3 Ways B2B Marketers Can Use AI To Increase Customer Engagement
This article is a contribution from PathFactory’s Co-Founder Nick Edouard.
Companies know they need to be using artificial intelligence to attract, win, and retain customers in 2023, but knowing exactly how to use it can be challenging. There are so many possibilities and making the transition can feel daunting at times.
We know AI offers the ability to create truly personalized business-to-business (B2B) customer journeys that are just as unique as the superior consumer experiences provided by consumer leaders like Netflix and Amazon. However, not every company has access to the same resources and technology as those behemoths. How can a company with only 100 or 1000 employees translate that vision into reality?
We’ll explain three core use cases for AI in B2B marketing that can serve as a guide for your ongoing research, piloting, and adoption of the technology.
1. Scale Your Operations
There are plenty of AI use cases in B2B marketing. AI can do all sorts of things, including:
- Write email subject lines
- Recommend content
- Tailor customer content journeys to personal preferences
- Create data-driven content
- Inform keyword research and content strategy
But, no matter what AI can do, it’s built for scale from day one.
AI excels at making predictions using large datasets. The more high-quality data, the better the prediction. In fact, AI performs all of the above use cases better the more you throw at it. For instance, an AI tool that writes email subject lines will likely write better subject lines after 100,000 subject lines written than 10,000.
Traditional marketing technology often becomes more unwieldy and complex the more data it’s required to process or handle. The opposite is usually true of artificial intelligence.
That means marketers should look at what they’re already doing (or trying to do) with traditional marketing technology. There’s a very real chance AI can scale your existing operations far better than—or in tandem with—the systems you’re currently using. It just needs a large, high-quality dataset to run on.
2. Outsource the Right Decisions
Many marketers fear AI, because they worry about losing their decision-making power over campaigns and strategy. Make no mistake, AI does make decisions for humans. However, there is nothing to fear, because AI is best at making decisions you could never make in the first place.
Take the following example:
Your traditional marketing automation platform requires you to be heavily involved in decision-making. You use rule-based logic to determine which marketing messages and actions are best for a particular prospect. The marketing automation software then executes your decisions.
However, this type of decision-making isn’t overly complex. There’s a limit to just how intricate your marketing automation workflows and logic can become before the whole system becomes ineffective to manage.
But what happens if you need to provide highly personalized experiences to hundreds of thousands or millions of prospects and customers? Humans don’t have the cognitive capacity to plan out a campaign of this complexity. And today’s traditional marketing solutions don’t have the firepower to execute it.
This is another area where AI excels. AI takes these types of highly personalized, at-scale decisions out of your hands, because it’s the only technology capable of making these decisions in the first place. By making thousands and thousands of marketing decisions at scale, AI does what it does best—while freeing up human marketers to do more of what they do best.
That means B2B marketers should look for areas of current or potential complexity in decision-making to deploy AI. It’s not about outsourcing your current decisions to AI. It’s about finding the decisions you’re struggling with or unable to make on your own.
3. Analyze Large Volumes of Data
B2B marketers can use AI to scale their current operations and outsource decisions that are beyond them. But there’s one more big area where AI can be deployed to great effect: Data analysis.
Large volumes of data can be an AI system’s natural habitat. If you have a lot of data you need help capturing value from, AI could be a good fit. That’s because AI not only analyzes large volumes of data, but also surfaces insights that human analysts or traditional data tools miss.
These insights can drive both major cost reductions and revenue increases. Not to mention, these may be business opportunities that you didn’t even realize were possibilities.
It’s just another reason why so many B2B marketers are turning to artificial intelligence in various areas of their operations. There are plenty of ways to apply the power of AI, if you know where to look.