April 10, 2026
The company runs a large online auction platform and shopping website that connects buyers and sellers in over 190 countries. Their website has millions of sellers with 1.9 billion global listings and over 132 million active buyers.
THE CHALLENGE
The company identified categories that are focused on enthusiast buyers who tend to spend higher amounts on their annual purchases than other segments of buyers. These categories included luxury handbags, sneakers, automobile parts, trading cards and watches. To improve buyer trust, the company introduced an authentication verification program which included a team of experts that would verify each product, before it was sent out to the buyer.
Under the watches category, there was a sub-category of luxury watches which consisted of both new and pre-owned products. The business partners who managed the sellers that dealt in luxury watches received regular reports on the top selling products in that sub-category. They needed to understand the optimized combination of listed luxury watches that would increase the overall sales and Gross Merchandise Volume (GMV, which is the total value of all paid transactions inclusive of shipping fees and taxes).
Additionally, these business partners did not have insights into the pricing competitiveness of the luxury watches segment, as compared to other leading online retailers.
The company needed an analytics partner to develop an Inventory Intelligence Platform that included a comprehensive framework to understand current inventory levels for luxury watches and enable business partners to take corrective action based on pricing competitiveness.
THE SOLUTION
The Prescience team performed exploratory data analysis (EDA) to understand the luxury watches segment and identify the leading brands and top sellers on the marketplace. To compare the same items across different e-commerce platforms, the solution required the creation of unique product-specific inventory identification numbers, which consisted of a combination of each watch’s attributes. Next, the team chose a leading competitor’s website to map the luxury watches listed on both sites. To ensure that outlier products from both websites did not skew the overall results, our team used the Interquartile Range approach for data cleansing.
Each product listing on the competitor website had detailed information with categories that did not match what was on the company’s website. Our team defined a pricing methodology which split the overall inventory into fixed buckets, which were then mapped to the products on the competitor website.
This new Inventory Intelligence Platform helped the business partners immediately understand the specific luxury watches for which their prices were not competitive. In these cases, they discussed different pricing strategies with the sellers to improve the probability of conversion. For luxury watches where the pricing was significantly lower than that of the primary competitor, the business partners guided the sellers on marginally increasing the pricing, and hence profitability, without impacting the overall sales volumes.
The insights from the platform showed which site had the most competitive pricing for each of the listed luxury watches, whether they were new with tags, new without tags or preowned etc. These insights also provided brand wise views of pricing competitiveness along with the number of mapped products for each brand.
The different technologies used for this engagement included,
- SQL
- Tableau
- Python
Microsoft Excel
THE IMPACT
With the Inventory Intelligence Platform, the business partners now have detailed insights on the pricing competitiveness of each luxury brand and all the luxury watches that are sold on their marketplace. The business partners are able to help sellers dynamically update their product wise pricing to be more competitive and increase their sales.
