Value Function: The S-Shaped Curve That Explains Why Losing $100 Hurts More Than Finding $100 Feels Good

I want you to try something. Imagine you found a $50 bill on the sidewalk this morning. Feel that little rush? Good. Now imagine you lost a $50 bill out of your wallet this afternoon. Feel that sinking gut punch?

If the loss feels worse than the gain feels good (and for most of you, it will), congratulations: you've just experienced the value function in action. And this asymmetry in how humans experience gains and losses is one of the most important concepts in all of marketing, pricing, and consumer behavior.

What Is the Value Function?

The value function is the central mathematical component of prospect theory, developed by Daniel Kahneman and Amos Tversky in their landmark 1979 paper "Prospect Theory: An Analysis of Decision Under Risk." It describes how people evaluate outcomes not in terms of absolute wealth or utility, but in terms of gains and losses relative to a reference point.

The value function has three defining characteristics:

1. Reference dependence: People evaluate outcomes as gains or losses from a reference point (usually the status quo), not as absolute levels of wealth
2. Diminishing sensitivity: The difference between gaining $100 and $200 feels larger than the difference between gaining $1,100 and $1,200. Same for losses. The curve flattens as you move further from the reference point.
3. Loss aversion: Losses hurt roughly twice as much as equivalent gains feel good. The value function is steeper in the loss domain than in the gain domain.

When you plot the value function, it creates a distinctive S-shaped curve: concave (bowing outward) in the gains domain and convex (bowing inward) in the loss domain, with the loss side significantly steeper than the gain side.

This concept is closely related to reference-point dependence and framing, which are both direct applications of the value function's insights.

The Shape of the Curve: Why It Matters for Marketing

Let me break down the S-curve into its practical implications:

Kahneman himself, in his 2011 book Thinking, Fast and Slow, summarized it this way: "The concept of loss aversion is certainly the most significant contribution of psychology to behavioral economics." I think most marketers underestimate just how much of consumer behavior this single curve explains.

The Four Rules of Hedonic Framing

Richard Thaler (another Nobel laureate, and a frequent collaborator with Kahneman) formalized the value function's marketing implications into what he called the "hedonic framing" principles. These are practical rules for how to present information to maximize perceived value:

Rule 1: Segregate Gains

When you have multiple pieces of good news, deliver them separately. Each gain is experienced on the steepest part of the value function curve.

Example: Apple doesn't announce all new iPhone features at once in a single slide. They reveal each feature one by one during the keynote, letting each "gain" register independently.

Rule 2: Integrate Losses

When you have multiple pieces of bad news, deliver them together. The diminishing sensitivity to losses means the incremental pain of each additional loss shrinks when bundled.

Example: Car dealerships bundle all the fees (documentation, delivery, dealer prep) into a single line rather than itemizing them in sequence. One $2,000 hit hurts less than four separate $500 charges.

Rule 3: Integrate Smaller Losses With Larger Gains

When you have a big gain and a small loss, present them together. The gain absorbs the loss.

Example: "Your refund this year is $3,200, and the filing fee is $150." The refund is so positive that the fee barely registers. Contrast this with receiving the fee invoice separately from the refund notification.

Rule 4: Segregate Small Gains From Large Losses

When delivering a large loss, separate out any small positives. The small gain registers on the steep part of the curve, providing disproportionate relief.

Example: "We need to raise your subscription price by $40/month, but we're adding premium support at no extra charge." The price increase is painful, but the "free" support registers as a separate gain.

Real-World Marketing Applications of the Value Function

The Value Function and Pricing Strategy

I think the area where the value function has the most direct impact is pricing. Several pricing strategies on Markeview are essentially applied value function theory:

• Prestige Pricing: Works because the reference point shifts upward. A $300 wine doesn't just taste "better"; the high price resets the reference point so the experience is evaluated relative to a premium expectation.
• Price Signaling: High prices signal quality because consumers use price as a reference point for expected benefits.
• Price Elasticity: Price increases feel like losses, which the value function tells us hurt twice as much as equivalent gains. This is why demand drops more sharply with price increases than it rises with price decreases.
• Price Skimming: The initial high price sets a reference point. Subsequent price drops feel like "gains" to consumers who were waiting.

What's Changed: The Value Function in the Digital Age (2020-2026)

The value function itself hasn't changed (it's a description of human psychology, after all), but the environments in which it operates have shifted dramatically:

Dynamic pricing makes reference points unstable. When Amazon changes prices multiple times per day, the consumer's reference point becomes a moving target. Tools like Camelcamelcamel exist specifically because consumers want to anchor their reference point to a product's historical low.

Subscription fatigue is loss aversion in action. The reason people struggle to cancel subscriptions (even ones they don't use) is the value function at work. Canceling feels like a loss of access, which hurts more than the equivalent monetary gain of keeping the money. Deloitte's 2025 digital media trends report found that the average US consumer maintains 4+ streaming subscriptions, with many reporting they'd cancel "if they got around to it" but never do.

Dark patterns exploit loss aversion. "Only 2 left in stock!" "Your cart expires in 10 minutes!" These are value function manipulations, creating artificial losses that trigger disproportionate urgency. The FTC has increasingly scrutinized these tactics, issuing updated guidelines on dark patterns in 2024.

Gamification leverages the entire S-curve. Apps like Duolingo use streak mechanics that exploit loss aversion (don't break your streak!) while delivering frequent small gains (XP points, level-ups) that register on the steepest part of the gains curve.

The Value Function and the Broader Behavioral Economics Landscape

The value function doesn't exist in isolation. It connects to a web of behavioral concepts that marketers should understand:

• Loss Aversion: The steeper slope on the loss side of the value function
• Reference-Point Dependence: The foundation of the value function's starting point
• Framing: How you present information determines whether it's processed as a gain or loss
• Diminishing Marginal Value: The value function's concavity in the gains domain is a specific application of this principle
• Competitive Advantage: Companies that understand the value function can create psychological advantages that competitors with better products can't easily replicate

Thought Leaders and Key Resources

Frequently Asked Questions

What is the value function in marketing?

The value function, from Kahneman and Tversky's prospect theory, describes how consumers evaluate outcomes as gains or losses relative to a reference point, rather than as absolute values. It has an S-shaped curve that is steeper for losses than for gains, explaining why losing $100 hurts more than gaining $100 feels good.

How does the value function relate to loss aversion?

Loss aversion is a direct property of the value function. The value function is steeper in the loss domain than the gain domain, meaning the psychological pain of losing something is roughly twice the pleasure of gaining the same thing. Loss aversion is the name for this asymmetry.

What is a reference point in the value function?

A reference point is the baseline against which consumers evaluate outcomes. It's usually the status quo, but it can be influenced by expectations, past prices, competitor offerings, or marketing framing. For example, if a product "usually" costs $50, that becomes the reference point; a $40 price feels like a gain, and a $60 price feels like a loss.

How can marketers use the value function in pricing?

Marketers can frame prices as avoiding losses rather than achieving gains ("don't miss out" vs. "save money"), bundle price increases into a single change, separate value additions into multiple communications, and use free trials to create a sense of ownership that triggers loss aversion when the trial ends.

What is hedonic framing?

Hedonic framing is Richard Thaler's application of the value function to how information is presented. The four rules are: segregate gains (deliver good news separately), integrate losses (deliver bad news together), integrate small losses with large gains, and segregate small gains from large losses.

Does the value function apply to B2B decisions?

Yes. B2B buyers are still humans. Research consistently shows that loss aversion, reference-point dependence, and diminishing sensitivity affect organizational purchasing decisions, especially in complex sales where multiple stakeholders bring different reference points to the evaluation.

What is the difference between the value function and utility theory?

Traditional utility theory assumes people evaluate outcomes based on final wealth states and are consistently risk-averse. The value function, from prospect theory, shows that people evaluate outcomes relative to a reference point, are risk-averse for gains but risk-seeking for losses, and weigh losses more heavily than gains.

How do digital platforms exploit the value function?

Digital platforms use urgency cues ("only 3 left!"), streak mechanics ("don't lose your 30-day streak!"), free trial-to-paid conversions (creating ownership before asking for payment), and price anchoring (showing the "original" price next to the sale price) to manipulate reference points and trigger loss aversion.

Sources & References

1. Kahneman, D. and Tversky, A. "Prospect Theory: An Analysis of Decision under Risk." Econometrica, 1979. Link
2. Kahneman, D. Thinking, Fast and Slow. Farrar, Straus and Giroux, 2011.
3. Thaler, R. "Mental Accounting and Consumer Choice." Marketing Science, 1985. Link
4. The Decision Lab. "Prospect Theory." Link
5. Collins, J. "The Value Function." Notes on Behavioural Economics. Link
6. Ariely, D. Predictably Irrational. HarperCollins, 2008.
7. Deloitte. "Digital Media Trends." Link

Written by Conan Pesci | April 5, 2026 | Markeview.com

Markeview is a subsidiary of Green Flag Digital LLC.