5 ways to leverage AI in B2B marketing automation for transformative results

Artificial intelligence is the new frontier in marketing automation for B2B marketing to create hyper personalized experiences, a more nuanced understanding of buyers and to make faster, data-driven decisions. Make sure your enterprise business isn’t left behind…  

If you’ve ever used a website chatbot, asked Siri to tell you a joke or used Gmail’s suggestions of what to say next, you’re familiar with artificial intelligence. AI is already deeply embedded in our daily lives and is only set to revolutionize them further as Microsoft’s Chat GPT and Google’s Bard race to outdo each other. 

With its complex processes and large volumes of data, B2B marketing is now looking towards AI (artificial intelligence) as its natural partner. Marketers are learning to exploit the new capabilities of machine learning algorithms and advanced data processing capabilities to optimize marketing efforts, understand their buyers better and make more accurate decisions on how best to communicate with them.  

AI can analyze vast amounts of data, identifying patterns in buyer behavior, draw on overlooked data sources and enhance buyer segmentation, and it can do this faster than a human ever could. By integrating AI tools into their marketing automation platforms, B2B marketers are better able to respond to their buyers’ ever-increasing demand for greater personalization, lightning-fast response times and superior customer experience.  

If your enterprise business is considering investing in AI, you’re in good company. Forrester’s Q2 2022 Global State of AI In B2B Marketing Survey found that more than 70% of respondents plan to ‘moderately’ or ‘significantly’ increase their plans for using AI in marketing processes. As for how organizations already using AI in their marketing efforts and business objectives are feeling – 60% of survey respondents described AI adoption as positive and 28% felt neutral. None of those using AI described its impact as negative.  

 “AI will increasingly determine which firms win and which firms lose.” 
Phil Clement, former CMO of Aon to B2B Marketing 

What’s the difference between artificial intelligence and automation?

Crucially AI and automation are not interchangeable technologies. Whereas automation replaces previously manually performed tasks by following a strict set of rules, AI has broad parameters and processes vast amounts of information to decide which path is best to take to arrive at a solution. Whereas automation simply performs the same task over and over, AI uses machine learning to improve its performance over time and predict and recommend what to do next. In short, for a marketer working within marketing automation, AI is the best personal assistant you’ll ever have.  

How can AI deliver more value from marketing automation?

Marketing Automation Platforms are immensely powerful tools, but resource-heavy and with many moving parts. Just a few of the skills required include data selection and segmentation, content planning and creation, email build and testing, campaign build and testing, reporting and optimization, with each of these skills typically belonging to a different resource and taking a certain amount of time to execute. While it can’t and shouldn’t replace these resources, it has the potential to add an additional layer of intelligence, speed up processes and reduce both errors and the overall time invested.

Use cases for AI in B2B marketing automation 

Here are five ways that AI tools can be integrated into marketing automation for more accurate and more effective marketing covering all the complex B2B buyer touchpoints, and possibly lightening the load on resources:  

          1.      AI function: Data analysis
                  Marketing win: Hyper-personalized marketing campaigns 

B2B buyers want the same level of personalization as their B2C customer experiences – a study by Accenture found that 73% of buyers desire personalized experiences, but only 22% say their most recent online experience was completely personalized to them. AI in marketing automation can plug this gap by its ability to process buyer data and make recommendations for content and offers based on their previous purchases and personas, resulting in higher engagement rates and improved customer loyalty.  

“It is important for B2B companies to look at their data as if it is one of their products; invest in its upkeep and integrity while finding ways to continuously improve it. Using advanced analytics powered by AI and ML to identify patterns from large amounts of data, B2B companies can activate insights into customer decision journeys to maintain loyalty, personalize experiences to improve satisfaction and boost revenue, while also finding ways to optimize costs. For example, with analytics, enterprises can streamline spend to focus on the highest-performing channels and reduce waste.” 
Giusy Buonfantino, Google Cloud VP, Consumer Packaged Goods Industry Solutions  

 2.      AI function: Lead nurturing and lead generation
          Marketing win: Generating high-quality leads at scale

A study by Ruler Analytics showed that generating quality leads and a high volume of leads are among the top 5 challenges for B2B marketers. Collecting, managing and analyzing data takes time and resources. AI can be integrated into lead generation processes and can capture hyper-accurate data in real time. Data is more accurate, dynamic and visible throughout the sales funnel.  

 3.     AI function: Intelligent lead scoring
         Marketing win: Prioritization of the most valuable prospects

AI algorithms assess lead quality based on their likelihood of becoming customers. They quickly rank them according to personas, engagement levels, and interactions and assign lead scores. Rather than using a traditional rules-based approach, AI is quicker and more accurate and can provide further information on which fields are most influential for lead scoring.  

“It’s a lot easier to leverage these tools than you think. It’s taking your data and developing ways to automatically analyze that data faster and turning that into human decisions.”  
Tom Kershaw, Chief Product and Technology Officer, Travelport  

4.      AI function: Predictive analytics
         Marketing win: Gain a nuanced and deeper understanding of the buyer(s)  

Understanding your buyer through data can be time consuming and laborious. AI can quickly look at historical data, collating it from multiple data sources to predict future buyer behavior. Buyer intent, churn rate and lifetime value, for example, can be generated fast. AI can also unite on and offline data, for example, collecting data from triggered emails based on buyer behavior online and offline intent data. This refined buyer data can inform a 360-degree view of your buyer.  

These predictive analytics are invaluable for account-based marketing (ABM), allowing you to map your leads to accounts and identify new contacts within them. AI tools can also look at your most valuable accounts and find and target similar accounts and recommend the best time to send an email or launch a campaign.  

5.      AI function: AI-powered segmentation
         Marketing win: Improved engagement and conversion rates 

Time-consuming segmentation can be easily automated with AI. Melanie Fox, formerly digital engagement leader at Ingersoll Rand, explained to B2B Marketing that she recognized the need for the company to move away from ‘batch and blast’ communications to highly targeted groups with specific identified needs. They looked towards AI within marketing automation for the answer and specifically IBM’s integration of its high-profile Watson AI platform into its Campaign Automation platform.  

“One of the things that impressed us most about the IBM solution was its ability to automate time-consuming processes such as segmentation – enabling us to build personalized campaigns at speed and scale,” explains Fox. “For example, we can now create campaigns with dynamic content designed to appeal to specific customer roles. This means we can reuse the same basic campaign template, but show the recipients different creative, information and images depending on factors such as their job title.” [LinkedIn & B2B Marketing, AI in B2B].  

AI tools working within your marketing automation platform have powerful capabilities to study all of your data and segment buyers automatically based on the criteria you choose. This enables more accurate persona building, improved customer engagement and an uptick in ROI.  

“The great thing about AI is that it can predict and learn in real time what the audience is going to be receptive to… [so we can] create a great value exchange between the brand and consumer in ways we weren’t able to do before.”  
Bob Lord, IBM Senior Vice President  


What AI plans do the main Marketing Automation Platforms have?

The good news is that the above could soon be available ‘out of the box’. The key players in marketing automation are already working on the roll-out of new generative AI within existing automation platforms with the goal of enhancing performance and production. Oracle, in partnership with Cohere, have promised end-to-end generative AI that will “focus on data security, model customization, and enabling enterprises to create business value.” Sensei GenAI from Adobe goes into more detail and will offer tools such as audience creation and activation, automatically creating new audiences, generative playbooks with simulated customer journeys and segment refinement, as well as other functionality. Meanwhile, Salesforce have introduced their latest generative AI product offerings, Commerce GPT and Marketing GPT. The latter will allow marketers to “automatically generate personalized emails, smarter audience segments, and marketing journeys.”

Summing up 

AI-powered marketing automation is fast becoming a key tool to exploit in order to stay ahead of your competition. Before you start to implement the capabilities of AI, make sure you are buying the right tools and platforms for your organization and marketing needs – each AI platform has its own pros and cons. You may choose to purchase technology with embedded AI capabilities (and this will include the MAPs themselves), build your own or leverage pre-trained AI models through services and platforms from third-parties.