If your company is like most, you probably have a slide deck that lays out your customer tiers: enterprise, mid-market, SMBs.
But if your company is like most, you’ll also come to a point where you are flipping through that deck and realize that those old categories no longer make sense. They don’t actually reflect what is happening in deals. Buyers are crossing boundaries. Product mixes are blurring.
Suddenly, yesterday’s logical segments feel like yesterday’s news.
The Problem with Traditional Segmentation
This isn’t just a data issue.
Traditional segmentation, where customers and prospects are grouped by customer type, size, or product line, assumes that willingness-to-pay is somehow stable inside each bucket.
But in B2B markets, willingness-to-pay shifts with context: urgency, competitive pressure, service requirements, and industry dynamics. Simplistic static segments can’t keep up.
To counter this reality, some teams try making the segments more granular. But piling on more micro-segments often makes things worse:
- Complexity creep: Dozens of tiny segments confuse sales teams and slow down decision-making.
- Stale signals: Evergreen attributes like company size or industry can’t capture deal-by-deal dynamics.
- False precision: The appearance of accuracy masks the fact that price guidance can still be misaligned.
In the end, the team has segments that aren’t much more useful than the original big buckets.
Dynamic Pricing Segmentation
A better alternative—and one we increasingly see in the wild—is dynamic, attribute-based price segmentation.
Instead of asking, “What type of customer is this?” it asks, “What’s happening in this deal at the transaction level that affects willingness-to-pay?” It considers attributes like competitive intensity, time sensitivity, required support levels, unit volumes, and payment methods.
If that all seems like too much for one human being to figure out, you’re right.
Instead, modern pricing tools can crunch all these numbers in the background. Sales sees only the final result—clear, simple guidance based on the best intelligence available.
This approach isn’t about adding complexity for its own sake. It’s actually just the opposite. It abstracts the complexity, hiding it from the reps in the field while providing them with prices that are far more accurate—and far more profitable.
What about you? Is your team using dynamic segments that reflect reality? Or are you forcing today’s deals into yesterday’s boxes?
If you haven’t tried this approach yet, or if you think your implementation could use some optimization, check out the Dynamic Price Segmentation webinar. It offers a more comprehensive explanation, complete with practical examples. It also includes tips on how to build and operationalize a model that captures real willingness-to-pay without burying your team in the complexities of attributes and data.
The world has changed a lot in the last few years. It just makes sense that it’s time for your pricing approach to evolve as well.
Dynamic Price Segmentation
How do you build a price segmentation model that aligns to deal-by-deal price sensitivities while still being manageable? In this session, we illustrate why dynamic, attribute-based segmentation is best practice.
