How can retailers transform Big Data into uber-relevant oers that make a customer’s purchase activities highly predictable and increasingly profitable? It’s not by focusing on which channel initiated the shopping journey: Rather, today’s mobile-enabled customers’ unique tastes, influencers, likely behaviors and other personal and predictable factors ― not their bricks or clicks starting point ― must be at the heart of all customer-centric retailing.
While many continue to wrestle with managing Big Data, channel integration and how to translate channel activities into transactions, other more enlightened retailers have advanced to true customer-centric models. These retailers continually gain knowledge about customers’ preferences and behaviors; then use decision-science tools, many developed for the financial services, travel and hospitality industries, to distill Big Data into bite-sized slices, producing accurate retail predictions. Their customer-centered retail strategy provides clear-cut scientific answers to their once-perplexing business questions. It produces highly relevant and personalized oers that drive customer relationships, not just transactions ― all critical to transforming the commerce ecosystem to maximize long-term enterprise value.
Imagine being able to calculate what customers are likely to buy before they even inquire! Or to recommend products (including size, color, style and season) personalized for a customer’s upcoming vacation, business trip, favorite music venue or birthday shopping spree. Imagine the ability to draw on hours-new consumer data ― gathered across myriad customer-facing touch points ― that is condensed, then dissected to correctly segment, predict, localize, personalize, merchandise, pre-order, stock, cross-sell, up-sell and much more…..all without human intervention.