Powering the omnichannel personalization engine

Modern enterprises leverage big data to build a 360° view of the customer to uncover customer insights, reveal consumer sentiments, and predict outcomes. Layer that with a mobile-first approach and you have the ability to deliver personalized experiences in your customer's moment of need across online and offline touchpoints. 

The complexity becomes more interesting as you plan for specific customer outcomes.

Big data and analytics drive actionable insights

Simple rules-based recommendations, segmentation, and targeting don’t cut it for the next-generation experiences that consumers have come to expect. Delivering deep personalization across journeys and touchpoints goes beyond transaction histories. Savvy businesses collect data like mobile location, social sentiment, clickstream data, processing through machine learning algorithms to provide predictive and prescriptive analysis and deep, real-time consumer insights. Leveraging these insights, businesses can move faster to enable strategies that were unimaginable a few years ago, such as:

• Managing retailer inventory based on customer demographic behaviors
• Building customer models that mix sales history with psychographics in order to improve conversion rates in a recommendation engine

To leverage data pipelines and improve customer personalization, over 50% of developer teams will embed cognitive services into their apps (versus 1% today), providing U.S. enterprises over $60 billion in annual savings by 2020, reports IDC. For example, emotion recognition from images or videos is just one way that cognitive services can help to personalize experiences in a scalable, automated way.

A 360° view of customer

Understanding your customer is the first step to creating the right customer experiences. A 360° view means having a complete perspective of customers by aggregating data from the various touchpoints that a customer may use to engage a company to purchase products, gather information, or get support. This calls for integrating disparate and siloed customer data from backend applications like CRM and ERP with data from merchandising systems, activity logs, POS systems to name a few. Extracting and analyzing this data is crucial to developing deep insights like vivid buyer personas and predictive consumer behavior. This analysis adds intelligence to your sales and marketing and also forms the solid bedrock for building integrated personalized interactions and customer loyalty.

For example: a 360° view of its customers equips a retailer’s frontline employees with the exact situation and needs of the customer, enabling them to provide customers with better customer service, quick solutions, relevant offerings, and a guided path to making a purchase. When the customer connects to their website or mobile app, s/he finds the same targeted 1:1 personalized experience.