home / skills / flpbalada / my-opencode-config / loss-aversion-psychology

loss-aversion-psychology skill

This skill helps you apply loss aversion principles to retention, pricing, and onboarding to nudge users toward desired actions.

npx playbooks add skill flpbalada/my-opencode-config --skill loss-aversion-psychology

Review the files below or copy the command above to add this skill to your agents.

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---
name: loss-aversion-psychology
description:
  Leverage loss aversion in product design and messaging. Use when designing
  retention features, pricing strategies, onboarding flows, or any experience
  where framing around potential loss can drive behavior.
---

# Loss Aversion Psychology - Losses Loom Larger Than Gains

Loss Aversion is a cognitive bias discovered by Daniel Kahneman and Amos Tversky
showing that people feel losses approximately twice as strongly as equivalent
gains. This asymmetry profoundly influences decision-making and behavior.

## When to Use This Skill

- Designing retention and anti-churn features
- Crafting pricing and upgrade messaging
- Creating urgency in conversion funnels
- Building streak and progress features
- Writing copy for landing pages
- Framing feature benefits

## Core Concepts

### The 2:1 Ratio

```
        Psychological Impact
              ^
              |         Gains
              |        /
              |      /
     +--------|----/---------> Value
              |  /
           Loss|/
              |
              |  The loss curve is ~2x steeper
              v
```

A $100 loss feels as bad as a $200 gain feels good.

### Prospect Theory Framework

| Concept              | Description                      | Example                      |
| -------------------- | -------------------------------- | ---------------------------- |
| **Reference Point**  | Current state as baseline        | "You currently have X"       |
| **Loss Frame**       | Emphasis on what could be lost   | "Don't lose your progress"   |
| **Gain Frame**       | Emphasis on what could be gained | "Get 50% more"               |
| **Endowment Effect** | Valuing owned things higher      | Free trial creates ownership |

### When Loss Framing Works Best

| Situation                 | Loss Frame Effective? |
| ------------------------- | --------------------- |
| High stakes decisions     | Yes                   |
| Preventing bad outcomes   | Yes                   |
| Risk-averse audiences     | Yes                   |
| Building habits           | Yes                   |
| Low-involvement decisions | Less effective        |
| Exploratory behavior      | Less effective        |

## Analysis Framework

### Step 1: Identify Loss Opportunities

Map user journey for potential loss frames:

| Stage   | What User Has      | Potential Loss  |
| ------- | ------------------ | --------------- |
| Trial   | Access to features | Losing access   |
| Active  | Progress/data      | Losing progress |
| At-risk | Streak/status      | Breaking streak |
| Churned | History/investment | Losing history  |

### Step 2: Choose Frame Appropriately

```
Decision: Frame as loss or gain?

Consider:
├── User relationship stage
│   └── New users: Gains more welcoming
│   └── Existing users: Losses more motivating
├── Action reversibility
│   └── Reversible: Lighter touch OK
│   └── Irreversible: Loss frame powerful
└── Ethical considerations
    └── Does this genuinely help the user?
```

### Step 3: Implement Ethically

| Approach                 | Ethical          | Manipulative       |
| ------------------------ | ---------------- | ------------------ |
| "Your streak will reset" | Honest reminder  | Manufactured guilt |
| "Unused credits expire"  | Clear policy     | Hidden deadline    |
| "Limited time offer"     | Genuine scarcity | Fake urgency       |

## Output Template

```markdown
## Loss Aversion Analysis

**Feature/Message:** [Name] **Date:** [Date]

### Current Framing

**As gain:** [Current copy/design] **User response:** [Current metrics]

### Loss Frame Opportunity

**What user has:** [Established value] **Potential loss:** [What could be lost]
**Loss frame version:** [Proposed copy/design]

### Ethical Check

- [ ] User genuinely benefits from taking action
- [ ] Loss is real, not manufactured
- [ ] Messaging is honest and transparent
- [ ] Would we be comfortable if users knew the psychology?

### Implementation Plan

| Element  | Current   | Proposed | Expected Impact |
| -------- | --------- | -------- | --------------- |
| [Copy 1] | [Text]    | [Text]   | [Estimate]      |
| [Design] | [Current] | [Change] | [Estimate]      |
```

## Real-World Examples

### Example 1: Duolingo Streaks

**Mechanism**: Users build daily learning streaks **Loss frame**: "Don't lose
your 47-day streak!" **Psychology**:

- Streak = accumulated investment (endowment)
- Breaking it = losing days of effort
- Effect: 2x stronger than "Build a 48-day streak!"

### Example 2: LinkedIn Profile Completion

**Gain frame**: "Complete your profile to get more views" **Loss frame**:
"You're missing out on 40% more profile views"

The loss frame outperforms because it highlights what you're currently losing.

### Example 3: Trial Expiration

**Weak**: "Your trial ends tomorrow" **Strong**: "Tomorrow you'll lose access
to:

- 47 saved projects
- 12 team members
- All your custom settings"

Making the loss concrete and specific amplifies the effect.

## Ethical Guidelines

### Do

- Use loss framing for genuinely beneficial actions
- Be honest about what's at stake
- Give users real control and options
- Balance loss frames with positive experiences
- Test that users feel good after taking action

### Avoid

- Manufacturing fake urgency or scarcity
- Guilt-tripping for engagement metrics
- Hiding information to create loss anxiety
- Using loss aversion on vulnerable users
- Dark patterns that exploit psychology

### The Ethics Test

Ask: "If users knew exactly how this works psychologically, would they:

1. Thank us for the helpful reminder?
2. Feel manipulated and resentful?"

If (2), reconsider the approach.

## Best Practices

### Effective Loss Messaging

| Element         | Example                                         |
| --------------- | ----------------------------------------------- |
| **Specific**    | "Lose your 23 saved items" not "Lose your data" |
| **Immediate**   | "Expires tonight" not "Expires soon"            |
| **Personal**    | "Your progress" not "Progress"                  |
| **Recoverable** | Show how to prevent the loss                    |

### Timing Matters

| Timing     | Effectiveness             |
| ---------- | ------------------------- |
| Too early  | Feels irrelevant, ignored |
| Just right | Motivates action          |
| Too late   | Creates resentment        |
| After loss | Recovery opportunity      |

## Integration with Other Methods

| Method                     | Combined Use                            |
| -------------------------- | --------------------------------------- |
| **Hooked Model**           | Investment phase creates loss potential |
| **Fogg Behavior Model**    | Loss increases motivation               |
| **Cognitive Biases**       | Combine with other biases carefully     |
| **Progressive Disclosure** | Reveal loss implications gradually      |

## Resources

- [Thinking, Fast and Slow - Daniel Kahneman](https://www.amazon.com/Thinking-Fast-Slow-Daniel-Kahneman/dp/0374533555)
- [Predictably Irrational - Dan Ariely](https://www.amazon.com/Predictably-Irrational-Hidden-Forces-Decisions/dp/0061353248)
- [Prospect Theory Original Paper - Kahneman & Tversky](https://www.jstor.org/stable/1914185)

Overview

This skill teaches how to leverage loss aversion—people feeling losses roughly twice as strongly as equivalent gains—in product design and messaging. It explains where and when loss framing moves behavior, and provides an ethical framework, templates, and implementation guidance. Use it to turn existing user value into protective, motivating messages without resorting to manipulation.

How this skill works

The skill analyzes user journeys to identify what users already own (access, progress, streaks, settings) and reframes options as potential losses rather than only gains. It guides selection of loss vs gain frames by user stage, action reversibility, and ethical impact. Concrete copy patterns, timing recommendations, and an implementation checklist help teams test and ship loss-framed interventions responsibly.

When to use it

Designing retention, anti-churn, or re-engagement flows
Crafting pricing, upgrade, or downgrade messaging
Creating urgency in conversion funnels or time-limited offers
Building streaks, progress bars, and habit-forming features
Onboarding where establishing ownership (endowment) increases commitment

Best practices

Identify genuine user value before framing it as a potential loss
Be specific and concrete (e.g., number of saved items, days of streak)
Time messages so they’re relevant—too early is ignored, too late breeds resentment
Keep loss recoverable: show clear actions to prevent or reverse loss
Avoid manufactured scarcity, hidden deadlines, or guilt-based triggers

Example use cases

Trial expiration: show precisely which saved items, projects, or settings will be lost and how to keep them
Streaks and habits: remind users they’ll “lose X days” of progress rather than only promising future gains
Pricing upgrade: highlight features the user currently enjoys that will be removed on downgrade
Onboarding: emphasize the personal data or progress at stake if setup isn’t completed
Reactivation: tell lapsed users what current benefits they’re missing out on now

FAQ

Is loss framing manipulative by default?

No. When used transparently to help users avoid real, clear harms or loss of their own value, it’s ethical. It becomes manipulative when scarcity or consequences are fabricated or hidden.

When should I prefer gain framing?

Prefer gain framing for new users, exploratory contexts, low-stakes actions, or when the action builds trust. Use loss framing for existing users with invested value or when preventing real negative outcomes is the goal.