In July 2019, Gartner published research by Brent Adamson and Nick Toman that quietly rewired the modern seller-effectiveness conversation. They looked at high-performing B2B sellers across thousands of deals and clustered them into three archetypes based on how they shared information with buyers.
- Givers — sellers who provide as much information as possible.
- Tellers — sellers who filter information and give buyers what they think buyers need to know.
- Sense Makers — sellers who help buyers make sense of information they've already gathered themselves.
Only one of the three archetypes actually improved buyer confidence. Only one of the three closed materially more deals. And it wasn't the archetype most sellers had been trained to be.
This is the Sense Making thesis, and it's the framework I think about more than any other when I coach sellers on how to be useful to a modern buying group. This piece is the definitive explainer: what sense-making actually is, why Givers and Tellers get beaten in modern B2B, and what "sense-making at scale" looks like when a lot of the information the buyer has already gathered came from AI.
The three seller archetypes, defined
Adamson and Toman's original framing (Gartner press release, July 29, 2019):
The Giver
The Giver's operating theory is that more information equals better decisions. They send whitepapers, case studies, ROI calculators, and follow-up emails at high volume. They believe their job is to make sure the buyer has everything they could possibly need.
The Giver was the dominant archetype in B2B sales throughout the 2010s. Every content marketing motion, every SDR sequence, every "helpful outreach" playbook is fundamentally a Giver playbook. Volume of value delivered.
The Teller
The Teller's operating theory is that the seller knows better than the buyer what matters, so the seller should filter aggressively. Tellers walk into a discovery call and prescribe. They tell the buyer what's important, what to prioritize, and what to ignore. Challenger Sale sellers, in their most orthodox form, are Tellers.
The Sense Maker
The Sense Maker's operating theory is different: buyers already have too much information. What they lack is a way to make sense of it. The Sense Maker's job is to help the buyer de-conflict, prioritize, and interpret the information the buyer has already gathered — not to add more.
Adamson and Toman found that Sense Makers were consistently the highest-performing archetype in the modern buying environment. Not by a small margin. By a large one.
Why Sense Makers win
The reason Sense Makers outperform is downstream of a specific truth about modern B2B buyers: they don't have an information shortage. They have an information glut.
A modern buying group of 6-10 stakeholders is armed with 4-5 independently gathered pieces of information per person (Gartner, https://www.gartner.com/en/sales/insights/b2b-buying-journey). That's 30-50 pieces of information circulating inside one buying group. Some of it is contradictory. Some of it is out of date. Some of it is AI-generated and not fact-checked. All of it is competing for the buying group's attention.
In that environment, Givers make the problem worse. Every whitepaper is another piece of information the buying group has to process, and every one increases the risk of new internal conflict. Tellers get resisted. Their prescriptions bump into the buying group's already-formed opinions and land as dismissive.
Sense Makers do the one thing the buying group actually needs. They come into the discussion, understand what information the group has already accumulated, and help the group make sense of it — reconciling contradictions, surfacing what matters, and quietly correcting misinterpretations.
Buyers with high confidence are approximately 10× more likely to make a high-quality, low-regret purchase (Gartner, https://www.gartner.com/en/digital-markets/insights/improve-b2b-buyers-confidence). Sense Makers build that confidence. Givers erode it. Tellers can't build it because they don't earn the trust required.
What sense-making actually looks like in a sales motion
Sense-making isn't a personality trait. It's a set of behaviors, and they're teachable.
Behavior 1: ask what the buying group already believes. A Sense Maker doesn't open a discovery call with "let me tell you about our product." They open with "walk me through what you've already learned, what you're weighing, and where you're not sure." This is not softness. It's efficiency. The seller is establishing the information map before adding anything new.
Behavior 2: name the contradictions. Once the seller has the map, the sense-making value comes from naming the tensions. "You mentioned your team believes X. But then you also said Y. Those two things are usually incompatible. Which one is the actual priority?" That's what sense-making sounds like. It's the seller being the person who names what the buying group is quietly struggling to reconcile.
Behavior 3: de-conflict with peer context, not with product pitch. When a Sense Maker adds information, it's almost always a specific data point from a comparable customer situation. "The last three customers who ran this decision your way ended up regretting the on-prem choice within 18 months. Here's what changed." That's peer context. It's the highest-leverage information a seller can add because it can't be pattern-matched from generic content.
Behavior 4: route to trusted third parties. Sense-making sometimes requires an outside voice the seller can't be. That's when a Sense Maker routes the buying group to a peer, a customer, or an industry contact who can validate the direction. The seller who knows when to bring in a third party — and has the network to do it — is the seller who closes clean.
Why Givers get beaten in modern B2B
Every AI SDR platform on the market is running a Giver motion. More email. More content. More touches. It's the definitional Giver behavior, industrialized.
Buyers respond exactly the way Gartner's research predicts. They stop engaging. Seventy-three percent of buyers actively avoid suppliers who send irrelevant outreach (Gartner, https://www.gartner.com/en/newsroom/press-releases/2026-03-09-gartner-sales-survey-finds-67-percent-of-b2b-buyers-prefer-a-rep-free-experience). The avoidance behavior is a direct response to Giver overload.
The AI-powered Giver motion is a category error. It uses AI to scale the exact behavior Gartner has told us since 2019 doesn't work. The result is what Melissa Hilbert calls the "value ceiling" of AI in sales — by 2028, AI agents will outnumber human sellers 10-to-1, yet fewer than 40% of sellers will report AI improved productivity (Gartner, https://www.gartner.com/en/newsroom/press-releases/2025-11-18-gartner-predicts-by-2028-ai-agents-will-outnumber-sellers-by-10x-yet-fewer-than-40-percent-of-sellers-will-report-ai-agents-improved-productivity).
The productive frontier of AI in sales isn't more Giver output. It's Sense Maker enablement — using AI to help sellers understand the buying group's information map faster and route the right peer at the right moment.
Why Tellers get beaten in modern B2B
Tellers had a decade of legitimacy during the Challenger era. That decade is over.
Challenger's original insight — that top sellers teach the buyer something new about their business — remains valid. The problem is that the "teach" behavior has to be delivered in a way that doesn't bump into what the buying group already believes. A hard-Teller motion runs into what psychologists call reactance. The buying group's response to "here's what you should think" is "who are you to tell me what to think?"
Modern buying groups are especially resistant to Tellers because they've done their own research. They've read the same content the Teller is drawing from. They've probably run their own AI-synthesized analysis on the same topic. When the Teller shows up with a prescriptive point of view, it lands as redundant at best and condescending at worst.
The evolution of the Challenger archetype is toward sense-making. The seller's insight becomes valuable only when it helps the buying group de-conflict what they already know — not when it replaces their thinking with the seller's.
What sense-making requires that AI can't provide
Sense-making has three requirements. AI can support two of them and can't provide the third.
Requirement 1: information map of what the buying group already knows. AI is great at this. Voice-of-customer analysis, email threading, call transcript analysis — all of it can synthesize what the buying group has said, believes, and repeated. Every RAO platform is now selling this capability. See our writeup on Revenue Action Orchestration for the market landscape.
Requirement 2: reference data on what similar buying groups did. AI is good at this too. Case studies, patterns from past deals, benchmarks — synthesized and delivered on-demand.
Requirement 3: trusted external voice at the moment of decision. AI is not good at this. It cannot be the peer who's been through the same decision, whose word is trusted by the champion, and whose validation moves the buying group from "we think" to "we're sure." That voice has to come from a human, and that human has to be someone the buying group already trusts — or can be quickly persuaded to trust.
Requirement 3 is where sense-making at scale actually gets built. Ninety-five percent of your target buyers likely know at least one of your customer champions from a prior role, from school, or from an industry community. Sense-making sellers activate that graph — routing the right peer to the right buying-group moment.
Boomerang customers running this motion see 3-5× higher meeting conversion vs. cold, 25% higher win rates on multithreaded deals, and 40-55% more deals multithreaded in stages 2-3. Those numbers aren't from doing more outreach. They're from doing sense-making at scale.
How to build a sense-making sales team
Three practical shifts.
One: shift SDR training from message frameworks to research frameworks. The Giver-era SDR was trained to write better cold email. The Sense Maker-era SDR is trained to understand the buying group's information map before writing anything. That's a different set of skills — closer to research analyst than to copywriter.
Two: instrument peer intros as a top-funnel motion, not just a stage-5 asset. Most sales orgs treat customer references as something you produce for procurement's sake in the last two weeks. Sense Maker teams treat peer intros as something they mobilize starting in stage 2, because sense-making requires the peer voice throughout the buying journey. Our writeup on warm intro orchestration covers the mechanics.
Three: measure sense-making, not activity. The traditional sales activity metrics — emails sent, calls made, meetings booked — measure Giver behavior. Sense-making needs different metrics: buying group information map completeness, peer-intro attach rate, seller-authored point-of-view artifacts. Different KPIs produce different behavior.
What the buyer data says about the next five years
Buyer preferences point straight at sense-making as the winning motion.
Sixty-nine percent of buyers turn to sales reps to validate AI-generated insights (Gartner). Seventy-five percent will prefer human interaction over AI by 2030. Sales orgs providing AI-enabled next-best-actions are 2.6× more likely to achieve commercial growth (Gartner, https://www.gartner.com/en/newsroom/press-releases/2026-05-20-gartner-survey-finds-sales-organizations-that-provide-ai-enabled-next-best-actions-are-two-point-six-times-more-likely-to-achieve-commercial-growth).
Read those together. Buyers want humans. They also want the humans to be AI-enabled. That's a specific archetype. Not the Giver. Not the Teller. The Sense Maker with an AI layer that helps them show up on time, with the right context, with the right peer routed in.
That's the seller Gartner has been describing since 2019, and it's the seller who wins in 2028.
Frequently asked questions
What is a Sense Making seller? Per Gartner (Adamson and Toman, July 2019), a Sense Maker is a seller who helps buyers rationalize and de-conflict information they've already gathered — as opposed to Givers, who provide more information, or Tellers, who prescribe what buyers should think. Sense Makers were the highest-performing archetype in Gartner's research.
How does sense-making differ from consultative selling? Consultative selling is a broad umbrella that has shifted meaning over 30 years. Sense-making is more specific: it's the behavior of understanding the buying group's existing information map first, then adding value by de-conflicting rather than adding.
Are AI SDR platforms Givers by definition? Effectively yes. Their operating model is high-volume outreach at scale, which is the industrialized version of the Giver behavior Gartner's research identified as underperforming. This doesn't mean AI has no role in sales — it means the productive AI role is Sense Maker enablement, not Giver amplification.
Why don't Tellers work anymore? Modern buying groups are informed. They've done their own research and increasingly synthesized their own AI-generated analysis. A prescriptive Teller motion runs into reactance — the buying group resists having their thinking replaced. Insight remains valuable, but only when it helps de-conflict what the buying group already believes.
Can sense-making be scaled with AI? Partially. AI can produce the information map and reference data a Sense Maker needs. It cannot provide the trusted external voice at the moment of decision — that has to come from a real peer. Sense-making at scale means AI orchestrating human trust moments, not replacing them.
What's the single biggest behavioral shift a Giver-oriented seller has to make? Stop opening with "let me tell you about us." Open with "walk me through what you've already learned." That one shift moves the seller from information-provider to information-organizer, which is the foundation of sense-making.
