Generative AI continues to capture our attention but hasn’t yet demonstrated its impact on marketers’ day-to-day lives. There is certainly a big area of opportunity in content creation, but genAI also has the potential to impact B2B messaging for the better. Forrester’s data shows that 59% of buyers note that the materials that vendors share fail to demonstrate a clear understanding of their organizations’ needs. B2B marketers tend to default to information about their products, which continues to turn off buyers. Generative AI can help craft messages based on buyers’ needs, but this will require experimentation and iteration. Here are two areas where portfolio marketers should explore using generative AI in their messaging process.
1. Messaging Personalization And Activation
B2B messaging is notoriously complex. There are numerous levels of messaging that B2B audiences demand, and brand, thought leadership, portfolio, buyer, and employee messaging, among others, all must be connected to deliver the insight that audiences want. Portfolio marketers often struggle to coherently drive these various messages into content and communication programs. Generative AI can help marketers customize and personalize messages based on context.
For example, a portfolio marketer who is preparing messaging to target CFOs in the manufacturing industry in Germany may use generative AI to pull together brand- and portfolio-level messages targeting CFOs, messages for manufacturers, and messages for German audiences into a single narrative. It could also prioritize them based on the interests of the audience.
2. Competitive Messaging Insight
Portfolio marketers are always looking for better ways to understand their competitors. Competitive intelligence tools do a good job of mining the wealth of information available on the web, but parsing all the specific messaging that a competitor uses can be tricky. Generative AI tools aren’t best leveraged as search engines, but they can help marketers summarize competitors’ content into key message points that can be refuted or countered.
For example, portfolio marketers can ask for a summary of the top three things that their competitor is saying to a specific audience and then prepare responses for a seller who is dealing that competitor to help them differentiate in an active deal.
These two experiments in generative AI are just that: experiments. Generative AI is still prone to errors, hallucinations, and other problems that won’t allow marketers to fully automate or take on any of these tasks today. By testing these applications in their own organization, however, portfolio marketers can begin to understand better how they might make generative AI their superpower and help their messaging hit the mark.
If you begin to experiment with generative AI in these ways, reach out to me on LinkedIn or through your Forrester account management team.