One of the more popular features in the PricingBrew Journal is our Help Desk, where subscribers can send in questions about the specific pricing issues they’re wrestling with, the organizational problems they’re running into, and even the new initiatives they’re thinking about pursuing next.
Our research team will then work to provide straight answers and practical advice, based on what we’re seeing and hearing about what actually works in other B2B environments. No theory for theory’s sake. No vendor hype. No hallucinations. Just frank info and advice about messy, real-world pricing situations and challenges.
Recently, a pricing team leader submitted a question whose answer is not as obvious as it might seem to some…
Since Generative AI is really fast and pretty good at writing, couldn’t we use it to produce comprehensive differential value stories for our sales teams, without waiting on Product or MarCom to get their act together?
It’s a fair question. Because in far too many cases, the Product and Marketing teams don’t even realize that the product specs and fluffy platitudes they’ve been serving up for years are woefully lacking in today’s noisy and hypercompetitive climate. And meanwhile, sales reps are out there every day, struggling to explain why your offerings are better than the alternatives, using arguments, messages, and materials that are shallow, incomplete, inconsistent, and just plain weak.
As such, the idea of using Generative AI to dramatically accelerate the production of more comprehensive and robust value cases is extremely compelling. And I have to say, there are some very real positives about it…
Generative AI is great at following basic instructions to very quickly produce something that at least resembles a coherent story or argument. In the process, it can also suggest various ways to frame benefits, highlight differentiators, organize talking points, and even anticipate and address potential objections.
And instead of every rep having to improvise their own value stories for different opportunities, you can use AI to both tailor and standardize the messaging across different customer segments, applications, and competitive situations.
So yeah, there’s a whole lot of potential! But there are also some gigantic caveats that should not be overlooked or ignored…
On its own, GenAI doesn’t actually know what your customers value most. On its own, GenAI won’t understand the nuances of your target segments or the trade-offs your buyers are being forced to evaluate. And on its own, GenAI can’t know the differentiators your buyers are really willing to pay for, or to what degree.
What GenAI does have, however, is a massive amount of generalized and largely consumer-oriented information, scraped from the recesses of the public internet, and combined with an extremely sophisticated ability to predict what you want to hear while sounding like it knows exactly what it’s talking about.
It will confidently tell you what your customers care about most…even if it’s dead wrong about who your customers are in the first place.
It will authoritatively describe how your competitors stack up…even if it really has no idea who or what your buyers deem to be viable alternatives.
It will compelling articulate how your products deliver against buyers’ value drivers better than the alternatives…even if every feature, function, and differentiator is entirely fabricated, along with nearly every other aspect of the story.
And the real kicker here is that it will all sound great. Polished, professional, logical, and even quite persuasive. It’ll be the kind of thing one could easily imagine a newbie dropping into a slide deck or a sales playbook, no questions asked…even though it’s mostly Bravo Sierra.
The point is that if you’re thinking about using Generative AI in this way…and again, I believe there are tons of great reasons you should absolutely pursue it…it’s all about the raw materials you’re feeding into the machine:
- Customer research. Not guesses or anecdotes. Evidence-based insight into what different customer segments value, how buyers prioritize trade-offs, and what outcomes matter most.
- Competitive analysis. Not generic positioning statements or feature-set comparisons. A clear-eyed view of how the perceived alternatives deliver on the things that actually matter to buyers (see above).
- Key differentiators. Not platitudes, puffery, or mere differences. An objective assessment of where, how, and by how much, your offerings are meaningfully better at delivering more of what buyers value than the alternatives.
You don’t get a pass on the homework. As the fundamental building blocks of rock-solid differential value cases, these are the key inputs you’ll need to be able to provide. Without them, you’re just asking GenAI to hallucinate something that sounds plausible.
And that, my friends, is just asking for trouble.
The Fundamentals of Value-Based Pricing
Value-based pricing is like any other business practice in that most of the power comes from mastering the fundamentals. In this on-demand webinar, learn the core concepts and essential processes that generate the most bang for the buck.
Step-by-Step Competitive Analysis for Strategic Pricing
How to use competitive analysis to identify actionable opportunities to gain strategic advantage, expose competitive gaps, provide differentiation beyond price, and reduce the pressure to discount.
Communicating Value Over Price
How do you know whether your value messaging is good, bad, weak, or strong? And how do you ensure that the value of your offerings is being communicated as effectively as it really could and should be?
