Topic 3.3: Data Collection for Product Research

Date

October 23, 2026

Time

04:00 PM Karachi

Duration

45 Minutes

Learning Outcomes

By the end of this 45-minute session, you will be able to:Leverage Native Dashboard Intelligence: Extract real-time traffic and conversion data using Daraz Business Advisor to spot emerging category gaps.Deploy Third-Party Scraping Tools: Use specialized product research extensions to extract competitor sales velocity, revenue totals, and review velocity. Analyze Search Demand & Keyword Indexing: Identify high-volume search queries and measure keyword competition levels before investing capital. Audit Competitor Stock Movements: Execute inventory tracking methods (X-ray stock level monitoring) to calculate exact daily order volume for top listings.Construct a Standardized Data Extraction Model: Build a clean, formula-driven spreadsheet to aggregate scraped data and calculate accurate profit predictions.

Session Agenda

(00:00 – 00:08) First-Party Data vs. Third-Party Scraping: Understanding the difference between native Seller Center insights (Business Advisor) and external browser extensions (e.g., SellerDash, XenonHunt, Daraz Toolkit). (00:08 – 00:18) Navigating Daraz Business Advisor: Extracting category traffic trends, conversion rate baselines, traffic source breakdowns, and revenue potential metrics directly inside the seller dashboard.(00:18 – 00:28) External Data Scraping & API Insights: Deploying web tools and Chrome extensions to scrape listing sales volume, estimated daily order velocity, revenue totals, and historical price changes. (00:28 – 00:37) Keyword Volume & Search Indexing: Mining search query data, keyword search volume, and giveaway/ranking calculations to assess customer acquisition difficulty. (00:37 – 00:45) Building the Master Product Research Sheet: Structuring an Excel/Google Sheets database to record scraped metrics, estimate net margins, and score candidate products.