AI E-CommerceWatch – Product Research Agent for E-Commerce By RunnerH
Shreya Nalawade

Shreya Nalawade @shreya111111

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Joined:
Apr 22, 2023

AI E-CommerceWatch – Product Research Agent for E-Commerce By RunnerH

Publish Date: Jun 19
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This is a submission for the Runner H "AI Agent Prompting" Challenge

What I Built

I created an AI-powered autonomous product research agent using Runner H, focused on helping e-commerce sellers identify high-potential products for platforms like Amazon, Etsy, and Shopify.

This Runner H agent performs:

  • Trend analysis across platforms (Amazon, TikTok Shopping, Google Trends)
  • Product data aggregation (prices, reviews, profit margins)
  • Competition scoring
  • Supplier discovery
  • Launch strategy generation

All of this is saved in a structured PDF and Google Sheet for actionable insights.

Demo

Prompt Used

Agent Objective:
You are an AI Agent designed to help Amazon sellers identify profitable product opportunities by scanning e-commerce trends, evaluating market demand and competition, and shortlisting suppliers.

Inputs Required:
- A keyword or niche idea (e.g., “portable blender”, “eco-friendly yoga mat”)
- Minimum profit margin (%)
- Minimum monthly search volume
- Maximum competition threshold (scale of 1–10)
- Target region (e.g., US, India)

Tasks:
1. Trend Research:
   - Search Amazon, Google Trends, Etsy, and TikTok Shopping to evaluate the popularity of the keyword.
   - Capture top 5 trending related keywords.
   - Summarize seasonality insights if any (e.g., spikes during summer).

2. Market Evaluation:
   - Find 5 top-selling listings on Amazon for the keyword.
   - Collect price, estimated monthly sales, reviews, rating, and fulfillment type (FBA, FBM).
   - Calculate rough profit margin: (Price – Est. Cost) / Price.
   - Flag products meeting the margin & volume criteria.

3. Competition Analysis:
   - Count total number of sellers.
   - Analyze top 3 sellers’ review counts.
   - Estimate barrier to entry (low/medium/high).
   - Score the competition level from 1–10.

4. Supplier Discovery:
   - Search Alibaba or IndiaMART for potential suppliers.
   - List top 3 suppliers with MOQ, cost per unit, and contact info.

5. Launch Plan Generation:
   - Recommend pricing strategy.
   - Suggest 3 key differentiators or features.
   - Suggest initial launch platform (Amazon, Etsy, own store).
   - List recommended ad budget and keywords.
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Youtube Link

RUNNER H LINK : Prompt Link
Outputs:

Image1

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Image5

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Write all outputs in a structured PDF with fields matching the Google Sheet schema below.

Generated PDF
AI Market Analysis - Google Sheets

How I Used Runner H

Workflow Structure

  • Input Collection
  • User enters a niche or product idea (e.g., "phone")
  • Trend Analysis (Runner H agent)
  • Scrapes Amazon bestsellers, Google Trends, TikTok Shopping
  • Extracts seasonality, rising interest, top keywords
  • Market Evaluation
  • Collects top listings from Amazon (price, reviews, rating)
  • Estimates profit margin, average monthly sales
  • Assigns a competition score
  • Supplier Sourcing
  • Pulls top matches from Amazon / IndiaMART with MOQ and pricing
  • Launch Strategy Generator
  • Recommends pricing, ad budget, key differentiators, and best platform
  • Data Export

All data saved to a structured Google Sheet: AI Market Watch – Q2

Use Case & Impact

Who it helps:

  • Indie e-commerce founders
  • Amazon FBA sellers
  • Product researchers
  • DTC brands

What it solves:

  • Manual product validation is time-consuming. This solution speeds up:
  • Market research
  • Competitor tracking
  • Sourcing suppliers
  • Launch planning

Social Love

Made with ❤️ by Shreya N

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