Customer Intelligence is the New Heartbeat as Consumerization Takes Hold

Key to Discovering Growth Opportunities and Profitability for Brands and Retailers

Consumerization — which in the context of the Consumer Value Chain — means the Consumer, is in control of the path to purchase.  For Brands, engaging directly with consumers is not an option but a necessity. Until now, Brands relied on Retailers to inform them about consumer behavior and purchase trends. For Retailers, the traditional business model of getting a customer to come to the store is under attack.  So for both Brands and Retailers, building dynamic Customer Intelligence models becomes paramount and hence is the New Heartbeat to track and monitor to seize growth opportunities, be profitable and build sustainable advantage.

In the digital era of connectivity and Big Data, the shopper’s path to purchase has completely changed and is now more of a digital eco-system that the shopper uses to make the best purchase. The most telling impact on this new digital path to purchase is the proliferation of mobile devices and mobile apps. This is having a significantly negative impact on the traditional retail business model. Shoppers, empowered by these mobile apps, are comparing prices, reading reviews, getting recommendations, and more while they are in the store.

So how then should brands & retailers leverage and engage with this new digital path to purchase — Use Big Data Analytics to correlate data from internal and shared external sources to build multi-dimensional views of the shopper and discover actionable insights that allows both brands and retailers to address this shopper’s quest for a purchase into a sale in new ways.

In this session, you will learn from a case study how to leverage real-time big data analytics to build your customer intelligence models using the following capabilities:

1. Correlate data, in real-time, from multiple sources without moving data or creating expensive data warehouses. Sources could be customer profiles, social network brand pages, campaign responses, coupon redemption/usage patterns, and more.
2. Automatically discover patterns and trends on shopper behavior, attitudes and preferences in real-time or otherwise.
   
3. Leverage out-of-the-box and custom Key Performance Indicators and Data Models that allow you to track and monitor shopper behavior in real-time or otherwise.

We will also discuss the benefits of building such models and how it can enable relevant personalized messaging, positioning, service experiences, offers and more.

Big Data Retail Forum 2013 Special

Welcome to a special offer for Big Data Retail Forum attendees only! — 2GB Analysis Volume instead of 1 GB. Please fill out the following form.                  *required fields