Experiment 1: 28 emails sent, 4 replies, 1 hot
- Experiment 6: 5 calls booked, 4 held
SIGNALS OF DEMAND (Hot)
1. {{Company}} — {{Name, role}} — said "yes, INR 20k works, can you
start in 2 weeks". Founder to follow up Monday.
SIGNALS OF DEMAND (Warm)
1. {{Company}} — wants a sample first.
2. {{Company}} — budget needs partner sign-off, revisit Q3.
WHAT THE MARKET TAUGHT US
- Drone companies replied 3x more than AI infra companies. Possibly
because Inc42 already covers AI infra heavily.
- The phrase "engineering profile" outperformed "deep-dive" in
subject lines.
DECISION FOR NEXT WEEK
- Experiment 1: double down on drone + climate-tech list.
- Experiment 1: drop "deep-dive" from the subject line.
OPEN QUESTIONS FOR THE FOUNDER
- Please respond to the {{Company}} thread by Monday.
- Sample profile sketch needed for {{Company}} by Wednesday.
RESOURCE USE THIS WEEK
- 22 hours research + outreach.
- INR 1,500 (Sales Navigator trial, ConvertKit).
At the end of the program, the validation strategy produces three artifacts that drive the next phase of TrackFuture's investment.
1. The Validated Revenue Map
Which of the four revenue lines produced real "send the invoice" signals, at what price, with which buyer segment. This map tells the founder where to invest hiring and content effort first.
2. The Warm Pipeline
A CRM of 30–50 named prospects tagged hot or warm, with notes, conversation history, and stated price expectations. This pipeline becomes the launch inventory the future sales hire inherits on day one.
3. The Killed Hypotheses
Equally valuable: a documented list of revenue lines that did not validate, with the reasoning. This saves TrackFuture from re-running the same mistakes six months later.
A successful validation program is narrow on purpose. The scope below protects the integrity of the data.
This program does
This program does not