Trust and truth go hand in hand.
For decades, sales and marketing playbooks have contained strategic dishonesty: white lies, half truths, careful omissions, exaggerated or misrepresented outcomes, downplayed risks, and avoided product weaknesses and engineered competitive comparisons so our own product somehow always wins.
Then we train revenue teams to “build trust.”
Those two things are fundamentally at odds.
When sales training and playbooks are laced with strategic dishonesty, our trustworthiness is directly affected, whether or not any individual seller ever tells an outright lie or even knows the play was based on an exaggerated truth.
Modern revenue teams need a new approach, moving away from strategic dishonesty and toward strategic honesty.
Strategic honesty means giving buyers an accurate representation of the decision they are making.
That includes what the product does exceptionally well, where it has limitations, what outcomes are typical versus exceptional, where competitors may legitimately perform better, what risks exist, how those risks are mitigated, and what is required from the customer for success.
This is not simply an ethical argument, though it is that too. Behavioral science, decision science, economics, and the changing way buyers access information increasingly make strategic honesty the better revenue strategy.
Buyers Have Access to the Information Now
Strategic dishonesty worked when sellers controlled access to information.
For most of the history of B2B selling, buyers learned about a product largely through vendor collateral, demos, curated references, marketing, and whatever a salesperson chose to disclose. The seller held the information advantage, and the playbook was built around it.
Then information access changed, in stages. Review platforms like G2 gave buyers something closer to an independent account of a product's strengths and weaknesses. Comparison sites, analyst reports, and independent writers expanded that access further.
But companies could still influence a meaningful share of these channels through sponsorship, placement, SEO, cultivated reviews, and paid content. A buyer doing diligence still had to work to separate truth signals from purchased marketing.
Then came Reddit, which added a different layer. Reddit information isn't precise or universally reliable. But it tells a buyer where to sniff-test.
- Someone posts, “we had some security issues.” IT gets pulled into the evaluation.
- Someone complains about downtime or stability, and technical stakeholders know to investigate the architecture more closely.
- Someone mentions implementation took nine months instead of the promised three, and operations wants a real implementation plan before they sign anything.
Now AI has made that research dramatically faster.
Forrester's 2026 State of Business Buying research found that 94% of business buyers now use AI somewhere in the purchasing process, pulling together reviews, forum threads, analyst commentary, and comparison content in seconds instead of hours.
More information has not eliminated due diligence. It has enabled better-prepared due diligence.
Buyers increasingly know what to evaluate, what to test, which stakeholders to bring into the room, and what evidence to demand before they'll make the purchase.
Buyers Learned the Formula
Access to information has done more than teach buyers about your product.
Experienced buyers know the value proposition game.
- They know the case study is probably one of your best outcomes, not an average one.
- They recognize positioning designed to make every competitor look deficient.
- They know the ROI model contains assumptions selected to support the purchase.
- They know what happens when a risk question gets redirected into an objection-handling framework rather than a true risk discussion.
They've seen the playbook enough times to recognize the moves.
And increasingly, they have access to the same information revenue teams use to build those playbooks. Sales methodologies, positioning frameworks, competitive strategies, negotiation tactics, pricing approaches, marketing practices. None of this knowledge belongs exclusively to revenue teams anymore.
Now, a carefully constructed answer may sound persuasive to the seller while sounding evasive to the buyer.
And once you recognize the formula, you start looking for what the formula is designed to hide.
Strategic Honesty Is a Better Playbook
Strategic honesty is not a slogan. It is a specific, practical change in what gets said and when.
Take the case study. The traditional approach takes a customer who achieved 300% ROI and presents it as evidence of what the prospect should expect. Strategic honesty says instead: “This is the best result we have ever produced. It is exceptional.” Then it provides a second reference point: what customers typically achieve. This doesn't weaken the case study. It gives the buyer enough information to evaluate it accurately, which is what they were already trying to do independently.
Apply the same logic to risk. Instead of waiting for the buyer to uncover implementation risk on their own, forensic-analysis style, say it first: “Here are the biggest risks we see during implementation. Here is what we do to reduce them. Here is what we need from your team, and here is why.” Risk stops being an objection the seller is trying to overcome and becomes something buyer and seller can manage together.
The point is to give buyers an accurate picture of the decision they're making.
Sometimes that means acknowledging a limitation. Sometimes it means telling them a competitor is genuinely stronger for something they care about. And sometimes it means giving the buyer enough information to decide they shouldn't buy from you at all.
Sometimes truthful disclosure should result in the customer deciding not to buy. That's not a failure of the playbook. That's the point of it.
I've even personally seen this play out where the competitor was actually a better fit for the buyer's use case. But they still won the deal on the basis of trust and honesty. The buyer valued having a trusted partnership more than the features or product strength.
Because the other seller deployed strategic dishonesty, they lost with the superior product.
Expectations Control Customer Satisfaction
A few decades ago, I heard an expression that I embraced and have used ever since:
Happiness equals reality minus expectations. (H)=(R)-(E)
It's simple math. When your expectations are a 10 and reality is a 7, your happiness is a negative 3.
For nearly 20 years, I've used this idea when thinking about customer expectations. Product and delivery teams are always working to get the reality number up. Build a better product. Improve the service. Fix the implementation. Create better outcomes.
But revenue teams have enormous influence over the other side of the equation: the expectations we create before the customer ever buys.
When we sell on strategic dishonesty, persuasion, best-case scenarios, “no-brainer” value propositions and “risk-free” approaches, we can create the negative number ourselves. We set expectations so high that even a good customer outcome can feel disappointing compared to what they were sold.
There is behavioral research behind this relationship. Expectation-disconfirmation research has studied how expectations shape customer satisfaction, and recent research continues to support that connection.
What customers experience matters, but so does how that experience compares to what they expected.
That doesn't mean the answer is to intentionally lower expectations. The goal is to set accurate expectations. If the likely outcome is a 9, sell the 9.
If you have a customer who achieved an incredible result, talk about it. If your product can create significant value, sell that value. But don't present the best outcome you've ever produced as though it's what everyone should expect.
There is a meaningful difference between creating excitement about what is possible and misrepresenting what is probable.
The consequences of getting that wrong don't end when the contract gets signed.
- Talk with anyone in onboarding, services or customer support and they'll tell you very quickly what happens when expectations exceed reality.
- Talk with customer success and they'll tell you about the hoops and hurdles they go through trying to prevent churn when a customer is disappointed.
- Anyone in finance will tell you the economics of non-renewal, particularly when CAC payback is tracking in years. A customer who churns before you've recovered the cost to acquire them can turn the deal everyone celebrated into a financial loss.
Strategic dishonesty may help close the deal in the beginning. The unrealized expectation can still cost everyone in the end.
There Is a Behavioral Reason Buyers Care This Much About Risk
Traditional revenue value propositions are built almost entirely around gain. More revenue. More productivity. More efficiency. Faster growth. More customers. The pitch is optimized to make the upside as large and as vivid as possible.
But buyers are not only weighing potential gains.
They are running a parallel calculation about potential losses.
What if implementation fails? What if nobody adopts it? What if this disrupts something that already works? What if the promised ROI never materializes? What if I spend this budget and have to explain to my leadership why it went wrong?
That asymmetry between how sellers frame value and how buyers actually evaluate it has a name in behavioral economics: loss aversion.
The research has continued to evolve, but the core finding holds: we tend to care more about preventing a loss than achieving an equivalent gain.
That matters in sales because while sellers are busy building the biggest possible upside, buyers are also evaluating everything that could go wrong.
I’ve noted some articles at the end of this blog for anyone wanting to learn more with the Journal of Economic Literature and Economic Psychology.
Revenue teams build value propositions around maximizing perceived gain. Buyers organize a substantial part of their decision process around preventing loss. A playbook that only addresses the first leaves the second to the buyer's imagination, which tends to fill in worse outcomes than the truth would.
Every Buyer Knows Limitations Exist
Every product has limitations. Every competitor does something better. Every implementation carries risk. Every customer has responsibilities that affect the outcome, whether or not the seller says so out loud.
Experienced buyers already know this.
When a seller presents enormous upside, negligible downside, and a competitor with no meaningful strengths at all, sophisticated buyers recognize the formula immediately, and go investigate, or worse decide the company is not trustworthy.
The response is more stakeholders, more technical review, more procurement scrutiny, more requests for evidence.
Forrester's research on procurement shows the function now operates as a decision-maker, not a gatekeeper, in more than half of B2B buying cycles, and they are engaged from the earliest stages rather than brought in at the end to negotiate price.
Revenue organizations often interpret all of this as buyers becoming more difficult. A more accurate read: buyers have become less willing to accept strategic dishonesty, and they finally have the tools to act on that unwillingness.
Your Operating Teams Already Know the Risks
Here's the comedy: the truth is often less scary than what the buyer is imagining.
Operating teams usually know where things go wrong. They know what causes implementation delays, adoption problems, or poor outcomes, and they've often built processes specifically to reduce those risks.
But that knowledge rarely makes it into the sales playbook.
This is a GTM architecture problem.
Sales leaders build sales training with sales teams, often without the cross-functional input of the people who actually manage these risks. So when a buyer asks what could go wrong, the seller has been trained to downplay the risk instead of explain it.
The buyer reads the evasiveness as higher risk when the truth may be moderate risk with active mitigation.
Strategic honesty requires connecting those teams so sellers can say: “Here's how we mitigate this.”
Trust Isn't a Magic Trick
Revenue teams invest heavily in rapport, personalization, executive presence, thought leadership, social proof, customer stories, discovery frameworks, sales methodology.
All of it is designed to “build trust.”
If the underlying playbook still contains white lies, half truths, careful omissions, and avoidance of known risks, we are asking buyers to trust us while actively giving them reasons not to.
No amount of rapport-building overcomes this.
I once said on a sales call as the buyer, “I’m not saying you are personally dishonest. What I’m saying is that I don’t particularly care whether the bad information is coming from a dishonest place or an incompetence place. Neither are trustworthy.”
Strategic honesty is not complicated.
Here is where we're excellent. Here is where we're not. Here is where our competitor may genuinely be better. Here is the best outcome we've achieved. Here is what customers normally achieve. Here is where this could go wrong. Here is what we'll do to reduce that risk. Here is what we need from you for this to work.
If your product is market viable, solves a real problem, and creates meaningful value, you shouldn't need strategic dishonesty to sell it. Modern revenue teams need a new playbook, built around strategic honesty instead of strategic dishonesty.
Trust building isn't a magic trick. It's founded on being trustworthy. Trust and truth go hand in hand.
Sources & Further Reading
- Forrester, “The State Of Business Buying, 2026”
- Kahneman, D. & Tversky, A., “Prospect Theory: An Analysis of Decision under Risk,” Econometrica, 1979
- Brown, A. L., Imai, T., Vieider, F. M., & Camerer, C. F., “Meta-analysis of Empirical Estimates of Loss Aversion,” Journal of Economic Literature, 62(2), 2024
- Walasek, L., Mullett, T. L., & Stewart, N., “A meta-analysis of loss aversion in risky contexts,” Journal of Economic Psychology, 103, 2024
- Schiebler, T., Lee, N., & Brodbeck, F. C., “Expectancy-disconfirmation and consumer satisfaction: A meta-analysis,” Journal of the Academy of Marketing Science, 54(1), 2026
- Eisend, M., “Two-sided advertising: A meta-analysis,” International Journal of Research in Marketing, 23(2), 2006
