At the top of many 2024 B2B marketing prediction lists is the mass adoption and implementation of generative artificial intelligence (genAI) across marketing collateral. Forrester’s July 2023 Artificial Pulse Survey participants agree, ranking creating marketing content with genAI as the most important use case for AI over the next 12 months. The same survey found that four out of five decision-makers anticipate a positive impact on their businesses within two years of implementing genAI.
With such high expectations, the question of how to use AI effectively doesn’t just apply to the obvious deliverables. It’s essential for companies to adopt tools that pave the way for innovative strategies to reach and engage their target audience—and AI implementation creates an opportunity to make your account-based marketing (ABM) strategy more efficient by automating repetitive tasks, enabling more effective personalization at scale, and optimizing resource allocation.
Read on to learn how AI can be effectively integrated into an ABM strategy to drive measurable results and gain a competitive edge.
Enhance Efficiency Through Automation
One of the biggest benefits of AI across all industries is its ability to enable humans to do things faster and often better. By dramatically accelerating automation capabilities, AI can process vast amounts of data in minutes, freeing up your marketing team’s time to dive deeper into campaign strategy and insights.
Repetitive tasks often consume a significant chunk of time and resources that can drain your team’s time, leading to errors, fatigue, and inconsistency. When it comes to ABM, which requires a deep focus and understanding of key accounts and buying committee member behaviors, there’s no room for error. While ABM is an effective approach, it is also a largely manual process—making it both time-consuming and resource-intensive.
AI plays a crucial role in streamlining ABM tasks through its automation capabilities. AI-driven ABM allows you and your team to analyze vast amounts of data to identify patterns and insights that might otherwise be missed by a human marketer. Once you upload your data sets manually or integrate your customer relationship management (CRM) platform with your AI platform, it quickly sorts through the information to compile key findings, which saves you and your team ample time from the tedious, low-value task of data aggregation and resolution. AI-powered analytics help you quickly understand customer behavior, identify buyer patterns, and predict customer needs, which enables your teams to tailor their efforts accordingly, increasing the chances of successfully capturing the attention of multiple accounts and converting them into customers.
AI’s automation capabilities also impact other repeatable processes, such as lead generation, email marketing, and social media management. Whatever you can automate, such as sending a confirmation email for a newsletter signup or posting on a social media platform, frees up valuable time for sales and marketing teams to focus on “the why”: the deeper insights around your audience and how you can clearly communicate why your brand is the perfect solution for their business needs.
Regardless of the streamlined ease and efficiency that AI offers with otherwise time-consuming tasks, you still can’t completely discount the human element. AI still requires input and oversight from you and your team to ensure that your processes and campaigns are effective and aligned with your overall marketing strategy. It’s important to view it as a co-pilot—there to assist you in your tasks but never fully replacing the expertise and knowledge you and your team provide.
Personalization Across Content and Messaging
In today’s competitive B2B landscape, delivering personalized customer experiences is no longer a luxury—it’s a necessity. Customers expect businesses to understand their individual needs and preferences, and to provide tailored experiences that cater to them. AI plays a pivotal role in enabling businesses to achieve this level of personalization, allowing them to create meaningful connections with their customers.
Each member of the buying committee has different concerns regarding any product or solution, and you need to have content and messaging ready to go to persuade them that you are the right partner with the right solution for their needs. Use generative AI to create content that addresses and solves each committee member’s concerns, and plot where the content and messaging falls within the buyer’s journey. Your AI platform can quickly work through the vast amount of historical customer data, including demographic data, purchase history (technographic data), browsing behavior, and interactions with customer service, to gain a comprehensive understanding of each buyer’s preferences and pain points. This data-driven approach enables businesses to deliver highly relevant and personalized content and advertisements that resonate with each lead on a deeper level to propel them through your sales funnel.
One collaborative measure between marketing, sales, and customer success teams is to observe buyer and customer interactions with an AI-powered chatbot. Chatbots and virtual assistants enhance personalized customer engagement by providing real-time assistance and answering customer queries efficiently that align with your messaging. Leveraging an AI chatbot as part of your ABM strategy ensures buyers and customers alike receive the support they need when they need it. Sales and customer success teammates can also pick up where the chatbot leaves off, so to speak, as they follow up with leads and customers to ensure they’re satisfied with the answers from the chatbot and provide any further information they may need.
This is another area where you must continue to oversee the content and messaging produced by AI to ensure it demonstrates an understanding of buyer pain points and concerns. With the use of genAI to produce marketing content expected to rise in 2024, Forrester predicts that 70% of buyers will grow frustrated with thinly customized marketing materials created by the technology. You must view genAI as just a tool and not an extension of you and your team for your content and messaging to stand out and truly resonate with buying committee members. Apply the knowledge gained from intent data and insights gained from your sales and customer care teams to the content and messaging generated from AI to ensure it reaches buyers more effectively. This approach enables you to continuously create net-new content for campaigns while also refining content, messaging, and nurture paths to meet the evolving needs and expectations of leads and customers alike.
Improve Decision-Making for Optimizing Processes
Your ABM strategy is never truly “set and done.” Measuring and optimizing the success of your ABM strategy is crucial to ensure that your efforts are continuously delivering the desired results. AI can play a significant role in boosting your marketing efforts through advanced analytics and predictive modeling that delivers actionable information for optimizing your approach, uncovering new strategies, and managing your resources.
AI-driven analytics enables you to gather and analyze vast amounts of data from various sources, including customer interactions, social media, website traffic, and more. This allows you to more quickly and efficiently uncover patterns, trends, and correlations that your team might otherwise miss, allowing you to make data-driven decisions with greater confidence. It can also help you gain insights into campaign performance, making it easier to optimize your content and messaging for maximum reach and engagement. This helps ensure that buyers receive a personalized experience tailored to their specific needs and pain points.
Predictive modeling takes your campaign measurement and optimization a step further by using historical data and machine learning algorithms to forecast future outcomes. This empowers you to anticipate customer behavior, identify potential leads, and optimize your marketing campaigns for maximum impact. By understanding which strategies are likely to yield the best results, you can allocate your resources more effectively and achieve higher ROI.
Future Trends and Advancements in AI for ABM
The future of AI implementation as part of your ABM strategy is bright, with new and exciting advancements on the horizon. These advancements allow businesses to use AI to better understand buyers and customers, engage with them in more personalized ways, and optimize their ABM campaigns for maximum results.
But one thing is vastly clear: AI platforms and content require a human touch. AI platforms perform best at gathering the “what”—the data sets you need to dive deeper into the “why” buyers are looking into your solution and what you can do to convince them that you’re the right partner. GenAI also saves ample time on brainstorming ideas for content. And while an AI platform can provide a great foundation for your content, you still need to educate the platform on your brand’s voice and guidelines and edit the content to ensure it has the right messaging that will reach the right members of the buying committee.
How Madison Logic Paves the Way for an AI-Driven ABM Strategy
When it comes to successful ABM strategies, you want as much data as possible. The ML Platform integrates with your CRM platform to help uncover key insights around your customers and buyers. ML Insights empowers marketers with real-time intent data from over 20 million companies that allows marketers to gain deeper insights into their target accounts, including firmographic, technographic, and behavioral data. This data-driven approach allows businesses to create highly targeted and personalized campaigns that resonate with buying committee members across in-market accounts.
Ready to see how a truly data-driven ABM strategy benefits your bottom line? Request a demo today to learn how you can leverage crucial buyer and customer data for your ABM initiatives and unlock new opportunities for growth.
