Needs-based segmentation is marketing’s secret weapon. It focuses on uncovering the “why” behind customer decisions—their true motivations and needs. Yet, many companies struggle to adopt it because it’s been perceived as “too hard” to definitively classify B2B accounts (i.e., “tag them”) into one and only one segment.

AI is changing that. Effectively tagging accounts is now within reach for marketers and sales teams, and within hours instead of months. Read on to discover how AI makes needs-based segmentation practical and effective.

Why Traditional Segmentation Falls Short

Most companies rely on behavioral or classification-based segmentation. These methods focus on customer’s past actions to segment them (e.g., “loyalists”, “occasional users”, etc.) or broad descriptors, like company size or industry.

While easier to understand than a needs-based segmentation model, these approaches lack depth. They provide superficial insights, leaving companies with bland strategies that don’t resonate deeply. 

Even more importantly, these approaches don’t provide clues as to how to gain more business from an account.  The behavioral segment of “occasional user” tells you only that you have some but not all of the business of an account in this group.  But a needs-based segment like “Operations Maximizers” lets you know what you must do to win more with these accounts.

Here’s an example: A medical device client found out that reps were touting their technology’s clinical benefits without paying enough attention to how the device could fit into existing workflows.  This worked with a large segment of customers focused on maximizing patient outcomes.  But a huge segment of customers did care about the operational implications of this type of device.  So, our client identified hospitals in this needs-base segment (“called Operations Maximizers”) and tailored their messaging to highlight workflow advantages.  They immediately began winning more with both segments.  

Actionable Advice: Move beyond behavioral or firmographic segmentation methods. Ask: “Why do different customers make different choices?” Let this guide your segmentation strategy.

Why Companies Abandon Needs-Based Segmentation

Even companies that are initially excited about a needs-based segmentation approach eventually must face a reality.  Sales reps often feel that many of their accounts could fall into more than one segment. 

This causes frustration followed by resistance and, ultimately, abandonment of the needs-based approach.  Historically, it’s been easier to figure out which accounts fit into firmographic or behavioral segments like loyalists and occasional users, using data. 

But now, AI tools can learn the specifics of your segmentation approach and instantaneously analyze vast amounts of data—from company websites to annual reports and more – to accurately tag accounts into “one and only one” needs-based segment.   This process is a game-changer. AI handles the heavy lifting of tagging accounts and will provide a “source trail” to explain its choice, leaving sales teams to simply fine-tune the tagging for a small percentage of accounts.

As an example, in Japan, our own Scout^TM AI tackled a notoriously private market. It helped create a needs-based segmentation that explained the major motivating factors by which large B2B accounts made decisions.  Even more impressively, it analyzed digital clues and tagged over 90% of major accounts into a segment that the responsible sales rep agreed with.

Actionable Advice: Train your AI system on your needs-based segmentation approach. Then use the AI system to tag accounts quickly and explain why each account falls into its proper segment. 

Getting Sales Teams on Board

As stated earlier, sales teams have often in the past resisted needs-based segmentation. They’ve seen it as complicated and abstract. AI bridges this gap by making tagging B2B accounts into specific segments faster and more actionable.

It’s still great advice to get sales team members involved early in your AI-enhanced segmentation efforts.  They will see that AI can take the guesswork out of segmenting and tagging accounts, because it has the ability to process all of the available data on every account instantaneously.

Actionable Advice: Partner with respected members of the sales team to kickoff, refine and deploy your needs-based segmentation strategy.

Conclusion: Make no mistake: AI isn’t just enhancing needs-based segmentation. It’s unlocking its full potential by adding an accurate, respected tagging process with a source trail to explain decisions. The result? Better targeting, stronger value propositions, better marketing and sales coordination, and happier customers. Ready to move beyond basic segmentation? Let AI guide the way to smarter strategies and better results.