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Bringing Big Data Into Marketing Operations

Smart Marketing Using Big Data: What Marketers and Agencies Need to Know

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Marketers often get accused of creating hype. But when it comes to big data, they're facing the same challenge as everyone else in separating fact from fiction. Like "the cloud" before it, "big data" is the latest IT buzzword being twisted and reshaped to fit all sorts of agendas. In Gartner's Emerging Technologies Hype Cycle 2012, big data is nearing the peak of inflated expectations. Underlying the squishy definitions, though, is the growing role that data plays in helping marketers identify, understand and communicate with target audiences.

How to share data with agencies and vendors
How to share data with agencies and vendors

Advertising Age Research's latest report, "Smart Marketing Using Big Data," explains how to bring big data into marketing operations, how to find and attract the talent you need to implement big-data strategies, how to build an infrastructure that uses big-data techniques, whether to outsource or keep operations in-house and tips for safely sharing data with agencies and vendors. (Order it here.)

Thanks to advancements in the ability to collect, store, manage, analyze and access vast quantities of data, "We're able to now do what the industry was talking about 10 years ago," manipulating and leveraging large amounts of disparate data in a cost-effective way, says Andy Fisher, chief analytics officer for Merkle, a customer-relationship-marketing agency. "The dream is becoming possible."

Arguably, marketers have applied analytics to some pretty large-data stores for a long time. But recently, new capabilities are taking data analytics to the next level:

■ Distributed processing, cloud and other data-management improvements mean marketers can work with the entirety of the database vs. representative sampling in a rapid and cost-efficient way. That fuels capabilities such as more effective customer segmentation as well as one-to-one and real-time marketing.

■ Much of the value of combining multiple data sets comes in finding points of overlap, particularly for exercises such as audience measurement. With more and more varied data, there is more likely to be overlap and therefore more complete views -- not just who touched a brand, for example, but where and why the consumer chose that interaction. "That's a big innovation that's important to marketers and publishers to monetize," says Andrew Lipsman, VP-industry analysis, ComScore, a digital-marketing-services company.

■ Marketers can micro target audiences with messages that are relevant to them in the channels where they want to receive them, reducing the scattershot approach necessary when there was less audience insight and segmentation.

■ Data-analytics-software developers are crafting front ends that serve up results in a clearer, more actionable way, making results more accessible to a wider, nontechnical audience. That spreads its impact more widely.

In the past, says Merkle's Fisher, people tended to aggregate big data into small-data sets to solve big problems, such as channel allocation. "The success of big data is solving little problems on a massive scale," he explains, such as Amazon recommendation engines or delivering the right ad to the right consumer.

Why big data matters

All this comes at a time when consumer expectations, fueled by mobile apps and the customer-first attitude born of the recession, are higher than ever. Marketers are under pressure to support customer-satisfaction initiatives at the same time they're being asked to prove the return on investment for marketing spending.

Many see the answer in gaining a more complete view of the customer by segment and even individually, enabling them to understand, predict and even shape their buying behavior.

They see big data, together with sophisticated mining and analytics tools, as the key to unlocking those capabilities. Big data in marketing is finding a wide range of applications, from correlating ads and sales, to audience measurement, to predicting customer behavior. Leveraging big data in new ways is enhancing the ability to make advertising and marketing more effective, not just cost-wise, but in the ability to shape and target messaging in a highly customizable way.

Marketers have applied analytics to some pretty large data stores for a long time. But recently, new capabilities are taking data analytics to the next level. Distributed processing, cloud and other data-management improvements mean marketers can work with the entirety of the database vs. representative sampling in a rapid and cost-efficient way. That fuels capabilities such as more effective customer segmentation as well as one-to-one and real-time marketing. Much of the value of combining multiple data sets comes in finding points of overlap, particularly for exercises such as audience measurement. With more and more varied data, there is more likely to be overlap and therefore more complete views -- not just who touched a brand, for example, but where and why the consumer chose that interaction.

Marketers can micro target audiences with messages that are relevant to them in the channels where they want to receive them, reducing the scattershot approach necessary when there was less audience insight and segmentation. Data-analytics-software developers are crafting front ends that serve up results in a clearer, more actionable way, making results more accessible to a wider, nontechnical audience. That spreads its impact more widely. All this comes at a time when consumer expectations, fueled by mobile apps and the customer-first attitude born of the recession, are higher than ever. Marketers are under pressure to support customer-satisfaction initiatives at the same time they're being asked to prove the return on investment for marketing spending.

Many see the answer in gaining a more complete view of the customer by segment and even individually, enabling them to understand, predict and even shape their buying behavior. They see big data, together with sophisticated mining and analytics tools, as the key to unlocking those capabilities. Big data in marketing is finding a wide range of applications, from correlating ads and sales, to audience measurement, to predicting customer behavior. Leveraging big data in new ways is enhancing the ability to make advertising and marketing more effective, not just cost-wise, but in the ability to shape and target messaging in a highly customizable way.

"The role of the marketing department is changing dramatically because of analytics," says Richard Rodts, manager, IBM Analytics Academic Programs. "They're not just looking at the consumer; it's how the consumer feels about the brand, and how individuals feel about the brand, and how we recognize and interact with individuals specifically as a marketing department.

In this report, you will learn:

  • How to bring big data into your marketing operations
  • Strategies for building a big-data infrastructure
  • The technology you should have
  • The talent you should hire, and how to attract the candidates you want
  • How to share data with agencies and vendors
  • How to decide whether to outsource, or keep operations in-house
  • 10 tips from leaders that have already embraced big data practices

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