Blog post By Paula Chiocchi on 2022-11-09
Whether you realize it or not, Artificial Intelligence (AI) and machine learning technologies are everywhere. Things that just a short time ago seemed possible only in Sci-Fi movies are now a part of everyday life. Voice assistants that respond to our commands. Facial recognition in the palm of our hands. And of course, self-driving cars. I think Marty McFly and the rest of the 1983 “Back to the Future” characters would be impressed.
Businesses are continuously seeking new ways to use AI and machine learning to streamline operations, improve efficiency and optimize customer experiences, among other things. Marketers may have the most to gain from AI, according to Harvard Business Review. “Marketing’s core activities are understanding customer needs, matching them to products and services, and persuading people to buy—capabilities that AI can dramatically enhance.”
It’s no wonder “AI has proliferated” through the martech stack, says Forrester. “AI-powered technologies are making predictions and decisions to automate actions based on the needs of audiences and marketers alike while continuously learning from those outcomes.”
AI is powering lead gen in some interesting and very effective ways. Here are four practical ways marketers are leveraging AI to optimize campaigns:
Create seamless omnichannel experiences.
Programmatic advertising has risen as a top tool for marketers. Platforms that deliver ads to reach prospects across channels and at the right time – that’s AI.
The most common method of implementing programmatic buying is through real-time bidding (RTB), which is the practice of buying and selling ads in real time on a per-impression basis in an instant auction. This is typically facilitated by a supply-side platform (SSP) or an ad exchange. A demand-side platform (DSP) is a programmatic advertising platform that allows advertisers and media buying agencies to bid automatically on display, video, mobile and search ad inventory from a wide range of publishers.
Find buyers ready to buy now.
Using intent monitoring, marketers can zero in on prospects who have a high probability of being ready to buy. The process analyzes searches based on pre-selected keywords and uses natural language processing (NLP)—a type of AI—to categorize the signals across multiple keywords, allowing brands to apply the findings across all of their prospecting offers (or products) at one time.
It also provides brands insight into who their prospects are and where they are in the buying cycle, both of which are critical information needed for further personalization and lead nurturing.
Show your prospects you really know them.
Marketing personalization is surging, with marketers finding new ways to show prospects they know them far beyond adding their name or business to the email subject line. But personalizing each touchpoint would be incredibly time-consuming, and not feasible at scale. Marketers are finding new ways to use machine learning for personalized emails with relevant content as well as visual preferences, such as adjusting images or color schemes.
It’s important to note that efforts to personalize will be hindered without accurate data and can actually result in the opposite effect—showing you don’t know the contact at all! Quality data that includes firmographics, such as our OMI Living File®, is a must as AI technology can only rely on the data it’s being fed.
Deliver the right content at the right stage of the buying journey.
According to the Forrester 2022 Global Marketing Survey, 27% of B2B organizations plan to invest significant effort in using AI to drive content recommendations. As marketing becomes more customer-focused, sellers need to get ahead of buyers’ needs by delivering the right content based on their buying journey and know when to reach them to optimize sales.
Thankfully new ways are being developed to optimize content. One example is generative AI, which was identified by Gartner as a technology disruption that will impact sales for the next five years. Generative AI “learns from existing content artifacts to generate new, realistic artifacts that reflect the characteristics of the training data, but do not repeat it.” This can include images, video, music, speech, text, software code and product designs. Gartner predicts that by 2025, 30% of outbound messages from large businesses will be created with generative AI. This type of technology goes to show that AI is a science and an art.
So while flying cars and real hoverboards weren’t actually commonplace in 2015 (like they were in the second installment of the well-known time travel movie), who’s to say what’s possible in the coming years.
It’s exciting to see how advances in AI and machine learning will continue to improve B2B marketing, especially when it comes to lead gen processes. Every business wants to find new customers and increase sales. If there are new ways to do that more efficiently and with less headache, we’re ready for them.
Did you know? Over 75 million of OMI’s 80 million manager- and professional-level and above contacts are matched to the LiveRamp RampID graph, including 65 million records from our SMB and medical market databases. Contact us today to learn more about building a custom audience.
At OMI, we believe good things happen when you share your knowledge. That's why we're proud to educate marketers at every level - in every size and type of organization - about the basics of email marketing and the contact data that powers it.