All of this focus on the Internet of Things (IoT) is really about the “Internet of Me” (IoM). From social media sites to smartphone apps and GPS systems, loads of data are being generated today about individuals – their interests, their travels, their behavioral patterns, their purchases, and so on. No one in this digital economy can afford to ignore the demands of the “me” generation. It is no longer good enough to tailor marketing based on customer demographics alone. All interactions now need to be customized to your customer’s specific situation and emotions.
With all of this digital interconnectedness, one thing that is very clear is that customer loyalty is at risk. Comparison shopping is as easy as a few mouse clicks, and previously loyal customers can quickly discover new products, new services and new vendors, and learn what other buyers like and dislike — all without leaving their laptops and other mobile devices.
Research shows that more than 50% of consumer interactions are now occurring in this multi-event, multi-channel environment. But, 65% of consumers get frustrated by companies that do not provide a consistent experience through these various media. Those firms that put a priority on the consumer experience and can provide consistency regardless of source have been shown to generate 60% in additional profits versus their less enlightened competitors.
The bottom-line is that a brand is no longer simply what we tell the consumer it is. “It’s increasingly what consumers tell each other it is.” So, how do you ensure brand competitiveness in such a volatile environment?
Well, this is where competitive organizations must recognize and strategically embrace the emerging nexus of social, mobile, cloud and information, where Big Data and advanced analytics serve as revolutionary ways of advancing the digital ecosystem. We must therefore look for big data opportunities across the nexus shifts, and in turn craft a vision that takes into account more of an all-encompassing “personalization” perspective.
It is imperative that we leverage these newer data sources and types for personalizing the digital experience for each customer by considering the environmental factors and circumstances that surround an individual use case (so contextual), or then a customer’s previous interactions to provide an evolving experience that spans across interactions (behavioral), in attempts to align a customer’s preferences with those of a pre-defined target persona through that journey! So, persona and journey- based personalizations.
Therefore, it is pertinent that customer-centric organizations be able to create a continuous, seamless virtual cycle of targeting the right customer with the right offer @ the right time by looking at avenues to enhance the existing 360- degree view of the customer. Initiatives focused on such a view have gone a long way toward providing those benefits by synthesizing customer profiles, sales and other structured data from multiple sources across the enterprise. But today, there is more opportunity for growth when you enhance that view with information from more sources, both within and beyond the enterprise. Information in email messages, unstructured documents, web logs, machine data, and social media sentiments – previously beyond reach – is now extending this view.
Organizations that make full use of these data sources can deliver better insights and a sharper competitive edge by making the customer’s experience more personalized, thereby encouraging loyalty and accelerating sales. Therefore, an enhanced 360-degree view of the customer is a holistic approach that takes into account all available and meaningful information about the customer to drive better engagement, more revenue and long- term loyalty. It combines data integration, data exploration, data governance, data access and analytics in a cohesive solution that harnesses the volume, velocity and variety of Big Data. To establish such a view of the customer, you must be able to:
• Eliminate duplicates and rationalize conflicting information through matching, linking and semantic reconciliation of master data to create and maintain a golden record
• Integrate high-quality data across multiple enterprise systems
• Manage new data types and navigate quickly through massive amounts of both structured and unstructured information from within and beyond the enterprise to find the most pertinent information
• Creating a single, up-to-date view of customers and other key entities that can be used throughout the organization, all by Leveraging Hadoop systems so that information of all types, in any volume and at any velocity, can be incorporated into the single view
• Assessing streaming data sources to analyze perishable data quickly and to select valuable data and insights to be stored for further processing
• Federate search, discovery and navigation securely across a wide range of applications, data sources and formats
New analytic opportunities are driven from this centralized, data lake architecture, where Hadoop is increasingly being leveraged as an enabler. What is critical here is to make the analytical process as specific as it can be to each customer’s digital journey by leveraging capabilities such as advanced customer segmentation, predictive and prescriptive analytics to enable cross-sell and up-sell, along with next best offer generation, thereby helping you create and evaluate the consistency of that experience across relevant products and channels.
In essence, digital transformation needs big data analytics technology, at-rest and in-motion, in order to enable a deeper level of analysis across various touch points: Mobile, Social, Web, Multi-channel. And, in order to make that happen, an effective analytical process tied to distinct digital data architectural capabilities needs to be created and implemented.