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B2B Marketers Look To Expand Predictive Capabilities Throughout The Customer Lifecycle

  • Written by Brian Anderson, Associate Editor
  • Published in Industry Insights

PredictiveMarketingFeature imageWhile it has been a successful tool for top-of-funnel demand generation, predictive marketing is becoming more widely used by B2B marketers to improve engagement at all stages of the buying cycle. Companies such as Salesforce have launched new predictive marketing capabilities within their offerings, aiming to enhance the customer experience throughout the entire customer journey by embedding predictive capabilities within the marketing cloud.

Industry experts noted that the expansion of predictive beyond lead scoring and early-stage demand generation is a growing trend.

"Leaders, especially in marketing, need to be able to extract insights and make predictions based on existing and external data," said Meagan Eisenberg, CMO of MongoDB and former VP of Customer Acquisition and Marketing at DocuSign, in Demand Gen Report's 2015 Marketing Automation Outlook Guide. "Marketers also need to create efficiencies in the follow up of leads using predictive analytics and modeling to create a better scoring methodology to focus on opportunities most likely to turn into customers."

The expansion of predictive marketing beyond the top of the funnel has the potential to increase ROI of marketing campaigns, observers noted. "B2B marketers need to look at the entire funnel, instead of just focusing on a piece," said Nipul Chokshi, Head of Product Marketing for Lattice Engines, in an interview with Demand Gen Report. "They need to believe that this data brings value the entire lifecycle."

A recent study from the Salesforce Marketing Cloud shows that predictive intelligence is attributed to approximately 40% of overall revenue after 36 months of implementation.

B2B organizations have several options for incorporating predictive marketing capabilities throughout the customer lifecycle — including lead nurturing, building buyer personas and campaign attribution.

"Predictive analytics can be applied to anything," said Kerry Cunningham, Research Director at SiriusDecisions. "It can help size your market, develop content, or even figure out what the best solution is to offer a prospective buyer."

B2B marketers are seeing success when applying predictive marketing to more accurately forecast campaign results, observers noted. "For many marketers, using predictive analytics usually comes to a conclusion in a score," said John Hurley, Director of Product Marketing for Radius. "What marketers really need are the signals or characteristics that they can apply to that vehicle that drives campaigns."

Predictive Analytics Support More Targeted Personas, Nurture Campaigns

The B2B buyer persona is an area where predictive capabilities can have a positive impact on accuracy and success. Analyzing prospects with scores similar to current clients helps marketers gain deeper insights into their most valuable prospects.

"It's a powerful way to see more deeply into what creates a persona," said Cunningham from SiriusDecisions. "It helps provide more data and information to make business decisions, then validate those decisions once the decision is made."

It's important to build a foundation before you dive deeply into predicting, according to Jane Rygaard, Head of CEM, Core and OSS Marketing for Nokia. "Businesses looking to expand their predictive marketing have to look outside the box to understand what variables are crucial to making accurate business decisions."

Rygaard pointed to a mobile operator that is using Nokia's new predictive marketing capabilities to create more targeted messaging for lead nurturing. The mobile operator analyzes successful customers within its client base, and targets leads based on how well they match with existing customers. The mobile operator's campaigns receive an average 25% click-through rate, in comparison to the 4% click-through rate they were seeing prior to leveraging predictive capabilities.

"The combination of what you can do with predictive, combined with the database you have, is expanding," Rygaard added. "This selection is used as a foundation to identify prospects who would be most likely to take my offer. Campaigns can then be created to meet these prospects' needs."

Lead nurturing is one of the common areas where predictive capabilities can enhance business results, according to sources. This is attributed to the role of content in the nurture process, and how personalized messaging — often gained from predictive insights — can be leveraged during content ideation and creation to nurture prospective buyers further along the funnel.

"Nurture streams are dependent on how buyers interact with content," Cunningham noted. "It's being able to harvest those signals, and use them to drive relevant content. That can be powerful in understanding how buyers are behaving outside the digital walls."

In a crowded digital landscape, marketers need to deliver what customers want before they even ask for it, according to Gordon Evans, VP of Product Marketing at Salesforce.

"That’s what predictive intelligence is for," Evans added. "It's a technology that allows marketers to target consumers based on their online behaviors, sending responsive and increasingly relevant messages over time."

Predictive marketing can help marketers anticipate the content and other resources buyers might need during the decision-making process. This insight can come from much more than the interactions prospects have with the brand, according to Cunningham. "Predictive analytics allows marketers to use data from outside our digital walls. It allows you to see more of what the prospect is up to, even if it's an existing customer."

However, connecting interactions throughout the customer journey has been a struggle for B2B marketers. A recent study conducted by Forrester shows that 42% of B2B marketers have difficulty analyzing data from all customer interactions.

"We've noticed that the whole crux of it forB2B marketers is that it hinges of the company targeting and company data housed in your system," added Derek Slayton, VP of Marketing for Dun & Bradstreet Netprospex. "The better you are at making sure you have accurate data, the better it's all going to work."

Slayton added that learned data, or the data obtained from current customers, plays an important role in helping connect the dots between customer interactions. "It requires a lot of thought and research in order to understand the parameters that signify potential opportunities."

"There is no silver bullet," Slayton concluded. "You have to create interest, educate your buyer and then drive that value towards them."

Predictive Puts Focus On Customer’s Lifetime Value

At the highest level, predictive intelligence can help B2B marketers understand the impact each touch on the customer journey has on the buyer. These predictive algorithms, and the insights provided by them, can then help explain how a particular channel is affecting downstream conversion.

"Each touch a buyer has with a brand ultimately increases or decreases the opportunity to close the deal," said John Bates, Sr. Product Manager for Data Science & Predictive Marketing Solutions at Adobe, in an interview with Demand Gen Report. "Attribution helps identify the forks in the road that buyers come across, which can then be used to help the buyer to make the right turn to move them further along funnel."

The insights from measuring these channels and campaigns can help answer questions that were once unanswerable with traditional metrics collected during campaigns. Understanding these metrics help connect the dots, ultimately helping B2B marketers tie revenue to particular campaigns or channels. Bates added. "Technology and machine learning can provides possibilities for responses, which marketers can then execute and test to understand what maximizes results."

Since many of the options throughout the customer lifecycle where predictive marketing can have a positive impact requires the analysis of current clients, it is clear that predictive intelligence can help B2B sales reps when looking for new opportunities within their current client base.

"Retention is growing into the new acquisition," said Dominique Levin, CMO of AgilOne, in an interview with Demand Gen Report. "Predictive intelligence can help B2B organizations focus on customer lifetime value, not sales and number of clients. This is done by alleviating the pain points of current clients in order to build customer loyalty."

Levin highlighted how several current AgilOne clients who were using predictive algorithms to detect potential churn within current customers. "Predictive can provide early warning signals for customer migration, if a customer buys this much one year, then buys less the following year, you can turn a situation around and win a customer for life by responding at a timely manner."

Other examples include using predictive intelligence to identify cross-sell opportunities, such as if a company is expanding into a new country or if a current customer has found a new job at a different company.

Levin said predictive not only helps to identify high-value clients, it can improve retention. "It would be a bigger hit to lose the client than to increase the budget to market to them. Once the purchase is made, companies can then predict how many recurring purchases will be made over time — increasing the customer's lifetime value."