26 – 29 March 2018
Hotel Jen Tanglin Singapore

Conference Day 2 | 28 March 2018, Wednesday

8:00 am - 8:55 am Morning Refreshment and Registration

8:55 am - 9:00 am Chairman Opening Remarks

IMPROVING CUSTOMER ENGAGEMENT, PRODUCT & SERVICE OFFERINGS THROUGH MACHINE LEARNING

9:00 am - 9:40 am How to: Better understand customers’ behaviour to drive business growth through machine learning

Vivek Nair, Head of Analytics, South East Asia,Visa
  • Using Machine Learning applications and prescriptive analytics to micro-segment customer groups
  • Monitoring customers’ behavior, profiles and patterns to discover actionable insights
  • Providing more personalized and tailored customer service to different customer segment groups
  • How can we leverage on Machine Learning and prescriptive analysis to increase engagement with customers and take pre-emptive measures to raise customer loyalty?

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Vivek Nair

Head of Analytics, South East Asia
Visa

9:40 am - 10:20 am Enhancing Carousell’s user experience with deep learning powered features

Lucas Ngoo, Co-founder & Chief Technology Officer,Carousell
  • Improving categorization and classification with deep images features
  • Shortening buyer-seller processing time
  • Personalising the user experience
  • Listing products for sale from 30 seconds to 3 seconds
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Lucas Ngoo

Co-founder & Chief Technology Officer
Carousell

10:20 am - 11:00 am Morning Tea and Networking Break

11:00 am - 11:40 am Enhancing user experience with machine learning powered personalisation

Nikolay Novozhilov, Head of Digital Products,NTUC Link
  • Data beats algorithms. Data enrichment.
  • What do you do, if you are not Amazon? The problem of cold start.
  • Personalisation. Efficient? Overrated? Creepy?
  • Building a model is not enough – how do you bring it to production?
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Nikolay Novozhilov

Head of Digital Products
NTUC Link

11:40 am - 12:20 pm Improving customer engagement with personalization of recommendation engines

  • Growing the data science team – doing more with limited resources
  • Building and implementing a personalized product-based recommendation engine
  • Overcoming recommendation engine cold start problems
  • Delivering it as a data product to customer 

12:20 pm - 1:00 pm Increasing travellers’ conversion rate with personalised recommender systems from product-based to user-based

  • Proposing most-valuable option through predictive analysis and behavioural analysis
  • Moving from product-based recommender system to user-based recommender systems 

1:00 pm - 2:00 pm Networking Lunch Break

ENHANCING OPERATIONAL EFFICIENCY & ACHIEVING COST REDUCTION

2:00 pm - 2:40 pm Optimizing route planning with machine learning

  • Reviewing daily delivery performance  of drivers daily delivery performance  of drivers
  • Improving realistic and more accurate route plans
  • Identifying hidden inefficiencies to promote continuous distribution performance improvement 

2:40 pm - 3:20 pm [Case Study] How to: Improve Demand Prediction across 5 Business Ventures for Efficient Inventory Management and Optimized Pricing Strategies with Machine Learning

·         Identifying trends, seasonality, calendars and daily consumer patterns to improve demand forecasting
·         Incorporating real-time data into forecasting model
·         Purchasing the right amount, at the right time, at the right place  

3:20 pm - 4:00 pm Afternoon Tea and Networking Break

4:00 pm - 4:40 pm How to: Leverage on Data to Improve Estimated Time of Arrival with Faster Services

  • Evaluating Recency, Frequency, Monetary of rider to segment customers
  • Leveraging on historical data of similar routes to predict estimated time of arrival with actual time taken
  • Results yielded: Improving ride requests by 15% and reducing cancellation by 5% 

4:40 pm - 4:45 pm Chairman Closing Remarks