eCommerce catalog management software development using machine learning
Home > Blog > Use Case: ML Based Product Catalog Management To Declutter Data Inconsistency

Use Case: ML Based Product Catalog Management To Declutter Data Inconsistency

13 Aug 2021

eRetailers spend a significant amount of their time & money to understand customer needs to develop & sell the right products. As part of this approach, they focus on maintaining product information and storing data of user’s buying history.

However, there’s a limited emphasis on accurately managing the product catalogs. Their optimization is central to any eCommerce business today. By simply listing the product online doesn’t help if the consumer is not able to intuitively locate and access it. And, with web medium, it is a lot easier for the potential customer to switch sites between you and your competition. Scary, isn’t it?

With the advent of machine learning (ML) and Big Data, the manual processes for product classification can go away for good.  An ML product catalog management system can help capitalize on data to optimize cost and TAT with zero human errors to meet the growth.

If you’re a business keen to improve product assortment and achieve faster syndication across product data across channels, then this blog is for you.

You would agree, from small sellers to large enterprises, the accurate management of product catalogs on marketplaces is a huge challenge. We at Rishabh Software have experienced data scientists in place who can do the best application of machine learning for product catalog optimization. They help automatically classify and optimize product attribute values to improve the search accuracy of product catalogs.

Product Catalog Management Use Case

To put things into perspective, here’s a recent showcase of how we helped a Europe-based Fashion Retailer deliver a deep learning solution to meet their business objectives.

Here’s how we helped the client:

  • Data identification & preparation – Reduction in attribution errors by 25%
  • Increase in sales by 15%
  • Data modeling – Improved search accuracy & enhanced user experience
  • Testing & On-time Deployment

Listed below are the key considerations of what we try to understand before we design and deliver the custom ML-based Product Catalog Management solution that fits your demand;

  • Analyze the entirety of the product base with the overall value proposition
  • Identify the triggers that drive sales
  • Analysis of current product offerings and how are they organized
  • Key attributes of products – size, color, price, etc.
  • Target customer analysis and their behavior patterns, learn how we help enhance and boost business strategies with Customer Lifecycle Value
  • Average shopping and purchase cycles
  • Detailed analysis of factors leading to why customers might move away from your website

Last Words

A product management system powered by Machine Learning cohesively supports the product catalog data management from creation to fulfillment. It helps reduce manual efforts and improves time-to-market.

Struggling with Product Catalog Management?

Leverage ML capabilities to optimize product catalog in the most user-friendly and profitable way