Can retailers really predict shopper behavior by leveraging big data?
According to The Retail Equation, the answer is yes. Not only are they helping retailers predict shopper behavior, but they are shaping the future of shopper behavior.
Preventing return fraud is no small feat for retailers. In fact, this is estimated to be an $18 billion per year problem. The National Retail Federation estimated that return fraud in the 2013 holiday season alone would cost retailers $3.4 billion.
Staying ahead of return fraud is a priority; the reality is that it’s not easy.
What the Retail Equation has been able to do with big data is a great example of data enabling retailers to move beyond what happened and into prescriptive what will happen analytics—all delivered in real time at the point of sale. These actionable insights are driving better outcomes.
The Retail Equation isn’t just analyzing individuals, they are analyzing people, patterns and associations, thus enabling retailers to act with confidence at point of sale to either approve or deny a purchase. For shoppers, thinking twice about fraudulent returns is a reality.
Big data and analytics have opened a door for retailers to better predict buying patterns and, in this case, prevent fraud, save money and directly impact the bottom line.
To learn more about IBM Big Data & Analytics, check out these related links:
- IBM big data and analytics portfolio
- IBM Big Data & Analytics YouTube channel
- IBM Expert Integrated Systems YouTube channel