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December 5-6, 2016: Training
December 6–8, 2016: Tutorials & Conference

How Lazada ranks products to improve customer experience and increase conversion

Eugene Yan (Lazada)
5:05pm–5:45pm Wednesday, December 7, 2016
Data science and advanced analytics
Location: Summit 1 Level: Beginner
Average rating: ****.
(4.00, 2 ratings)

Prerequisite Knowledge

  • Basic understanding of the ecommerce industry and experience shopping online.
  • Basic understanding of data science projects end-to-end, from planning to delivery.
  • Optional: Basic understanding of Spark and Python frameworks

What you'll learn

  • How Lazada solves the following:
    • Ranking products to improve customer experience and conversion
    • Introducing new products (kind of like the cold-start problem, but harder)
    • Emphasizing product quality through ranking


Ecommerce has enabled retailers to make all of their products available to consumers and consumers to access niche products not found in brick-and-mortar stores. This growth provides consumers with unparalleled choice. Nonetheless, the sheer number of products brings with it the challenge of helping users find relevant products with ease.

Lazada has tens of millions of products on its platform, and this number grows by approximately one million monthly. Lazada’s challenge: How can we help users easily discover good quality products they will like? How can we ensure product selection remains fresh and constantly updated?

One way to do this is through the ranking of products. Via ranking, Lazada helps customers easily find products that will delight them by ensuring these products appear in the first few pages. I’ll share how Lazada ranks products on our website. (Note: Google “how amazon ranks products” for some industry background)

Topics include how we:

  • Develop methodology (and tricks) to solve not-so-well-defined problems
  • Collect and store user-behavior data from our website and app
  • Clean and prepare the data (e.g., handling outliers)
  • Discover and create features useful features
  • Build models to improve customer experience and meet business objectives
  • Measure and test outcomes on our website
  • Built this end-to-end on our Hadoop infrastructure, with tools including Kafka and Spark
Photo of Eugene Yan

Eugene Yan


Eugene Yan is a data scientist at Lazada working on product and user problems to improve the online shopping experience for consumers and sellers across Southeast Asia. Passionate and experienced in using data to build data products and create positive impact, he is proficient in research design, data preparation, feature engineering, machine learning, ensemble, validation, and A/B testing. Also familiar with Python, Scala, Spark, R, SQL, Elastic, AWS, and software engineering and production practices.

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Picture of Eugene Yan
12/08/2016 6:54am +08

Slides available here: