Toronto-based retail startup Tulip has announced a partnership with Google Cloud to improve store performance and sales associate effectiveness by using Google Cloud’s machine learning and analytics.

The new Tulip solution will leverage Google Cloud Machine and Google BigQuery to make recommendations on when to connect with customers and how to engage with them.

“Tulip is about enabling conversations, connections, and personal friendships between real humans, in this case between store associates and shoppers,” said Ali Asaria, founder and 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.”

Tulip’s mobile platform allows retail store associates to use a tablet or smartphone to access customer preferences, complete sales checkout, and communicate with clients. The company recently launched TurnKey Edition, which allows retail associates to use customer preferences, past interactions, and recent purchases to send personalized messages.

By analyzing data from Tulip’s in-store mobile applications, retailers will be able to 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 by leveraging Google Cloud products, including Google Cloud Machine Learning Engine and (to build machine learning models and prediction services to drive behavioral recommendations for store associates and managers) 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).

This article originally appeared in Betakit