To deliver a personalized brick-and-mortar shopping experience for each kind of customer, you have to understand customers’ demands, price expectations, doubts in choosing products or services, etc. Collecting and analyzing customer transaction data through an application is one of the efficient ways to make it done. However, many people wonder how does it work?
In this video, we will meet Wayne Lin, Co-Founder of GetUpside. That is a D.C.-based, mobile-app tech startup that uses machine learning to help their 25 million daily customers save money and get more value for their dollar. Based on the success in GetUpside, he will share with us some information about customer analytics data, including the following matters:
- The way to personalize the brick-and-mortar experience
- What scaling their app looks like across markets?
- How does GetUpside use data to change consumer behavior?
All video and audio footage used is either licensed through either CC-BY or from various stock footage websites. All creative commons footage is listed at the end of the video and is licensed under CC-BY 3.0.
Co-Founder of GetUpside
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