Customer Behavior Analytics for Retail
Deeper, data-driven customer insights are critical to tackling challenges like improving customer conversion rates, personalizing campaigns to increase revenue, predicting and avoiding customer churn, and lowering customer acquisition costs. But consumers today interact with companies through multiple interaction points — mobile, social media, stores, e-commerce sites and more. This dramatically increases the complexity and variety of data types you have to aggregate and analyze.
Personalizing the In-Store Experience With Big Data
The advent of people-tracking technology offers new ways to analyze store behavior and measure the impact of merchandising efforts. A data engineering platform can help retailers make sense of their data to optimize merchandising tactics, personalize the in-store experience with loyalty apps and drive timely offers to incent consumers to complete purchases with the end goal being to increase sales across all channels.
