Big Data

Big Data is Only One Component of Brand Experience

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Today’s consumers not only expect to interact with brands, they expect brands to interact with them. 

That interaction, of course, is enabled by Big Data, which most people think of as the mountain of information being collected on us with every key stroke or swipe. However, Big Data alone doesn’t create brand experience or build consumer loyalty; it’s the confluence of that data with technologies, product and service capabilities and human perspectives that does.

Customers are often unaware of, or don’t care about, the underlying data that sits behind a product or service. Rather, it’s the experience powered by that data that engages them. They are delighted by their ability to interact with brands across multiple channels and devices, and the ability of brands to know when to engage with them, and what their individual preferences may be.

Successfully delivering brand experience and rewards starts with embracing the concept of “confluence.” Big Data itself is nothing without context, and understanding that context is essential to meeting an increasingly higher standard demanded by consumers. Businesses across all industries are now learning to go beyond data collection, to learn how to use information effectively to deliver insights and create more engaging and immersive customer experiences.

Part of understanding this confluence is knowing how people interact with brands across myriad channels, screens and devices. But it’s more than just technology. It’s knowing how technology is delivering on the kind of personalized, value-oriented connections that customers expect. 

Today, people expect brands to know about them – to know where they are and when to engage with them, to demonstrate a knowledge of their lifestyles and personal preferences that’s at once intuitive but also unobtrusive. Financial services, healthcare providers, retailers and automakers are just a few industries learning to use data to reveal insights that create high-quality, immersive experiences for consumers.

Wearable health and fitness devices offer a glimpse into the potential and power of Big Data – not just in the sheer volume of information that can be collected in aggregate, but just how far that data can go in delivering benefit to multiple parties.

Nearly 100 million people will be using wearables by 2018, but the benefit goes well beyond their ability to simply track their heart rates and how far they walk. Hospitals, health care providers and insurers who tap into that collective information will be able to gain insights into how to promote wellness, and how to incentivize people to take better care of themselves. That data is even now being applied by law enforcement, as evidenced by a recent Connecticut case that hinges on the number of steps recorded by a victim’s Fitbit device. That use case may seem an unintended consequence of the monitoring capacity of wearable devices, and it may even seem jarring from a marketing standpoint, but it too represents a confluence of ideas.

In the entertainment world, and in sports, fans want a deeper and more interactive experience beyond the passive experience of listening or watching. Big Data delivers instant access to the outcome of the latest tennis match, but in the broader context, it also can deliver additional insights into player performance, key strengths and shot selection.

The auto industry is using Big Data insights to reinvent the travel experience with connected cars, which can, for example, automatically tap into weather and traffic data and recommend the best route. Those same connected cars can feed aggregate data back to automakers to give them insights into driving preferences and habits, and even to automobile insurance companies which can deliver safe driving benefits based on real-time information. And that’s just the beginning. The confluence of data, technology and human perspective is already leading the way toward the development of autonomous, self-driving vehicles.

Emerging open source technology offers a compelling alternative. Open source is becoming the standard for Big Data solutions because it knows no limitations on data volume or type, and offers unrivaled ability to perform complex, real-time analytics at a fraction of the cost of traditional solutions. Enterprises need to harness the flexibility of emerging open source technologies to boost the capacity of existing solutions and leverage them to enable real-time connectivity that is at the heart of true customer experience.

Traditional Business Intelligence (BI) solutions are no longer up to the challenge of meeting the expectations of companies and their clientele. These solutions focus only on a single dimension, not the confluence of possibilities that are revealed in leveraging the full potential of Big Data. Big Data is not just a technological solution, and those companies which approach it as merely a software problem will not realize its full potential unless it is seen as a multi-dimensional, transformational initiative that goes beyond the technology to include capabilities and a human perspective.

 

Jeff Augustin is a partner with ISG (Information Services Group). He offers more than 33 years of experience in the sourcing industry, including five years as the CIO for professional service firms, 23 years providing IT outsourcing services and 5 years as a senior advisor to global fortune 500 companies. His main areas of expertise include building and launching commercial markets and high visibility alliances for innovative products and technologies. Contact Jeff at Jeff.Augustin@isg-one.com.

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