E-commerce monitoring & intelligence platform drives 2x growth helping Amazon businesses on various markets

Location:

usa

Collaboration:

2020 – present

Technologies:

Kubeflow icon
Pandas icon
Tensorflow
Google cloud
Google cloud storage
GoogleBigQuery

About the Client

Our client is a successful platform for providing statistical data to e-commerce services around the world. They provide services that help the world’s leading brands power their e-commerce business: detect insights to improve sales performance, implement data-driven solutions to increase conversion rate in particular product categories, and tie and optimize the performance of online and offline stores together.

Business Context

Amazinum Data Scientists have joined the customer’s team in order to adopt machine learning algorithms to let retailers

  • Maximize product visibility
  • Improve supply chain management
  • Monitor competitor and retailer price dynamics
  • Provide data predictions to boost advertising ROI
  • Analyze in-stock/out-of-stock products to optimize availability issues
  • Track user behavior

Data Science in Action: Machine Learning for E-commerce Platform

ML algorithms

Specifications

Our team of Data Scientists has evaluated different versions of models autonomously, as well as changed the model evaluation pipeline in Kubeflow. In addition, since the project uses GCP, we need to work a lot with Google Cloud, BigQuery, and BigTable cloud storage.

Check up a few machine learning use cases introduced in e-commerce platforms:

  • Using the graphics below, sellers can analyze personal as well as competitors’ sales performance of the various products under one brand over a specific period
Monthly sales graph
  • Also, the retailer can evaluate the sales performance of multiple brands in general categories or particular products under one brand.
Sales and market share graphs
  • Customers can see the visualization of their personal or competitors’ year or monthly sales in the following graphic.
Monthly graph sales
  • If the sellers want to analyze the statistics of product sales for one category they get the graphic below. In addition to all of the above, the retailers can analyze the competitor`s sales for one product for a certain period.
Sales graph

Benefits of working with the Amazinum team

  • End-customers of the service saved more than 1000 hours, replacing manual labor with the machine;
  • Accurate calculation and predictions based on real data allowed brands and manufacturers to improve services Improve work with their customers
  • Personalized decisions on the prices of products, their popularity, and competitiveness had a positive impact in the form of increased income

Outcome

With the help of machine learning algorithms, a historical curve was created that determined the availability of goods and predicted when goods would not be available. In this case, the customer could choose the region, store, period, and category of goods and see if the desired product is available.

Thanks to this solution, sellers can:

  • Increase their sales among competitors and improve their rating
  • Obtain data on the volume of their products and the products of competitors
  • Improve sales strategy
  • Analyze traffic and easily predict stock trends
  • Monitor the price dynamics of competitors and retailers
  • Get information about which product is more profitable and have to be able to invest in its advertising
Content:

Vitaliy Fedorovych

CEO, Data Scientist at Amazinum

Vitaliy Fedorovych contact us photo

Hello there!

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