4 practical ways AI can transform B2B marketing via Marketo Engage

By Chuck Leddy

Artificial intelligence (AI) has already proven its value-creating capacities across many industries, with 80% of companies now deploying AI in some capacity. But while most B2B marketers know, at least theoretically, that AI can be used to dramatically improve their marketing efforts, less than 1 in 5 marketing teams have actually deployed AI in any form. 

In this blog post, we’ll outline 4 practical ways AI can transform marketing, then describe the current obstacles to leveraging AI for marketing and how they can be overcome. This post is based on a Marketo Engage webinar called Art Meets Science: How Marketers Can Transform Their Results with Predictive Capacities (free on-demand). During this webinar, Alexandra Quick (Product Marketing Manager at Adobe) and Badsah Mukherji (Senior Manager, Marketo Engage Product Management at Adobe) shared their insights about AI and the many ways your B2B marketing team can put it to work (specifically within Marketo Engage).

How does AI add value to marketing?

AI is a proven technology for driving marketing ROI, explained Quick. Surveys show that “top performing companies are more than twice as likely to be using AI in their marketing” as low performing companies, she said, and marketers who deploy AI also report “significant positive impacts” on their marketing performance and marketing ROI. Among the many benefits AI offers is “the ability to target and personalize engagement with customers,” according to Quick, who detailed a number of additional benefits:

  • AI rapidly performs data analyses;
  • AI learns (and improves) based on past performance;
  • AI can make improvements in real time;
  • AI can help marketers create more successful strategies;
  • AI drives better results.

AI transforms marketing in 4 major ways

Quick and Mukherji described 4 specific ways that AI can be used to improve campaign performance and marketing ROI:

#1. AI drives personalized customer engagement. Personalization of content is a prime driver of marketing ROI, with 86% of customers saying that personalization positively impacts their purchasing decisions, according to Quick. She also detailed how difficult content personalization can be without the use of AI. The challenges she outlined include:

  • large amounts of content must be located and tagged;
  • customer data must be collected and integrated from multiple channels;
  • customer interactions with content must be mapped to leads and (with ABM) to accounts;
  • putting all this data together in a way that’s actionable in real-time is hard.

AI completely changes how personalization happens, explained Mukherji: “AI automatically discovers and tags content, it selects and approves assets for content recommendations, and it measures content performance.” Each challenge to personalization gets resolved by AI, enabling personalization throughout the customer journey.

#2. AI helps with audience selection/segmentation. Sending email blasts to entire lists puts marketers at risk in multiple ways, including low open rates (due to limited content relevance for some recipients) and high volumes of unsubscribes and opt-outs. Simply continuing to recycle your same, old email lists is no way to improve key performance metrics, but instead drives audience disengagement.

AI can help by smartly pulling together the “right” contacts into your email lists from multiple databases, based upon the historical behavior of list members. As Mukherji explains: “Predictive Audiences [an AI-fueled feature in Marketo Engage] allows marketers to create lists based on historical data” around customer behavior and preferences, thus driving improvements in key campaign metrics. Better use of data through AI thus enables marketers to target the customers who are most likely to want your content

#3. AI drives marketing attribution. Every marketer, especially every B2B marketer, knows that the buying journey of today’s customer is complex, time-consuming and happening through multiple channels, most of them digital. In fact, the average buyer’s journey encompasses 7-8 different touch points across numerous channels, notes Quick. How can AI help you connect these customer interactions with revenues/ROI?

“AI allows you to build attribution models that become more accurate over time,” said Mukherji, noting that Marketo Engage works with Bizible on marketing attribution. Using AI, you can accurately weigh the impact of each interaction and each step of the customer journey, connecting your marketing spend with marketing ROI. You can show what marketing activities are driving revenues, and do more of them.

#4. AI helps you evaluate which customers and accounts (with an ABM approach) are ready to buy. Something called “purchase intent” is made up of multiple signals that AI can read and analyze, thus predicting conversions. For ABM, analyzing purchase intent is even more challenging because the purchase intent is collective and deeply-complex.

Marketo Engage’s “Account Profiling” feature “uses AI to rate the purchasing intent of accounts,” said Mukherji, “and it looks at all stages of the sales funnel” to do so. Best of all, AI gets smarter and more accurate over time about purchase intent: it “considers multiple models of purchase intent and observes which are the most accurate over time,” says Mukherji, which helps marketers engage with both individual customers and accounts.

Current obstacles to AI adoption for B2B marketing

AI is clearly a great tool for marketing, as we’ve seen above, but why are only 18% of marketing teams using this proven and powerful tool? Mukherji notes that finding the right AI tools to meet your marketing needs can be a challenge, as can learning how to properly use and integrate AI tools into what you’re doing now. But one obstacle to AI adoption stands out above the rest.

Many marketing teams don’t use AI because they lack the data management practices and processes to support it. To state the obvious, AI is fueled by data, so if your “data house” (i.e., your data management) is a mess, you don’t have the proper foundation upon which to build your AI capabilities. As Mukherji sums it up, “you need the integration of all your marketing data in order to create a data ecosystem where AI can benefit you.” Doing that “foundational” work with your data management is thus a necessary prerequisite to deploying AI.

Interested in learning more about using AI in your marketing? What about improving your data management maturity so you can begin gaining the massive benefits of AI? If so, reach out to us here.

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