Success Story
Senheng
AI-predicted customer list generated order values 12x greater than that of rule-based segmented list
“In Senheng, we are always dedicated to deliver the best shopping experience to our customers. With this goal in mind, we’ve worked with Appier closely to help the business adapt to customer data platform and AI technology so that we can understand each customer’s behavior and preferences, whether they shop online or offline.”
June Tai Tze Ten
Brand Story
Established in 1989, Senheng is Malaysia’s leading consumer electronics chain store. The retailer has over 100 physical stores in Malaysia as well as a website for online shopping. Senheng carries over 280 brands in Mobile & Tablets, Computers & Laptops, Home/Kitchen Appliances, Health & Beauty and categories, and is committed to being a one-stop shop for consumers’ electronic needs. As the company seeks to evolve with consumer needs and consumption habits, it has undergone significant digital transformation to ensure an Online-Merged-Offline (OMO) experience.
Goals
As the leading consumer electronics store, Senheng is regularly promoting new products. It wanted an accurate and effective way to identify the right customers to target with each product and how best to segment their massive and ever-growing customer base to precisely promote their products. In a market that was increasingly operating online, Senheng wanted to replicate the edge it has had in physical retail online.
Challenges
Lack of transaction data for promoting new products
When it came to promoting new products, the client had no previous transactions to use as reference for which customers to target. In the particular case of a new smartphone series, the client had a difficult time gauging which type(s) of customers the product would sell to. It needed help narrowing down potentially purchasing customers so it was not blindly marketing to everyone.
Limited ability to generate list of purchasing customers to target
Like most retailers, the client relied on rule-based segmentation to figure out whom to target with what product. This traditional approach generated limited results and was in need of innovation.
