Why AI’s Jump to Conclusions Might Be Perfect forB2B
B2B marketers must jump to conclusions
In the early 2000s, I was the chief marketing officer at a web content management software company. Our monthly goal could be creating or nurturing as few as 30 leads. The company would close an average of five to 10 new customers a month.
Understanding which ads, platforms, events, and thought leadership topics resonated the best hinged on a small number of people. We looked at the minimum data and estimated what worked. We had to jump to conclusions.
Now, some B2B companies jump to the right conclusion – the perfect thought leadership message or brand differentiation. The flywheel starts because differentiation happens quickly. By finding the groove of a disproportionate share of voice, marketing and sales become easier.
The perfect example of jumping to the right conclusion is the concept of inbound marketing.
Inbound marketing: A great jumped conclusion
In the early 2000s, an interesting trend in digital marketing appeared called “article marketing.” Brands could create interesting, thought-provoking articles on the web that would help the companies be discovered through search engines. Sound familiar?
But none of the content management or marketing automation solutions latched onto that as a messaging strategy. (To be fair, it wasn’t as obvious as it is now.)
In 2006, Brian Halligan and Dharmesh Shah founded HubSpot as a way to grade your website, look at social media engagement, and create blog posts and landing pages for leads. They coined the term “inbound marketing.”
This Google Trends graph shows that searches for “inbound marketing” (red line) gained its groove around 2008. It overtook searches for “article marketing” (blue line) by 2013. HubSpot had made the “inbound marketing” messaging a standard.
Brian didn’t have data on which to base that messaging strategy. If he had used the available data, he might have centered on “article marketing” as the term. But he looked at Dharmesh’s success through blogging and connecting through content on social media and believed that represented a new way of buying. Brian liked the concept of calling it “inbound,” as he shares in this 2019 interview.
AI’s jump to conclusion may provide a B2B opportunity
I see an emergent challenge and perhaps a unique opportunity in generative AI and B2B marketing and content.
Generative AI tends to confidently “make up” answers. These “hallucinations” occur because the LLMs (large language models) acting as information sources are limited to what’s generally available on the internet. For niche B2B content, these sources may be few. So, when it comes to B2B content, generative AI often jumps to false conclusions.
Opportunity for jumping to conclusions
If no human intelligence exists to feed generative AI tools, they’ll jump to false conclusions. But since B2B marketers have been jumping to conclusions for years, you use AI’s weakness to your advantage.
If you’re in a niche B2B market, AI’s false conclusions can propel or at least inspire you to find your version of “inbound marketing.” You can create content that defines (or redefines) the industry – the information that separates and sets new standards for your solutions to problems. You can more easily set the “right answer” for what generative AI should deliver.
You can teach your audiences as you train the machine.
This opportunity requires a renewed focus and big-time human output of thought leadership, content, and idea messaging. It also means you cannot lean on the traditional ways of defining what you do. You should learn what and how AI thinks of your industry, your approach, and your terms of art. See what your buyers can experience through these AI tools. Continue reading →
