In 2016, Coca-Cola updated its core loyalty marketing program to a mobile-first web platform. The program requires consumers to input 14-character proof-of-purchase codes for entry into promotions. Consumer engagement would have been badly impacted if users had been required to thumb-enter these codes into web forms on their mobile devices. To solve this problem, Coca-Cola built a custom Optical Character Recognition (OCR) capability using Convolutional Neural Networks and TensorFlow. This TensorFlow CNN is hosted online for web-based promotions and installed natively as a component of the Coca-Cola iPhone and Android apps. Patrick Brandt of Coca-Cola North America will share his design for Coca-Cola’s mobile proof-of-purchase platform and discuss some of the challenges that his team overcame to deliver a fast, highly-accurate custom OCR using TensorFlow.
Published on April 11, 2018 by Carlo LepelaarsCategory AI Machine Learning Talk Tensorflow Tag A.I. (Artificial Intelligence) Coca Cola Google Machine Learning Marketing OCR (Optical Character Recognition) Patrick Brandt Talk Tensorflow
December 19, 20185971 0
April 24, 20199081 0
July 23, 20193491 0