AnalyticsEgg

AnalyticsEgg

Client came to us with a request to build MVP for SaaS service that would collect data from different eCommerce platforms and show actionable stats for store owner.

The biggest challenge of this project was in getting different eCommerce platforms data format under one roof and display in the same format for end-users.

Second problem we’ve got was with quick display of millions of orders data. So we had to develop own data mining approach which made multi-annual stats with daily breakdowns perform fast.

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SoftFormance team started with Magento platform support. Then added Magento2 and finally also integrated WooCommerce stores.

Key features implemented:

  • Customer Segmentation based on recent buys and customer activity
  • Bubble Graph with Customer Segments displaying not only Customer Segment but also size of that segment
  • Ratio KPIs – displaying multiple stats for Average, Min and Max Order, same for Revenue, Orders and Items Sold
  • Volume KPIs graphs – displaying multiple stats for numbers of Customers, Orders, Order Value, Items per Order, etc…
  • Product Recommendation algorithm which give store owner a tool to predict which products would be most popular within the next 28 days and act accordingly
  • Product Recommendation based on Customer Segments

Using these data store owners can be prepared for the next months and adjust their marketing strategy appropriately.

 

Key Technologies used:

  • Python and Django web framework
  • PostgreSQL database
  • Celery for background tasks
  • jQuery for front-end app
  • chart.js
  • Own approach to data mining

More Screenshots:

Bubble Graph

Bubble Graph

Volume KPIs

Volume KPIs

 

 

 

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Posted on

December 25, 2017