Improved the seller experience for a leading e-commerce platform

  • October 11th, 2018

What We Did: Created a comprehensive framework to enable a data-driven decision process to better engage with sellers interacting with the platform

The Impact We Made: The data-driven initiatives to improve trust among sellers resulting in an incremental annual revenue of $1.5MM

Summary – Improving seller experience and satisfaction

The client wanted to stem seller dissatisfaction and proactively protect genuine sellers from abusive buyers. Mu Sigma worked on a series of initiatives to enable the client achieve this goal which involved, to name a few, creating a framework to defi­ne a bad selling experience, formulating rules to identify and auto-suspend abusive buyers, as well as create a seller trust score to fi­lter out genuine sellers.

About The Client – A leading commerce platform and technology company

The client is a global technology company that enables online commerce through marketplaces and payments segments. They offer online platforms, tools and services to consumers and businesses of all sizes globally. The client is the world’s most diversifi­ed casino entertainment provider and an industry leader in establishing a customer loyalty program.

The Challenge – Declining NPS scores

The client was facing seller dissatisfaction, reflected by declining Net Promoter Score (NPS) from seller surveys. Though there are strict policies to ensure a safe marketplace for transactions, those are often buyer biased. Genuine sellers sometimes are victims of malicious activity from abusive buyers. The client felt the need to improve seller NPS by implementing policies to protect genuine sellers.

The Approach – A new trust score metric

A two-pronged approach was used to improve seller NPS: focus on reducing bad selling experiences (BSE) and generating goodwill among sellers

  • A framework was created to de­ne BSE using historical buyer-seller interactions. The framework resulted in creation of a global metric that spanned different orgs and was monitored on a weekly basis to assess the impact of new initiatives
  • Another framework was designed to generate heuristics-based rules to auto-suspend abusive buyers on the platform
  • A trust score metric, based on seller transaction history, was also created. Highly trusted sellers were refunded through a “refund campaign” to create a better seller experience

The Outcome – Refund campaign to boost seller confidence

  • The BSE has been adopted as a key metric across almost all countries where the client operates
  • The refund campaign was a huge success and has helped boost seller confi­dence. Since implementation, around 2,000 abusive buyers have been suspended automatically; thereby preventing an annual loss of around $2MM to sellers (that are small businesses)
  • These initiatives helped reduce the seller detractors by 10% YoY, leading to a $1.5MM in incremental annual revenue