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Recognize That You Don’t Know What You Don’t Know

And it’s OK that you don’t know. Analytics can provide the answers you need.

The dynamic shift in consumer behavior in recent years has challenged companies to stay ahead of the curve by utilizing new ways to engage with their customers, as well as to predict new consumer trends. Ask those in charge of marketing, consumer affairs or advertising at a consumer packaged goods company, and many will say they look to Big Data to help extract the information they need to predict the often fickle consumer behavior.

Consumers today have many more options for providing feedback on their purchases than they had in the past, and they are more apt to use social media and online research before making a purchase. In many cases, consumers have already made their purchasing decision before they see an advertisement or product on the shelf. It is this consumer behavior that companies struggle to address, and look to Big Data for assistance.

However, Big Data—as it is—is not the panacea that many purport it to be. It has simply become too big and almost unusable, unless companies really know how to approach it and to extract the specific information they need. To do so, businesses must receive data that is timely and insightful, but most importantly it must be specific. In short, the data must tell a story; otherwise, it will remain just static data.

The role of Big Data is to ensure that the company’s consumers are happy and that the business is growing.

Expert Help

Extracting intelligent information from Big Data is not just about innovative software, and it isn’t something that can be done by just anyone (or at least done correctly). Data mining experts possess specific skills and must have a statistical and mathematical background, as well as a desire and passion for data exploration. Because of the technological, organizational and skills challenges, companies are increasingly turning towards partnerships with analytics providers that can offer these high-skilled services and help them resolve these challenges.

Experienced data scientists know that consumer patterns can be recognized through advanced analytics gleaned from social media, customer relationship management (CRM) systems, sales, shipments, media and promotion. By harnessing analytics technologies and adopting a more holistic approach to multi-channel customer interactions, they are able to mine data from a wide range of sources to provide a 360-degree view of consumers and new insights into their behavior prior to and during a purchase. These consumer behavior patterns are valuable because companies are then able to present the consumer with desired goods and services instead of waiting for the goods and services to find the consumer.

The Importance of Context

One of the most crucial aspects of better understanding Big Data is context. Without context, the information has no meaning. Take the case of a company that was launching a new snack product. The company packaged the product in individual servings, and its marketing strategy was targeting primarily health-conscious female consumers.

To gauge customer feedback, the company’s contact center staff was given a script that allowed them to categorize different types of feedback on the product—whether they liked it, whether they would buy it again, what they thought about the flavor, and so on. While consumer responses definitely fit into each of these categories, the most common was one that the company’s market research team had not anticipated. A significant number of consumers loved the product so much that they wanted to be able to share it with their families. They wanted it to be sold in family-sized packs instead of individual servings.

Unfortunately, this opinion wasn’t readily available on the drop-down lists in the questionnaire the call center employees were using. Only after the data specialists culled through the call transcripts were they able to obtain this specific feedback. This invaluable consumer feedback showed the company that there was a real desire within the marketplace for its product; it just needed to change the packaging.

This case is a perfect illustration of the old adage, “You don’t know what you don’t know,” and is the basis of why Big Data mining is a factor no company can ignore. While companies are able to glean useful information from their CRM systems or from monitoring their social-media channels, they need to go beyond those two databases to get the big picture, in full HD color. Companies’ contact centers can provide the best data from their direct consumer contacts through a number of channels and deliver it to their clients in almost real-time, whether daily, weekly or monthly—depending on what the client deems important.

Big Data Ownership

Because of the important role Big Data plays in today’s consumer engagement, marketing and overall business growth strategy, a question that’s most often asked is: Who owns Big Data? The answer is both simple and complex. Big Data, as an entity in general, has no owner and many owners, depending on what the data actually is.

Much like it has changed the way people relate to one another, social media has changed data ownership forever. Once a piece of information is out there, it is available for anyone to use. Whether a savvy consumer has taken a screen grab of a controversial Facebook post on a brand’s page or a quick-thinking reporter analyzes the tweets posted by a company, that data is free for all eyes to see.

However, while useful, data from social media is just one piece of the Big Data pie. Companies hungry for deep analysis of consumer behavior know that the depth of information is not out there for everyone to see and access, but is only available to them from content providers and for a price.

Within the companies, analysis and insights have specific business owners. Consumer affairs managers, marketing and sales executives, and branding gurus—they each have different goals and want different results, and therefore the lines of ownership blur. In today’s silo-less universe, where collaboration between internal and external forces is key, it’s best not to assign ownership for Big Data, but to place the onus onto business outcomes.

Data must tell a story; otherwise, it will remain just static data.

Its Functions and Roles

Gregg Clark, American leader for consumer products in the advisory services at Ernst & Young, recently offered the following opinion regarding Big Data, “Companies have invested in high-end customer analytics and have armies of people trying to make sense of disconnected and confusing data. They run statistic reports and push them to the sales and marketing teams, reporting on the past.”

While true, what companies do with that past information is what determines whether Big Data insights are successful or not. At the end of the day, only two factors matter: the consumer and the brand’s market share within its industry. To that end, the role of Big Data is to ensure that the company’s consumers are happy and that the business is growing. By using insights from what happened yesterday, companies can predict what might happen tomorrow and take the appropriate actions to prevent or leverage the results. Only when companies are able to unlock the potential of analytics, can they begin to understand what they can achieve.

Big Data has transformed the way companies operate, engage with and deliver expectations to their customers, and plan for future trends. As the field of Big Data continues to increase (and it will), companies and their data scientists will continue to work hand-in-hand with technology to extract the usable from the static. Similarly, as consumer behaviors continue to evolve (and they will), successful companies will continue to adapt through the help of not just big, but smart data.

Maurice Kuritz and Gary Weber


Kuritz_MauriceMaurice Kuritz is vice-president of advanced analytics at Telerx (, which provides inbound services to Fortune 1000 companies for more than 30 years, providing extraordinary customer care, building and protecting nearly 700 brands. Kuritz focuses on identifying insight from Big Data to help companies grow and delight customers.

Weber_GaryGary Weber is director of data services at Telerx. His team is comprised of data architects and data engineers, supporting information management throughout its lifecycle, including analytical platforms build out and growth. Weber is a recipient of a patent and numerous recognitions for leading the design, implementation and alignment of enterprise-wide database management, architecture and analytical framework.