The infusion of ai into marketing automation platforms

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The rapid adoption of generative AI has raised the volume of excitement among marketers. AI-enabled enhancements to core use cases of marketing automation platforms—data management, campaign/lead management, and workflows/integrations—are being introduced by Salesforce, HubSpot, and other market leaders. They will change the mix of tasks marketers perform on a daily basis and impact planned improvements to customer experiences and satisfaction.

This quote sums up the scale of AI’s impact:

“Next-generation marketers know that to deliver the personalization and experiences modern consumers expect, marketing must become smarter. It must become marketer + machine.”

– Paul Roetzer and Mike Kaput, Artificial Intelligence Marketing
This statement could have been applied to the mainstream canada whatsapp data adoption of marketing automation platforms (MAPs) as natural language processing (NLPs) experienced an inflection point—similar to what we’re seeing with AI today—10 years ago. The widespread adoption of marketing automation set the stage for the exponential growth of applications, which will grow to over 10,000 by 2022—a 6,000% increase from 2011.

Why does this matter?
New capabilities will emerge from infusing MAPs with AI, further expanding the influence of the foundation of most organizations: a core MAP integrated with CRM. Therefore, large enterprises should invest in finding ways to modify their use cases to incorporate new AI capabilities. Tried-and-true best practices with AI technology will drive value in 2023 and beyond.

Here’s how AI will be applied to the three main uses of marketing automation. Each of these three will be the focus of a follow-up deeper dive piece next year.

Data quality
Data quality will be even more important when our data is used to train company-specific AI models.

Underlying data about customers and prospects is a big bet for personalizing marketing. As the amount and variety of data captured increases, efforts will need to be refocused on adapting to more natural language defaults in drop-down menus, form fields, etc. to describe customer engagements. AI will enable marketers to understand, process, and analyze data more efficiently.

Campaigns and lead management
AI will enable new campaign approaches within existing workflows. Generative AI will augment these approaches by choosing between content AI integration prompts or asking an AI assistant to help “code” business processes.

Workflows and Integrations
Previously assumed scope limitations for broader operations and orchestrations will be tested. If generative AI can help coders fix code, it’s only a matter of time before it can help extend an open API beyond a native integration.

Native platform integrations were the original natural language for field mappings and workflows between CRMs and marketing automation platforms. Instead of asking an IT team to build a custom API, we could use natural language software interfaces to configure them.

While overall AI trends are advancing at an unprecedented pace, reinvesting in these core MAP processes will prepare your organization to quickly adapt to these new AI-infused capabilities.