4 Use Cases of AI for B2B Marketers
AI has evolved significantly since the days of Siri’s languid chats with John Malkovich. It not only eases the burden of compiling and parsing information but is beginning to offer new and unique insights. In other words, the days of AI being primarily a buzzword are coming to an end.
Marketers, in particular, are finding that AI is more applicable to their business challenges, with user-friendly, pragmatic products seeing successful adoption. And, as AI and machine learning marketing capabilities are giving B2B marketers more lift and scale across their programs, this exciting tech is poised to become standard best practice as fast as it becomes available.
Here are four key ways that AI platforms and technologies are changing the game for B2B marketers right now.
1. Content: Delivery, Not Creation
Great content is expensive and time-consuming to create. Is it any wonder that so much has been made of AI programs can write content, web pages and emails that are grammatically correct and that target appropriate keywords? As a content marketer myself, I’m fascinated by these technologies, but extremely skeptical that we’re anywhere near an application of the technology that passes a sort of B2B content marketing Turing test. The truth is, the web (and your buyers’ inboxes and social streams) are full of mediocre content. More mediocre content will not stand out in the din of content marketing, and no AI program can generate the kind of new, creative, innovative ideas that will get your brand noticed. Yet.
But that doesn’t mean there’s no room for AI in content marketing.
Where B2B marketers can really flex some AI muscle is in content delivery. Standing out in today’s digital marketplace means maintaining markets of one with thousands—or even millions—of prospective buyers. That means delivering the right content to the right contacts at the right time, but that kind of personal interaction is impossible to scale.
Content marketing AI can scan your entire website and/or content library, categorize and organize the content you create, and deliver the right offers, pages, emails, social media posts, and more, to each buyer at every interaction. That keeps you doing what you do best—creating amazing content and campaigns—and lets AI do what it does best—giving you the lift of super-precise targeting across an enormous number of interaction points.
2. Social Media: Expand Your Audience
It is important to not just look for artificial intelligence you might add to your arsenal, but to examine what AI you might already be using and simply need to leverage better. If you want to experiment with AI and see the impact it can have on your marketing, look no further than Facebook Ads.
Facebook’s Lookalike Audience is a brilliant product that uses your first-party data to help you “find more people who look like your current customers.” With Lookalike, you can create custom audiences and massively expand the impact of your marketing—all based on behavioral data. This data can be:
- Pulled from a website by installing a pixel.
- Pulled from Facebook by assessing people who like your page.
- Uploaded directly as a list of current customers for Facebook to examine.
Similar technology is available for B2B marketers that scans digital signals from all over the web. Predictive lead scoring and predictive account scoring also use AI to expand your ability to reach buyers who look like your customers—in other words, opportunities that align to your ideal customer profile.
3. Google: The AI We All Use Every Day
Social companies like Facebook aren’t the only ones leveraging AI and machine learning to optimize the effectiveness of their ads. With Google touching upwards of receiving up to 3.5 billion searches every day, their RankBrain system might be the AI that people already interact with most, without even realizing it.
What is RankBrain? In short, it’s Google’s machine learning program that determines what and where results should be ranked in organic search. So how do you leverage it for your business’s marketing? By learning to use it.
But is RankBrain worth a B2B marketer’s time? Undoubtedly. As many as 90% of B2B buyers turn to a simple Google search to begin their buying journey, giving the businesses that adapt to RankBrain a distinct advantage. On top of the sheer amount of traffic coming from Google searches, SEO leads have a 13% better close rate than outbound leads.
While RankBrain hasn’t replaced the traditional SEO factors like keywords and backlinks, it is approaching things a bit differently. Now, a mere 53% of top 20 search results even have keywords in the title. Google is getting smarter thanks to RankBrain’s improved natural language processing (NLP), allowing it to parse human language and identify relevant results with more than just keywords. It remains for B2B marketers to lean into the change that Google’s AI is bringing to SEO strategy.
4. Email: Personal Conversations at Scale
Contrary to popular belief, email isn’t dead. It’s just wildly misused. With 270 billion emails sent every day, whether or not yours makes the cut comes down to how intelligently the message is targeted.
For the marketer, that boils down to timing, testing, and segmentation. Here again, AI can help, due to its ability to turn huge volumes of data into useful insight. AI that looks for the right elements can help segment customers, predict the outcome of a multivariate test, or even help you find receptive, adjacent audiences for a specific campaign.
Artificial intelligence and machine learning have been working for email marketers for years now, and many email and marketing automation platforms will emphasize their AI powers. The key to finding the right AI for email marketing is to invest in one that updates audience segments in real time, has predictive content capabilities, and provides a robust and marketer-centric vision for where AI will enhance the product in the future.
The Potential of AI, Made Practical
Just like all major technological innovations, artificial intelligence has been met with an initial level of distrust and even fear. However, most marketers recognize that AI is really only solving problems that they were already having: like maintaining personalized interactions at scale and gaining better insights into their buyer journeys.
How is AI serving your marketing strategy? Any use cases I missed?