Get ahead of your customer returns using AI with these simple steps

  • Malavika
  • December 2, 2019

With the holiday season underway, many of us are looking forward to relax and spending time with family and friends.
However for those in the retail industry, this is make or break season with holiday sales accounting for as much as 30–40% of the annual sales and setting the benchmarks for rest of the year. Brands launch their marquee products and biggest discounts and offers with hopes of driving maximum revenue from the season. Even with great sales at the starting of the season with Black Friday, business have to contend with another problem — customer dissatisfaction with the product. There are many repercussions to it — from returns to bad reviews and worse still, a permanently lost customer.
The reasons for customer returns could be many. Customers may have purchased products to “try” in multiple sizes or variations, product description/ size/ images may not have been true to the actual product, product may not have met customer expectations, could not be used because of inadequate instructions, better pricing and even — no longer needed. The returns could be processed online or in store, both the sources should be required to capture reasons for return. Customers also leave reviews on brand sites and eCommerce marketplaces, which are great indicators of why they loved it or why did not work for them.

Customer service, marketing and merchandising/ product teams are on high alert to identify trends and drivers for customer dissatisfaction and returns. While the service teams can gauge the trends, to get a view of how big the problem is difficult and the held belief is that this is mostly a reactive situation and it is too late to make any changes to affect a change. However that is not so.

Using sentiment analysis product such as Bewgle’s Lumens platform, retail and eCommerce companies can quickly identify the drivers of returns and customer dissatisfaction from support tickets, reviews and feedback surveys. This can help the customer service teams to be prepared with answers for top issues and help save the sale, update FAQs and increase customer loyalty. For merchandising teams, the ability to identify gaps in product information can allow them to update the product descriptions and images, get pricing right and identify channel, packaging and delivery related issues for working with their vendors. And marketing teams can take the delighters from customer verbatim and use it in their marketing content to amplify the product popularity.

With no integration required to get started and 7 day free trial, what is stopping you from getting ahead of your customer issues and making best of this holiday season?

Contact us today at to get started.

  • Tags:
  • AI
  • Analytics
  • Arlo
  • AWS Lambda
  • Beauty
  • Brands
  • competitive analysis
  • Customer Data
  • Customer Experience
  • Customer Reviews
  • DevOps
  • DIY market research
  • DTC
  • E-Commerce
  • Earbuds
  • Electronics
  • Finance
  • fitness
  • GKE
  • Jenkins
  • market research
  • Natural Language Processing
  • Product
  • Rapid API
  • Returns
  • Ring
  • sentiment analysis
  • Serums
  • social media
  • Sofas
  • Tech
  • video doorbells
  • voice of customer
  • wellness
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