How to automate marketplace reporting for Amazon, Flipkart and quick commerce

Most D2C brands in India don't sell on one marketplace; they sell on six or more. Amazon, Flipkart, Myntra, Nykaa, Blinkit, Zepto, Swiggy Instamart, your own website, and often modern trade too. Each has its own seller portal, its own report formats and its own definitions.

The result is familiar: someone on the team spends the first hours of every day downloading reports, cleaning them up and pasting them into a master spreadsheet. It's slow, it's error-prone, and it stops the moment that person is on leave.

Here's how to replace that with automated marketplace reporting, step by step.

Step 1: List the reports you actually use

Before automating anything, write down every report your team downloads and what decision it supports. A typical list looks like this:

• Sales / orders: daily units and revenue by SKU, per channel
• Inventory: stock at each marketplace warehouse or dark store
• Purchase orders: for quick commerce and B2B or vendor models
• Returns and cancellations
• Advertising: campaign spend and attributed sales
• Settlements / payments: payouts, fees and commissions

You'll often find that several reports exist only because another report was missing something. Automation is a good moment to simplify.

Step 2: Decide how each report will be collected

There are three common ways to collect marketplace data automatically:

1. Official APIs. Some platforms offer APIs for orders, inventory or ads. These are the most reliable option where available.
2. Scheduled report exports. Some portals can email reports on a schedule, which can then be parsed automatically.
3. Browser automation. For portals without an API, a script can log in and download reports, much like a person would. This needs good monitoring, because portal layouts change.

Most brands end up with a mix of all three. What matters is that every source is monitored, so a failed download is noticed the same day.

Step 3: Build a SKU and location master

This is the step most brands skip, and it's the one that makes everything else work. Every channel identifies your products differently: ASINs on Amazon, FSNs on Flipkart, style IDs on Myntra, partner item codes in quick commerce. Warehouse and city names differ too.

A master mapping table links each channel's identifiers to your own SKU code, product name, category and pack size, and each warehouse to a standard city and region. Once this exists, you can compare any metric across channels.

Step 4: Store everything in one place

Instead of a master spreadsheet that gets overwritten every day, load each report into a database or data warehouse, such as BigQuery or Postgres, and keep the full history. That gives you:

• Year-on-year and month-on-month comparisons
• One source of truth that every report and dashboard reads from
• The ability to answer new questions without re-downloading old reports

Step 5: Define your metrics once

"Sales" can mean gross order value, net of cancellations, net of returns, or settled revenue. Agree on definitions for your core metrics, calculate them once in the data model, and use those same definitions everywhere. This is what ends arguments about whose number is right.

Step 6: Deliver reports where your team works

The final step is getting the right numbers to the right people automatically:

• A daily summary by email or Slack with yesterday's sales, stock alerts and anomalies
• A live dashboard for deeper analysis by channel, category and SKU
• A weekly business review pack generated automatically
• Google Sheets extracts for teams that prefer to work in spreadsheets

What good looks like

When marketplace reporting is automated, the morning routine changes completely. Instead of downloading reports, your team opens a summary that's already there, sees what changed and why, and spends their time acting on it. New questions get answered in minutes because the data is already clean and joined.

Key takeaways

• Start by listing the reports you use and the decisions they support.
• Collect data through APIs, scheduled exports or monitored browser automation.
• A SKU and location master is what makes cross-channel reporting possible.
• Store full history in a warehouse and define metrics once.
• Push reports to people automatically instead of waiting for them to go looking.