Cleanse and cross-reference e-commerce data to better understand sales

The context

An e-commerce site specializing in prestige wines was having trouble analyzing its online sales because its databases were not connected :

• On the one hand, ERP with inventory and prices
• On the other, the online store with sales and product descriptions.

Reconciliation was manual, with frequent errors. It became essential to align the databases and make analyses more reliable.

What I’ve done

• Data matching via a link table between ERP and online store
• Data cleansing (duplicates, incorrect types, missing fields)
• Univariate price analysis to detect outliers

• Calculating sales by product, and overall total

• Interactive graphical representation of price anomalies
• Consolidation of all data into a final Excel file ready for sharing

The results

• Unified pricing, sales, inventory and product database
• Detection of inconsistent prices for easy correction
• Clear visualization of high-selling products
• Opportunities identified to improve stock management and sales analysis

What about the technical side ?

• Python (Pandas) for data processing and merging
• Plotly for clear, easy-to-read interactive charts
• Univariate analysis: descriptive statistics, outlier detection
• Creation of a final shared Excel file for business circulation

Let’s talk about it !

Do you manage an ERP system, an online store or several fragmented databases?
I can help you with :

• Consolidate your data for more reliable decision-making
• Detect input inconsistencies
• Set up product performance indicators

📩 Contact me to discuss your requirements !