大數(shù)據(jù)與數(shù)字化營(yíng)銷

【大數(shù)據(jù)與數(shù)字化營(yíng)銷】據(jù)對(duì)美公司首席信息官（CIO）的調(diào)查發(fā)現(xiàn)：僅23%的公司在收集顧客的人口信息和消費(fèi)習(xí)慣之類的數(shù)據(jù)，并且利用這些數(shù)據(jù)進(jìn)行戰(zhàn)略決策。但其中卻僅有46%的公司擁有數(shù)據(jù)分析的資源或系統(tǒng)。他們面對(duì)的主要挑戰(zhàn)在于數(shù)據(jù)處理、信息管理和數(shù)據(jù)分析難題。數(shù)據(jù)管理平臺(tái)（DMP）發(fā)展空間巨大，將是未來(lái)數(shù)字營(yíng)銷的理想工具。

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To Handle Big Data, Advertisers Turn to DMPs

DMPs help create actionable insights

There’s a big to-do about Big Data and data management platforms (DMPs) in the digital advertising space. According to a new eMarketer report, “Data Management Platforms: Using Big Data to Power Marketing Performance,” DMPs enable marketers to use their Big Data to make smarter and more efficient marketing decisions.

Still even as brands use Big Data to build a holistic picture of their potential and real customers, many still find it challenging to extract cross-channel insight from that data.

Ziff Davis found 49% of companies polled worldwide had enacted a data management strategy as of fall 2012. And according to a survey from IT staffing service Robert Half Technology, just 23% of US chief information officers (CIOs) said they were collecting customer data such as demographic information or buying habits. Of that small percentage, less than half (46%) reported having the resources or systems to analyze the information they gathered.

A very general term, Big Data can refer to first-party customer information, third-party audience data, offline purchase data, online advertising behavioral data, campaign analytics and much more.

It can prove challenging to integrate disparate sets of data coming from social media, campaign analytics, offline sources or third parties. In fact, Big Data solution provider Infochimps surveyed IT professionals in North America and found that 83% of respondents said processing such information was a leading Big Data challenge, followed by managing the information (42%) and analyzing the data (41%).

If data is digital marketing’s currency, then the DMP is its bank. Big Data is stored and standardized here so that each data asset can be tied to a particular customer or audience segment. Once standardized, marketers can use that information to power multiple functions, both within digital and across a company’s broader marketing program.

DMPs can house both structured data, typically quantitative in nature, as well as unstructured data, often qualitative in nature—for example, social network data. Once all of these disparate sources are entered, DMPs can standardize them to build a larger, more descriptive picture of a customer or audience base that marketers can act on.

The DMP’s ability to take all of that Big Data from first-, second- and third-party sources and then organize it into meaningful audience segments makes it an ideal tool for audience targeting. This function—particularly for first- and third-party data—was also the top-reported competency of DMPs by US marketing professionals in a September 2012 surveyed by Winterberry Group.

Other than their role in organizing data on customers, DMPs are also a prime tool for campaign measurement, both within digital and across platforms.

“There’s real value in being able to address the audience first to determine what to buy,” said Mark Zagorski, CEO of data provider eXelate. “By looking at your audience and how they’re interacting with a particular ad or promotion, you can take those learnings and feed them into your current efforts and your next campaign.”

The full report, “Data Management Platforms: Using Big Data to Power Marketing Performance” also answers these key questions:

• What are Big Data and DMPs?
• How are marketers using DMPs for audience targeting?
• How are publishers using DMPs for audience targeting?
• How are marketers using DMPs for digital and cross-platform attribution?
• How are DMPs different from CRM platforms?