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Today’s business-to-business (B2B) sales customers have increasingly sophisticated, evolving expectations.

Instead of simply being treated as a faceless entity within a company, they want and respond best to targeted, personalized, tailored campaigns that are reflective of past interactions.

“Customers expect that the full context of who they are, and how they engaged previously, comes across,” said Brian Glover, senior director of product marketing and B2B strategy at Adobe. “The challenge for brands is connecting with customers on their terms and creating personalized experiences at scale.”

B2B marketing and sales departments are increasingly adopting AI and machine learning (ML) capabilities to identify buying patterns and link response to, and engagement with, specific campaigns and marketing channels. This hyper-personalization helps target customers and predict their future purchasing patterns.

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According to AIMultiple, 71% of B2B marketers are interested in using AI for personalization, 63% are interested in using AI to identify trends and 59% expect AI to help identify prospective customers.

AI driven by Adobe Sensei

Adobe is looking to bolster its presence in this area with several new and expanded products announced this week at its Adobe Summit – The Digital Experience Conference. These capabilities aimed at driving personalization are powered by the company’s AI engine Adobe Sensei and embedded throughout its software-as-a-service (SaaS) platform Adobe Experience Cloud.

“It comes down to, how do you get a better idea of who is going to become a customer?” Glover said.

He quoted one-time U.S. Postmaster General, businessman and so-called father of marketing John Wanamaker: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”

“The challenge today might as well be, ‘I know I should be doubling down my resources on accounts, but I don’t know which half,’” Glover said.

Adobe’s expanded predictive lead and account scoring helps brands determine account context by identifying the people within their account and their behaviors, he explained. This helps create an understanding of whether they are likely to become a sales opportunity and a paid customer, thus leading to better ROI.

For example, models can look at leads and accounts that have become customers and the digital behaviors that have preceded them – such as opening emails or filling out website forms – and cross-reference them against other accounts. Those with similar patterns of digital behavior are given high scores. Based on those matches, marketers can then shift their tactics from broad-based campaigns to more targeted direct digital advertising, one-on-one reach-outs and small field events.

This tool can be used within the Adobe Real-Time Customer Data Platform (CDP) and will also be available with the company’s B2B marketing automation app Adobe Marketo Engage later this year, Glover said.

Similarly, the new offering Adobe Marketo Measure provides visibility into marketing spend and campaign performance. Through Adobe’s Real-Time CDP, marketers can then identify account leads and shift dollars to the most appropriate online and offline channels.

“You might discover you’re getting a higher ROI through some digital channels and interactions versus a live event or conference sponsorship,” Glover explained. “It helps solve for the John Wanamaker adage. I get more valuable insights that help me make decisions in an even finer grain way.”

Engaging with your customers — with help from AI

Adobe also announced the release of Adobe Dynamic Chat, which allows marketers and prospective customers to engage and accelerate the buying process, as well as AI-driven product recommendations and live search results for both B2B and B2C brands through its ecommerce software Adobe Commerce.

With multiple people in buying teams and numerous touchpoints across digital and physical interactions, it has historically been challenging for marketers to determine who is most likely to respond to a given campaign and whether that will translate to a purchase, Glover noted.

“Which people should I focus on, which are the leads in each account?” he said. “It’s helping marketers have more consistent, personalized experience across emerging channels.”

Real-time customer behavior data based on their interactions and those of similar customers help establish “people level profiles with context,” Glover said. Creating a complete picture of how campaigns perform across the entire customer journey translates to broader engagement because marketers can pinpoint who is responding to what and how they can best follow up based on history and preference. Emails, mobile and web interactions, events and interactive chats can be synchronized and capitalized on to make marketing more effective and create new opportunities and pipelines.

All told, Glover pointed out, the nature of the relationship between marketing and sales is evolving into one that is more in-depth and symbiotic — compared with the past when one simply handed off leads to the other.

“They are engaging key accounts at the same time,” he said. “The challenge becomes how do they stay coordinated; how does the left arm know what the right arm is doing? We are moving from a rules-based era of marketing to an AI-powered era of marketing.”

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