Nikki Candito, VP Integrated Marketing, Anteriad, explains how AI and generative AI tools can help B2B marketers identify and track behavior by buying groups. AI can sort and track data signals, and assign identities and roles to buyers, and generative AI can create customized content for each position.
The holidays are a time when personalized email shines. Retail marketing technologies are touting their use of AI this time of year to help their customers drive revenue because it works. Like millions of other shoppers, I know I'll see special offers in my inbox based on my recent search and buying behavior.
B2C targeting is straightforward because it targets individual shoppers. A B2B marketer's targeting job can be a lot more challenging. To be successful, a B2B marketer should target an entire buying group instead of just one person, according to Forrester's research. Gartner has found that buying groups can range from 6-7 people, or even more, involved who need to be consulted to make a single purchase decision.
Looking to 2024, the consumer holiday season's AI-driven marketing frenzy can be an exciting inspiration for B2B marketers. Recent research from the Winterberry Group shows that B2B buyers are acting more like retail consumers, preferring digital channels and self-guided study and responding to tactics like targeting and personalization. AI can help B2B marketers take advantage of this trend and get ahead of their competitors in the new year.
AI makes big data smaller
Historically, B2B marketers had much less data to work with compared to B2C marketers. A single retail website may get hundreds of thousands or even millions of visitors in a single day, if not more. A typical B2B website has far fewer visitors. This makes their customer file smaller, which can be a barrier to spotting patterns in the data. But, with the help of AI, B2B marketers can more easily break down the data and put it to work.
B2B buyers are using online resources much more heavily. In addition to a vendor website, buyers are visiting everything from YouTube to peer review sites, analyst sites, and popular blogs and articles. As buyers go along their buying journey, their activity leaves insights for B2B marketers along the way. The more of this information B2B marketers can connect to their customer files, the more they start to understand things like use case, intent, budget, and product of interest. AI helps marketers take the data from these online activities and turn them into actionable insights.
Marketers can use AI to find the best ways to segment data and find their Ideal Customer Profile (ICP). By asking for prompts to slice and dice data differently, marketers can get a new view that helps them find their ideal customer. Even further, AI can help B2B marketers analyze closed/won customer data to identify each contact's buying roles and develop predictive models that identify prospects that look like a company's best customers.
A considerable benefit of AI is that it can help B2B marketers use their data to find buying groups. Using AI to sort through the volume and complexity of the data can often be the only way that B2B marketers can gain a good picture of critical stakeholder activity and how stakeholders interact because of the volume and complexity of the data.
By analyzing data points from customer engagement across their buying journey matched and layering it with firmographic data like job titles, marketers can be used to identify the buying group and each member's buying role. Using AI helps marketers do this at scale. With this information, B2B marketers can tailor their targeting to each buying group member depending on their role.
AI makes personalization more personal
Anyone buying a red sweater doesn't need to spend three months reading research papers about which sweater performs best in cold weather, looks good with jeans, or stays lint-free. The copy on the website and a few customer reviews are usually enough – and a good blog or influencer video is even better.
Compare that purchase experience to a typical multi-month B2B process, which relies heavily on content from articles, research, and case studies. B2B marketers spend a considerable portion of their time and resources crafting content for different types of buyers. Within a buying group is the key decision-maker, the person most likely to use the product daily, the finance lead, the tech lead, the data lead, and potentially several more. They each want information that relates to their decision specifically. For any B2B company with multiple ideal customer profiles, the amount of content needed to satisfy everyone is enormous.
Here's where AI is starting to make headway. Generative AI can write customized content for buying group roles from a single asset. Gen AI can quickly rewrite a case study to highlight information that matters to each stakeholder. What's more, AI can repurpose content for different channels like social media or email. A marketer can take one asset and have the AI position it differently based on other formats or rewrite that asset to focus on the specific buying roles' pain points for different targeted campaigns.
AI improves customer experience
Today, many B2B marketers employ AI-driven chatbots to help with customer service on the website, and that approach will expand even further. As prospects get closer to purchase, AI can be a helpful tool as marketers prepare to hand leads over to the sales team. Generative AI is a "large language model," which means it can process and understand language across text and audio for things like sentiment and intent. With AI analytics, B2B marketers can prioritize the leads that are most likely to buy, and rethink how to handle leads that aren't as ready to warm to the sale.
For a buying group, AI could identify which stakeholders are most engaged and which are still hesitant. This can also help sales teams with their approach, choosing a strategy to connect closely with their allies and find ways to engage stakeholders still on the fence.
B2B marketers have already laid the groundwork for a digital sales process. That means a virtual treasure trove of data is ready and waiting to feed different AI strategies to reach buying groups more effectively. Marketers can start by identifying pain points in the journey. Perhaps they lack resources to create personalized content for each stakeholder or don't have enough insight into why leads are going cold. These pain points are the right places to focus. AI has the potential to unlock the next level in buying group-based marketing.
With the proper generative AI prompts, marketers can segment their data and find their Ideal Customer Profile. AI can analyze data for patterns to find buying groups. For example, at Anteriad, we look at data to understand which customers are most profitable, who have been with us the longest, who engage with us regularly, and who refers us to other companies. Then we use AI to analyze our data, look for trends and patterns among our customers to help us build out our ICP. AI can help us understand which of these different data points is most strongly associated with high long-term customer value.
We also ask AI for advanced Excel formulas to ensure we’re testing all the ways to run analysis on what products customers purchased.. This subsequently saves our marketing operation hours of manual work while we learn new ways to work with data.
With buying groups in mind, marketers can use gen AI to build custom content for each buying group role and add the content to chatbot flows for a personalized customer experience. All of these tactics are free and ready to be tested in the new year.
