A couple of weeks ago, I wrote about what AI is and what it’s not. This area of technology is constantly evolving and still fairly fresh, but it’s been out long enough, and there’s a body of research emerging such that we can begin to understand and implement it in ways that are practical and appropriate beyond the initial flush of excitement.
So, this week, I want to talk about four great potential (and tested) ways to use it in complex sales.
Characteristics of Good Uses for Generative AI in Complex Sales
Not all potential uses of AI are good uses. Later, I’ll talk about the bad and the ugly, but today, I’m talking about the good. The practical uses of generative AI in complex sales share a few qualities in common:
- They are based on specific, carefully curated human-generated data sets
- They serve a specific strategic purpose within the organization
- They save time and creative energy so humans can focus on more strategic and high-level work.
Here are two key uses we’ve found to be effective for our sales and marketing teams and two more we think have strong potential.
- Summaries
At Membrain, we use various AI-powered tools to write summaries of podcasts and meetings. This saves a lot of time for our creative teams and makes it fast and easy for our sales teams to review the content of meetings and find critical information within them.
Summaries are a terrific use for AI because the AI is accessing a limited set of data (the recording) and producing an outcome based on information that’s already been vetted by a human. It reduces the likelihood of “hallucinations” and wrong information, and provides an outcome that is useful and beneficial for humans to use.
- Content Repurposing
If you’ve got a body of proprietary content and information such as white papers, case studies, ebooks, research, and processes, AI can be a great tool for turning all that rich content into secondary content for social media, newsletters, and other sales and marketing content.
Again, this is a use where the AI is less likely to “hallucinate” wrong information because it’s based on a controlled set of data (your expertise). And it’s valuable because you can ask it to produce content for specific platforms, in a specific voice, using particular sections of your content. And in this way, almost infinitely generate useful and valuable content that aligns with your messaging and is unique to your organization. We’ve only begun exploring this use on our team, and excited to continue to build on what we’re learning.
Of course, you should have all content reviewed by a human familiar with your messaging and voice, but with that caveat, it can be a much faster and cheaper process than having humans on your team fully regurgitate existing content into new forms.
- Finding Answers Within A Specific Data Set
Most established companies have a wealth of “sales enablement” content that they make available to their sales teams. But it’s notoriously difficult to organize your materials so that salespeople know where to find it, when, and how, and to actually get them to use it.
So you end up with a lot of ad hoc content “creation” or outdated info being shared. This is a task that AI can potentially help with. If you train it on your own IP and then provide a chat tool to your salespeople, they could query the AI when a customer has a concern, and the AI could help them locate existing content to provide to the customer. This is a toolset we’re playing with introducing to Membrain and we’d love to know if you’d love to use a tool like this.
Again, we believe this can be effective in part because it’s based on a limited dataset, and it’s overseen by human intelligence. It could save a lot of time so your people can do the parts of their job only they can do.
- Idea Iteration
In the BCG study I cited in my earlier “What is AI” piece, it was revealed that AI is really bad at making strategic decisions, but actually quite good at creative ideation. Among their consultants, when tasked with coming up with product innovation ideas, those who used AI outperformed their peers not using AI by an average of 40%.
What does this mean for sales? It means that if you’re generating ideas for innovating your messaging, your process, your methodology, or product, AI can be your best friend. Additionally, you could use it to brainstorm ideas with a client, and then review the possibilities together to find best fit strategic solutions.
So far, these are some of the best uses we’ve come up with for using AI to support salespeople involved in complex sales. As I’ve mentioned previously, I’m not a fan of shoving it into every possible part of sales technology. The current glut of poorly thought-out AI uses is creating a lot of noise. Next time, I’ll talk about some of the worst cases I’ve seen.
But for now, I want to know what you see as its best uses in your sales process. Are you using it in any of these four ways? Or are there other uses you’d add to the list?
