How Retailers Increase Customer Satisfaction and Retention with the Snowflake Retail Data Cloud

Customers who feel understood are happy customers. According to a recent McKinsey report, 71% of consumers expect companies to deliver personalized interactions based on what they like—and 76% get frustrated when this doesn’t happen. To meet those high expectations, retail industry leaders are employing Customer 360 to gain deeper insights into their customers. 

Customer 360 involves giving the organization a 360-degree view of customers based on their interactions, transactions, and preferences, with touchpoints from sales to support. Armed with data from multiple sources and analytics that provide deep insights into each customer’s journey, retailers can do a variety of things: They can create personalized experiences that meet customers’ individual requirements. They can personalize offers based on customers’ characteristics and preferences. They can optimize support to create a better help experience. They can even perform predictive analytics to receive early alerts to potential issues. 

But data silos are the scourge of Customer 360. Data that lies in different systems is difficult to mine and analyze for business insights. 

To help companies combat fragmented data and employ Customer 360, the Snowflake Data Cloud centralizes data from various sources and in various formats—structured, semi-structured, and unstructured—in one secure repository. Snowflake Marketplace supplements a company’s  data with data from third-party sources. From there, companies can use pre-integrated features including data analytics, business intelligence, machine learning, and data management tools for deeper insights. They can then use those insights to make real-time, personalized, data-driven decisions to improve customer experiences and create happy, repeat customers. 

Here’s how a few of our retail customers are using Snowflake to satisfy and retain their own customers: 


To eliminate data silos and better serve the needs of customers, DoorDash turned to Snowflake’s Data Cloud to employ Customer 360. Snowflake’s multi-cluster shared data architecture scales to handle DoorDash’s data, users, and workloads with speeds twice as fast as before. Snowflake’s fully managed infrastructure with near-infinite scalability kept the BI team focused on data analytics and modeling. Ingesting DoorDash’s consumer, merchant, and Dasher data into Snowflake provides market managers across the globe with the latest supply and demand insights by 7 a.m. daily. Architecting DoorDash’s merchant portal on Snowflake provides merchants with data-driven reports for managing orders, inventory, and staffing. 

US Foods

Snowflake’s Data Cloud scaled to become US Foods’ single analytics repository for transaction data. Predictive analytics from DataRobot and Snowflake helps US Foods build forecasts and reduce the customer churn rate. Before removing products from its catalog, US Foods analyzes millions of historical records to estimate revenue impact, identify customers who are likely to leave, and develop individualized retention efforts. The combination of DataRobot and Snowflake modernizes operations and reports for US Foods, delivering instant, actionable insights with less hands-on manipulation and human error. 

Intelligent Shopper Solutions (ISS) 

Intelligent Shopper Solutions (ISS) enables retailers to get the most from its customer data by providing an industry-leading customer and marketing insights platform. ISS needed to adapt to meet the heavy demands of the company’s expanding client portfolio. To maintain the rapid speed to insights that originally set its solution apart from competitors, ISS needed a new data platform. ISS looked to Snowflake to modernize its infrastructure, ensure high levels of customer service to increase customer satisfaction and retention, and deliver effective solutions. Having a powerful platform provides better capacity and flexibility for running more complex reports and queries and for supporting concurrent users. Snowflake also improved ISS’ back-end configuration, which has led to a reduction in customer onboarding time of up to 50%. ISS now uses Snowflake for all its client data services, enabling it to easily transform, integrate, and monitor all client data. 

Discover how your organization can increase customer satisfaction and retention with Snowflake:

The post How Retailers Increase Customer Satisfaction and Retention with the Snowflake Retail Data Cloud appeared first on Snowflake.


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