Automated Reporting for an Ecommerce Warehouse

The Challenge

A specialty ecommerce company runs a 16,000 sq ft warehouse, ships 26,000 orders a year, and manages over 5,000 products across 15,000 SKUs. Two systems run the operation: one for inventory and purchasing, one for the online store and orders. Neither talks to the other.

Every morning, the operations manager would log into the inventory system, download three reports, open each spreadsheet, and copy the data into the planning sheets the business runs on. The owner would separately log into the ecommerce platform, pull the previous day's sales numbers, and type them into a cash flow tracker. Combined, this took over an hour every day. On top of the time, the product catalog, which drives what customers see on the site, was only refreshed monthly. Products could go hidden, get mislabeled, or fall out of stock without anyone noticing for weeks.

The data they were working with was always a little stale, a little suspect, and it took real effort just to keep it that way.

Key pain points:

• 10+ hours per week spent on manual data entry across two systems
• Product catalog only updated monthly, meaning visibility issues could go undetected for weeks
• Manual copy-paste introduced errors that compounded over time, eroding trust in the numbers
• No automated alerts when something went wrong. Problems surfaced only when someone happened to notice.
• The owner's daily cash flow tracking depended entirely on a manual morning routine

The Approach

The team didn't need new dashboards, new tools, or a data warehouse. They needed the data they already use to show up automatically in the spreadsheets they already trust.

We built five automated pipelines using the APIs already available in both systems, writing directly into the existing Google Sheets the business runs on. No new software to learn. No workflow changes. The same spreadsheets, the same tabs, the same formulas. Just no more manual entry.

What we built:

• Stock levels feed: Pulls current inventory for all 5,000+ SKUs from the inventory system API every morning at 4am
• Report feeds: Parses three scheduled reports (last 30 days of sales, 12-month sales summary, and days aging) delivered via email, converts them, and writes directly to feed tabs in the planning sheet
• Daily revenue pipeline: Pulls 8 revenue metrics (orders, gross sales, net sales, taxes, shipping, and more) from the ecommerce API every morning at 5am
• Product catalog pipeline: Pulls the full catalog of 15,000+ SKUs with status, visibility, and pricing from the ecommerce API at 6am, with change detection that logs every status change
• Formula guard: Runs at 7am to protect 130,000+ formulas from breaking when new data rows are added
• Health monitoring: Automated checks confirm every pipeline ran successfully. If something fails, the team knows immediately.

The Results

The operations manager got an hour back every morning. No more downloading reports, no more copying rows, no more checking whether yesterday's numbers made it into the sheet. The owner stopped manually entering sales data. Both now walk in to spreadsheets that are already current.

Product catalog freshness went from monthly to daily. A hidden product or a pricing error that used to sit unnoticed for weeks now surfaces within 24 hours through change detection logging.

The ongoing managed support costs a fraction of what the manual labor was costing. Even on labor savings alone, the business sees a 6:1 return, before accounting for data quality improvements and the errors that no longer happen.

What's Next

With the daily data foundation in place, the business is exploring AI-powered product recommendations, smarter inventory reorder alerts, and automated cash-out analysis for slow-moving stock. The reporting infrastructure we built is designed to support these additions without rebuilding anything.