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As Big Data Evolves, B2B Marketers Focus On Data Management

  • Written by Brian Anderson, Associate Editor
  • Published in Data Management

big data shutterstock 121671508The growth of Big Data has not gone unnoticed by B2B marketers. In an annual study from Infogroup Targeting Solutions, 54% of marketers said they have already invested in Big Data. Up to 30% of marketers said they plan to invest in Big Data for the first time in the next two years.

Although Big Data has been a part of the lead generation and nurturing process for quite some time, many B2B marketers are still developing strategies for managing and leveraging the influx of information they are collecting on prospects.

“There is such an abundance of data now, and yet there’s no standard practice, methodologies or systems presenting and quantifying and measuring,” said David Lewis, President and CEO of DemandGen International, in an interview with Demand Gen Report. “If you’re a CFO, there are actually published financial standards on how publically held companies should be reporting their finances. But the field of marketing — primarily because there has never been any framework for measuring — lacks any form of standards for reporting.”

The lack of a standard data management practice comes from the sudden growth in the amount of data that marketers are gathering. Marketers’ first reaction was to collect as much information as possible before developing a clear strategy for managing and leveraging it, according to Jim Lenskold, President of The Lenskold Group.

“I think marketing analytics is evolving,” Lenskold said. “I would say the evolution went from marketers having very little data to marketers having all of this data, and I think the first response is to find a way to report it. That leads to marketers comparing and counting all of their data. The thought of a strategy for data analytics is where all of these new questions are coming from. Since everyone has been sitting on this Big Data for a while, now marketers are starting to ask: ‘What else can I do with it?’”

While certain data points collected from areas such as content engagement, the sales pipeline and purchase activity help marketers identify the impact of their marketing strategies on sales and revenue, collecting behavioral data on a large scale is what leads marketers to make more predictive marketing decisions.

“With very specific data points, it’s like trying to find a needle in a haystack for many marketers,” said Robert Bois, Director of Product Marketing at Lattice Engines. “It’s really hard for marketers to apply value to their data. A lot of times they’re making assumptions about either the data they have or the data they should be collecting, or they’re just taking the standard data formats in their internal systems.”

Bois stated that automated platforms that sift through behavioral data can help marketers gain an advantage with their predictive analytics capabilities.

“The human brain can only hold a certain level of information in order to make a decision,” Bois explained. “But with predictive analytics, you never make any assumptions. You just feed in as much data as possible and it will spit out the things that are important for you and your company.”

Keeping Data Clean

With all of the data that is passing through each marketer’s management system, one of the biggest struggles they face is keeping their database clean and organized. Having clean data helps marketers feel secure about their data’s credibility, increasing the accuracy of business decisions.

“In the B2B marketing space, a clean CRM and database is critical,” said Nate Young, Director of Demand Generation at Kenshoo. “So it’s ‘junk in, junk out;’ you have to make sure that as your managing your data, that you’re staying on top of your CRM hygiene to collect the data that can be used later in terms of identifying different segments you can go after.”

Having a clean database can help marketers determine which pieces of data are valuable to company executives. Using this information, marketers can effectively present their data to show the ROI of their marketing initiatives.

“The marketing organization doesn’t naturally lean towards the analytics side — it’s mostly based around the idea of being more revenue-focused,” Lenskold said.“A lot of marketers in B2B only had tracking and goals that went halfway through the funnel, so the idea of focusing on revenue is where that mind-shift has to come into play. I think it’s coming, but I don’t think it comes naturally.”

Although it may be difficult, it’s possible for organizations to tell a story with their data and give viewers a clear understanding of every aspect of marketing operations — whether it be the effectiveness of a campaign, or the specific attributes of a target audience, according to Kathy Macchi, Managing Partner at Allegro Associates.

“Even if you collect all that data, at the end of the day you need to tell a story with it,” Macchi said. “You need to know how to design and present the data so people can just look at your dashboard and obtain context about what the data represents. You can do it — it takes time — but you just have to obtain the experience that will help you connect the dots. I didn’t say it was going to be easy, but it can be done.”

Is Outsourcing The Answer?

Oftentimes it is not possible for companies to manage all the data that is required to run effective campaigns and make intelligent decisions. This is a common problem that tends to be resolved with outside help from partner companies. Outsourcing data management can be handled in various different ways, according to Bois.

“The first way would be when marketers just go to a data appending company and outsource the collection component of the process,” Bois said. “The second would be to outsource the lead collection process as a whole, which is now being recognized as a somewhat bad practice. The third is to not outsource the data you need to run your sales and marketing operations.”

Marketers “might have assumptions” about what can be considered predictive about their customers, but outsourcing the analyzing buying signals data can give marketers better predictions about their customers, Bois reported.

“There is no sense for marketers to duplicate their efforts,” Bois added. “The data that marketers need to run their operations has to stay in their source systems. But the data and buying signals that enhance predictive capabilities for the in-house data can be outsourced to save a company time and resources.”

It is a delicate balance to decide how much of your data manage to outsource. But to outsource all of your data “is a really big mistake,” according to Erich Ziegler, VP of Marketing at RingCentral.

Ziegler explained: “My biggest question for up-and-coming companies offering to manage my data is: ‘How much time am I going to have to put into transferring and cleaning the data so you can use it?’ They will probably come back to me with the same results I could have gotten from keeping the work in-house with people who hold themselves personally accountable and use methods that they believe work the best for them.”