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And…Action! Three Big Data Use Cases Starring Remarkable Results

By on September 26, 2014

**This article originally appeared on CIO Story**

Big data has been synonymous with big opportunities for the past several years. As we embark on the era of data, organizations are beginning to discover how deriving insights from data can transform the status quo, disrupt markets and change lives.

According to research firm McKinsey, effectively using big data could save healthcare organizations more than $300 billion, reduce government inefficiencies by $149 billion and increase retail businesses’ operating margins by more than 60 percent. Given the promise of big data, it’s no surprise that more and more leaders are making it a top priority and seeking ways to use data insights to make smarter decisions.

But to avoid becoming delusional about big data, organizations must turn these opportunities into outcomes. Data-driven businesses are using analytics to democratize the decision-making process and increase the agility and speed in which smarter decisions can be made for big business impact.

So what use cases are delivering real results in a repeatable way? Check out these three big data use cases and how they’re turning big data opportunities into big outcomes.

Operational analytics

By implementing an operational analytics strategy, businesses can maximize productivity and profitability across every department. A leading telecommunications service provider wanted to do value-based network capacity planning— that is, have enough capacity to meet existing and forecasted cell tower demand while avoiding unnecessary costs with excess network capacity.

To operate at the ideal rate, businesses need accurate forecasting so that capacity can meet demand and customer satisfaction can be maintained without overspending on capital expenditures. For the telecommunications industry, this means capturing and analyzing data for not only voice traffic, but also mobile broadband traffic. By implementing operational analytics using big data, they integrated customer demographics, device and application behavior data and analyzed how it correlated with specific network capabilities and performance. In eight weeks this telecommunications company analyzed disparate data sets quickly and efficiently to provide business leaders the right insight to make data-driven decisions about network capacity planning and strategically decide where to invest or curtail infrastructure. The result? More than $100 million per year in savings!

Customer analytics

Today’s customer journey is more fluid than ever, challenging business to understand the complete sequence of events and where they have the opportunity to best connect with customers.

So in a world where customers interact with brands across multiple mediums and devices, a vast amount of structured and unstructured data is being created from social media, website click streams, mobile, CRM, transaction, call center calls and point of sale. Big data provides brands with a deep understanding of the customer journey by analyzing all this data together for new insights that until now was not possible.

Traditionally these data were being analyzed in isolated systems and from customer demographics and transactions. However, customers now interact more than they transact and interactions on social media and other channels can provide a wealth of information and clarity into who customers are and their preferences.

Understanding the value in integrating all of this data, a major financial services company analyzed the correlation between customer purchase history, profile information and social media behavior. To better understand how their high-value customers behaved, they performed a customer segmentation that combined social media data and transaction data and found that high-value customers frequently watched the Food Channel and shopped at Whole Foods Market. Armed with this behavior information, the company was able to strategically target advertising campaigns to these customers by offering special promotions for health food stores. With this data-driven approach, they reduced customer acquisition costs by 30 percent while improving cross-selling and up-selling opportunities.

With the right data solutions, companies are able to leverage these digital breadcrumbs to increase loyalty, reduce churn and ultimately better serve customers and prospects.

Data-driven products & services

Savvy companies are turning to big data to develop data-driven products and services that help create new revenue streams, build a competitive advantage and boost customer loyalty. With access to insights derived from big data, companies are able to offer innovative analysis offerings to other companies that closely align with their needs and desires, such as selling analytics reporting to make ad campaigns more impactful.

A leading energy management company leveraged big data analytics to collect and analyze over 7 million data points each day from smart meters, thermostats and other devices and provide analytic reports to utility companies. These reports are included in household bills to encourage consumer to conserve energy by comparing their household energy usage to their neighbors.

By providing customized energy consumption reports to each household this company has helped clients reduce energy consumption by $500 million per year and reduce CO2 emission by 7 billion pounds.

From operational analytics to customer analytics and data-driven new products, organizations are learning the most effective ways to turn the growing heap of big data into a business gold mine. With the use of big data analytics they are able to not only understand the past but also foresee the future so they can use big data as a strategic tool for timely data-driven decisions that make a significant financial impact.

 

 


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Stefan Groschupf

Stefan Groschupf

Stefan Groschupf is a big data veteran and serial entrepreneur with strong roots in the open source community. He was one of the very few early contributors to Nutch, the open source project that spun out Hadoop, which 10 years later, is considered a 20 billion dollar business. Open source technologies designed and coded by Stefan can be found running in all 20 of the Fortune 20 companies in the world, and innovative open source technologies like Kafka, Storm, Katta and Spark, all rely on technology Stefan designed more than a half decade ago. In 2003, Groschupf was named one of the most innovative Germans under 30 by Stern Magazine. In 2013, Fast Company named Datameer, one of the most innovative companies in the world. Stefan is currently CEO and Chairman of Datameer, the company he co-founded in 2009 after several years of architecting and implementing distributed big data analytic systems for companies like Apple, EMI Music, Hoffmann La Roche, AT&T, the European Union, and others. After two years in the market, Datameer was commercially deployed in more than 30 percent of the Fortune 20. Stefan is a frequent conference speaker, contributor to industry publications and books, holds patents and is advising a set of startups on product, scale and operations. If not working, Stefan is backpacking, sea kayaking, kite boarding or mountain biking. He lives in San Francisco, California.

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