The traditional linear marketing funnel is evolving into a circular buyer’s journey, and B2B marketers must employ targeting and personalization of key segments in order to accelerate that journey and better predict its paths and outcomes. These were the main points delivered in the “B2B Targeting and Personalization: Web Engagement and Predictive Modeling” session at the Adobe Summit.
Greg Ott, CMO of Demandbase, introduced the session by discussing how in this world of “Buyer 2.0,” the buyer is no longer just one person. “Marketers get so caught up in leads and numbers, but they’re really selling to a group of people,” he said. “Sales calls to one person are gone — companies now buy by committee.”
Compounding the difficulties buying by committee poses to marketers is the fact that most of the buyer’s journey, 67 percent according to Sirius Decisions data, happens before a company engages with a vendor. “The information buyers want is on your site,” said Ott. “Vendor selection and narrowing occurs long before buyers engage with salespeople.”
Ott said that the Internet has vastly expanded marketers’ ability to collect and leverage data. “Going online creates data marketers didn’t have access to in the past,” he said. “You can use it to engage customers and make marketing more effective. As you get better insight, you can align marketing activities more with revenue.”
Focused Analysis Delivers Results
To illustrate the changing world of B2B digital marketing, two marketing executives from data storage technology provider NetApp — VP of Marketing Technology Strategy Ben Chandurang and Senior Marketing Automation Manager Kim Mai, explained how their company leverages targeting and personalization.
Our digital marketing objectives are to expand our marketing universe, deliver a targeted and engaging digital experience, accelerate users through the buyer’s journey and identify leads and influencers contingent to sales,” said Mai. “We need a solid, robust targeting strategy, account and individual analysis, pattern analysis and predictive analysis.”
However, Mai cautioned that marketers must not and cannot target all of their customers. “Focus on your deepest segments,” she said. “Predictive analysis helps hone in on your deepest segments.”
In the case of NetApp, the company analyzes accounts, individuals and industries by search terms bringing them to the site, top sections and pages visited, onsite search terms and behavior on the site. Using this information, NetApp ran a test of a landing page targeted to clients from the US public sector and found by making changes as simple as using “organization” instead of “company” it caused significant lifts in demo plays, downloads and navigation to deeper product pages.
History Repeats Itself
Chandurang described how NetApp used pattern analysis to compare historical data such as the behavioral data and preferences of site visitors who came from off-domain (such as from third-party search engines) as opposed to on-domain visitors. “Surprisingly, off-domain visitors preferred longer content,” he said. “Conventional wisdom says shorter, more precise content always produces more conversions.”
However, Chandurang said NetApp realized off-domain visitors are coming to the site armed with less information and actually have a logical interest in more content. NetApp also studied patterns of site visitors based on the last category visited and by targeting content on the next page improved registration by 17 percent and interaction by 4.5 percent.
Predict the Future
In addition to using history to better understand real-time customer behavior, marketers can also use it to predict future behavior. Mai said marketers can feed data to marketing automation, CRM, business intelligence and analytics systems to help improve planning to meet future customer wants and needs. “Think big — which is product marketing, start small — which is accounts and industries, and move fast – which is testing and optimizing patterns,” she advised.