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APP IDEA #31 · ECOMMERCE · PRODUCT INTELLIGENCE

Dropkiller — the product research tool that tells you what to sell before you sell it

Built for Latin American e-commerce sellers, Dropkiller surfaces winning products and validated ad creatives so sellers stop guessing what to stock. $50,358 MRR, 2,307 active subscriptions, $1.1M total revenue — founded October 2024, barely a year old. The exact same model, rebuilt for India's Meesho sellers, Shopify D2C brands, and Flipkart merchants, is completely wide open.

$50.3K
MRR — ₹42.3L/month (TrustMRR verified)
2,307
Active subscriptions
$1.1M
Total revenue — ₹9.2Cr all-time
Oct 2024
Founded — barely a year old at this revenue level
01 / HOW IT WORKS

What the app actually does

Dropkiller's insight is that most e-commerce sellers — especially first-time dropshippers and small D2C brands — make product decisions based on gut feel or copying competitors. Dropkiller replaces that guesswork with data: which products are trending, which ads are performing, which niches are oversaturated. India's version of this tool barely exists.

1

Seller enters a product category, keyword, or competing store URL

The starting point is flexible — sellers can research by niche ("pet accessories"), keyword ("wireless charger"), or spy on a competitor's top-selling products directly.

2

AI surfaces trending products with demand signals and competition scores

Each product card shows estimated order volume trends, how many sellers are competing, profit margin estimates at India-realistic price points, and a saturation score so sellers know if they're late to the party.

3

The platform shows real winning ads for that product

Scrapes and surfaces actual ads running on Meta and Instagram for that product category — letting sellers see what creative formats and hooks are converting before they spend a rupee on their own ads.

4

Supplier links connect the winning product to an Indian sourcing option

For each trending product, the platform shows where to source it — Alibaba, IndiaMART, or local Indian wholesale suppliers — so sellers can move from research to stocking in one platform.

02 / INDIA POTENTIAL

Does this work as an India play

India has one of the world's largest e-commerce seller bases — Meesho alone has 15M+ sellers, most of them small resellers who have no idea what's trending or where to source it. Dropkiller's model, rebuilt for India, is a direct product-market fit.

15M+
Meesho sellers alone — mostly tier-2/tier-3 city resellers who make product decisions by guessing. A ₹299/month tool that tells them what's trending sells itself.
Meta Ads
India's D2C brands run Meta ads as their primary acquisition channel. A tool that surfaces what ad creatives are working for competitors right now is the single highest-value feature for this audience.
₹499/mo
Realistic India-priced entry tier vs Dropkiller's $19-49/month for LatAm — opens Meesho sellers and small D2C brands who can't justify dollar pricing but will pay ₹499 for verified product intelligence.
Flipkart
Flipkart seller intelligence — trending products, competitive pricing data, and review sentiment analysis for Indian marketplace sellers is a second, larger revenue tier above the Meesho reseller base.
03 / THE WEEKEND BUILD

Friday to Sunday, hour by hour

Scoped to product trend tracking and competitor ad spying for Meesho/Shopify sellers only. Skip the supplier sourcing integration for v1 — the research and ad intelligence is the core value to ship first.

Friday
Evening · 3 hrs
7–8 PM Set up a Next.js project, Supabase for auth/database, and a basic product search form — keyword or category input.
8–9 PM Build the product data pipeline — connect to a product trends API (or scrape Meesho/Flipkart trending pages) and store results in Supabase with order volume estimates, price range, and seller count.
9–10 PM Build the product results grid — cards showing product name, trend direction (up/down), estimated demand, competition score, and margin estimate at Indian pricing.
Saturday
Full day · 7 hrs
Morning Build the ad creative spy feature — scrape Meta's Ad Library for ads related to the searched product category. Display the top-performing creatives with estimated run time and engagement signals.
Afternoon Add AI analysis layer — send each product's data to Gemini API to generate a 3-bullet "opportunity summary": why this product is trending, who the buyer is, and what hook to use in ads.
Evening Build the saved products list — users bookmark trending products they want to track, and the system re-checks trend data daily via a Vercel Cron Job.
Sunday
5 hrs
Morning Build the competitor store analyzer — user pastes a Meesho/Shopify store URL and the system extracts their top-selling products and price points.
Afternoon Razorpay integration — ₹499/month Starter (50 product searches/day, ad spy), ₹1,499/month Pro (unlimited, competitor analysis, daily trend alerts).
Evening Test the full product search → ad spy → AI summary flow, record the demo for your first post.
04 / APP STACK

What you're actually building with

Nx

Next.js 14

Frontend + API routes

Search interface, product cards, ad creative gallery, and saved list in one framework.

Sb

Supabase

Auth + database

Stores user accounts, search history, saved products, and cached trend data.

Sc

Scraping layer (ScrapingBee)

Product + ad data

Pulls trending product data from Meesho/Flipkart and ad creatives from Meta Ad Library.

AI

Gemini API

Opportunity analysis

Generates a 3-bullet AI summary for each trending product — why it's hot, who buys it, what hook to use.

Cr

Vercel Cron

Daily trend refresh

Re-checks saved products for trend changes every 24 hours and alerts users to significant shifts.

Rz

Razorpay

Payments

₹499/month Starter and ₹1,499/month Pro tiers, UPI-first.

05 / WHERE & HOW TO DEPLOY

Going live

Where: Vercel for the app and cron jobs, Supabase for the database. The data quality of your product trend sources is the entire product — invest time upfront identifying which Indian e-commerce platforms have the best publicly accessible trending data before writing around it.

Push your project to GitHub, import into Vercel — auto-detects Next.js, no config needed.
Research Indian e-commerce trending data sources BEFORE building — Meesho, Flipkart, and IndiaMART all have publicly visible trending sections that can be scraped.
Add environment variables: SUPABASE_URL, SUPABASE_KEY, SCRAPING_API_KEY, GEMINI_API_KEY, RAZORPAY_KEY.
Set up Vercel Cron to re-check saved product trends daily.
Point a custom domain at it from Vercel domain settings.
06 / MARKETING & REVENUE

Getting paying users

How to market it

  • Post the "this product went from 0 to trending on Meesho in 30 days — here's how I found it before everyone else" format as a reel — first-mover discovery is the entire emotional hook.
  • Run 3-5 reels/day targeting Meesho resellers, Shopify D2C founders, and Flipkart sellers — each is a separate audience with its own content angle.
  • The Meta ad spy feature is its own reel: "I found the exact ads your competitors are running on Instagram" — this converts performance marketers immediately.
  • Target Indian D2C and e-commerce WhatsApp groups and Telegram communities directly — these communities actively share product research tips and will spread a good tool fast.
  • Offer 5 free product searches per day with no card required — sellers who find one winning product on the free tier will upgrade immediately.

Who pays, and why

  • Meesho resellers in tier-2/tier-3 cities who currently pick products by guessing what's selling in their network.
  • Shopify D2C founders running Facebook/Instagram ads who need to know what competitors are running before spending their own budget.
  • Flipkart and Amazon.in sellers wanting category trend intelligence and competitive pricing data before launching a new product.
Scenario
Paying users/mo
Revenue/mo
Slow start
200 × ₹499
₹99,800/mo
Meesho community traction + reels
2,000 × ₹499
₹9,98,000/mo
3-5 reels/day + D2C community deals
10,000 × ₹499
₹49,90,000/mo
07 / START BUILDING

Paste this into Claude or GPT

This prompt sets up the full build context so the AI scopes, plans, and starts coding the project with you from message one.

BUILD_PROMPT.txt
I want to build a product intelligence and ad spy tool for Indian e-commerce sellers, inspired by Dropkiller (which does Rs42.3L/month targeting Latin American sellers), scoped to ship a working version in a single weekend. Core product: 1. Seller enters a keyword, category, or competitor store URL and gets a list of trending products with demand signals, competition scores, and margin estimates at Indian price points. 2. For each trending product, the platform surfaces real Meta/Instagram ads running for that category — scraped from Meta Ad Library, showing creative formats, hooks, and estimated run duration. 3. An AI analysis layer (Gemini API) generates a 3-bullet opportunity summary for each product: why it is trending, who the typical buyer is, and what ad hook to use. 4. Users can save products to a watchlist — a Vercel Cron Job re-checks trend data daily and alerts users to significant changes via email or WhatsApp. 5. A competitor store analyzer lets users paste a Meesho or Shopify store URL and extracts the store's top-selling products and price points. Pricing: Rs499/month Starter (50 product searches/day, ad spy feature), Rs1,499/month Pro (unlimited, competitor analysis, daily trend alerts by WhatsApp). 5 free searches/day on free tier. Stack I want to use: Next.js 14 for the frontend and API routes, Supabase for auth and database, a scraping service (ScrapingBee or Playwright) for product trend data from Meesho/Flipkart and ad creatives from Meta Ad Library, Gemini API for the AI opportunity summaries, Vercel Cron for daily trend refresh, Razorpay for the subscription. Deploy target: Vercel. Help me, step by step, one question at a time: 1. Before code: what Indian e-commerce platforms have the best publicly accessible trending product data I can scrape without violating terms? 2. Build the product search and trend data pipeline first. 3. Build the product results grid with demand signals, competition score, and margin estimates. 4. Build the Meta Ad Library scraper for the ad creative spy feature. 5. Build the Gemini AI opportunity summary for each product. 6. Build the saved products watchlist with daily Vercel Cron refresh. 7. Build the competitor store URL analyzer. 8. Wire up Razorpay for the subscription tiers. Keep explanations short and India-context aware. Focus on Meesho and Flipkart as the primary Indian platforms for trend data. Flag any scraping legal/ToS considerations upfront. Push me to ship the smallest working version first. If I get stuck, tell me to ask @buildwithkanhaa.

Start building this weekend

Send me a screenshot of what you ship — it might be the next reel.

DM @buildwithkanhaa →