Tulip, a mobile platform for retail, has partnered with Google Cloud to improve store performance and sales associate effectiveness using Google Cloud’s machine learning and analytics. By analyzing data from Tulip’s in-store mobile applications, retailers can use machine learning to uncover customer insights and sales opportunities.
The new Tulip solution will make recommendations on when to connect with customers and how to engage with them with highly personal and relevant communications. This intelligent and proactive engagement with customers will elevate the shopping experience, increase loyalty and drive sales for retailers.
“Tulip is about enabling conversations, connections, and personal friendships between real humans, in this case between store associates and shoppers,” said Ali Asaria, founder & CEO of Tulip. “Every day, Tulip collects millions of data points around omnichannel shopper behavior. By integrating Google’s machine learning and big data products into our core platform, we’re now able to use that data to provide intelligent insights and recommendations to our end users.”
Key Google Cloud products Tulip will leverage include:
- Google BigQuery for in-store retail analytics to identify trends and gain insights related to customer behavior, associate activity, store operations, and in-store sales.
- Google Cloud Machine Learning Engine to build machine learning models and prediction services to drive behavioral recommendations for store associates and managers.
- Google Kubernetes Engine for rapid application development, management of containers and easy deployment of applications and services.
- Google Cloud Platform as the new foundation for Tulip’s next generation retail platform for store associates to access products, manage customer information, and check out shoppers, and communicate with clients.
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