opportunity-scoring

What this skill does

# Opportunity Scoring

You evaluate product opportunities using structured scoring methods. You research customer needs, satisfaction levels, and market data yourself — do not ask the user for data they would need to look up. Only ask the user for decisions and confirmations.

This skill complements `prioritization` (which ranks items using operational frameworks like RICE/ICE) by evaluating opportunities from a **customer-needs and JTBD perspective**.

## Supported Methods

| Method | Origin | Best for |
|---|---|---|
| **Ulwick Opportunity Score** (default) | Outcome-Driven Innovation (ODI) | Finding underserved customer outcomes |
| **Opportunity-Solution Tree** | Teresa Torres / Continuous Discovery | Mapping solutions to validated opportunities |
| **Multi-Criteria Weighted Scoring** | General | Custom evaluation with organization-specific criteria |

## Input handling

Follow shared foundation S7 -- interview mode. When input is missing or insufficient, interview to gather at minimum:

| Dimension | Required | Default |
|---|---|---|
| **Product/market context** | Yes | -- |
| **Customer segment(s)** | No | Will identify from context |
| **Customer research data** (surveys, interviews, reviews) | No | Will research autonomously |
| **Existing opportunity list** | No | Will identify outcomes in Phase 3 |
| **Scoring approach** | No | Ulwick Opportunity Score |

**Exit interview when**: Product/market context is clear enough to identify customer outcomes.

## Phase 1 -- Setup

### 1. Collect input

Accept one of:
- A product or market description
- A file path to customer research, segmentation report, or opportunity list
- Pasted content (customer interviews, survey results, business case)
- No input or vague input -> enter interview mode

### 2. Detect scope

From the input (or interview results), identify:
- **Product/service**: What is being evaluated
- **Market**: Target market and segments
- **Customer data source**: Imported research or to be gathered
- **Scoring approach**: Ulwick, OST, Multi-Criteria, or combination

### 3. Confirm scope

```
**Product/service**: [name]
**Market**: [target market]
**Customer segment(s)**: [identified or to be researched]
**Customer data**: [imported / will research]
**Scoring approach**: [method(s)]
```

Ask the user to confirm or adjust. Ask diagram render mode and output path per the `diagram-rendering` and `autonomous-research` mixins.

## Phase 2 -- Research

Use WebSearch and WebFetch per the `autonomous-research` mixin.

### 2a. Customer needs research

Research customer outcomes and satisfaction signals:
- Customer forums, review sites, social media discussions
- Common complaints and feature requests
- Workaround patterns (indicating unmet needs)
- Job-to-be-done patterns in the domain

### 2b. Competitive satisfaction research

Research how well current solutions serve customer outcomes:
- Competitor feature coverage and ratings
- App store reviews and satisfaction scores
- Industry analyst reports on solution gaps
- Switching behavior and reasons

### 2c. Market opportunity data

Research market context:
- Market size and growth for relevant segments
- Emerging needs and trends
- Regulatory or technology shifts creating new outcomes

## Phase 3 -- Outcome/Opportunity Identification

### If opportunity list or customer research is provided

Import outcomes, validate JTBD framing, request clarification for ambiguous entries.

### If no opportunity list

Identify 15-30 customer outcomes using JTBD framing:

| Field | Description |
|---|---|
| **ID** | O01, O02, etc. |
| **Job Stage** | The phase of the customer's job (e.g., Define, Locate, Prepare, Execute, Monitor, Resolve) |
| **Outcome** | "When [situation], I want to [outcome], so I can [benefit]" |
| **Category** | Functional / Emotional / Social / Related job |

Group outcomes by job stage. Present for user confirmation.

**Job stages** (adapt to domain):

| Stage | Description |
|---|---|
| Define | Understanding what needs to be done |
| Locate | Finding inputs, resources, information |
| Prepare | Setting up for execution |
| Execute | Performing the core job |
| Monitor | Tracking progress and results |
| Modify | Making adjustments during execution |
| Conclude | Finishing and wrapping up |
| Resolve | Handling problems and exceptions |

## Phase 4 -- Importance Scoring

Score each outcome on importance (1-10):

| Importance level | Score | Evidence indicators |
|---|---|---|
| Critical | 9-10 | Mentioned by majority, regulatory requirement, safety-related |
| High | 7-8 | Frequently mentioned, significant pain, workarounds common |
| Medium | 5-6 | Mentioned occasionally, moderate inconvenience |
| Low | 3-4 | Rarely mentioned, minor preference |
| Minimal | 1-2 | Almost never mentioned, no evidence of need |

Evidence sources for importance:
- Frequency of mention in reviews/forums
- Survey data (if available from imports)
- Severity indicators (workarounds, complaints, churn reasons)
- Regulatory or compliance requirements
- Research findings from Phase 2

| ID | Outcome | Importance (1-10) | Evidence |
|---|---|---|---|
| O01 | [outcome statement] | [score] | [evidence summary] |

## Phase 5 -- Satisfaction Scoring

Score current satisfaction with existing solutions (1-10):

| Satisfaction level | Score | Evidence indicators |
|---|---|---|
| Very satisfied | 9-10 | Praised feature, high ratings, no complaints |
| Satisfied | 7-8 | Generally positive, minor complaints |
| Neutral | 5-6 | Mixed reviews, some workarounds |
| Dissatisfied | 3-4 | Common complaints, frequent workarounds, poor ratings |
| Very dissatisfied | 1-2 | Widespread frustration, no adequate solution exists |

Evidence sources for satisfaction:
- Competitor product ratings and reviews
- Feature-specific satisfaction signals
- Workaround prevalence (more workarounds = lower satisfaction)
- Support ticket patterns
- Research findings from Phase 2

| ID | Outcome | Satisfaction (1-10) | Current solution | Evidence |
|---|---|---|---|---|
| O01 | [outcome statement] | [score] | [how currently addressed] | [evidence summary] |

## Phase 6 -- Opportunity Score Calculation

Calculate Ulwick's Opportunity Score:

```
Opportunity Score = Importance + max(Importance - Satisfaction, 0)
```

| Score range | Classification | Interpretation |
|---|---|---|
| > 15 | Extreme opportunity | Highly important, very underserved. Rare. |
| 12-15 | Strong opportunity | High importance, significant satisfaction gap |
| 8-12 | Moderate opportunity | Worth exploring, some gap exists |
| < 8 | Low opportunity | Well-served or low importance |

Full scoring table:

| Rank | ID | Outcome | Importance | Satisfaction | Opportunity Score | Classification |
|---|---|---|---|---|---|---|
| 1 | [id] | [outcome] | [imp] | [sat] | [score] | [classification] |

**Overserved detection**: When Satisfaction > Importance, the outcome is overserved. Flag these: "Outcome [X] is overserved (Satisfaction [Y] > Importance [Z]). Current solutions exceed customer needs — competing here offers diminishing returns."

## Phase 7 -- Opportunity-Solution Tree

For the top 5-10 opportunities (highest Opportunity Scores), build an Opportunity-Solution Tree per Teresa Torres' framework:

### Tree structure

```
Desired Outcome (product goal)
  |-- Opportunity 1 (customer need/outcome)
  |     |-- Solution A
  |     |     |-- Assumption Test 1
  |     |     |-- Assumption Test 2
  |     |-- Solution B
  |     |     |-- Assumption Test 3
  |-- Opportunity 2
        |-- Solution C
        |     |-- Assumption Test 4
        |-- Solution D
```

### Per opportunity

| Field | Description |
|---|---|
| **Opportunity** | The customer outcome (from Phase 3) |
| **Opportunity Score** | From Phase 6 |
| **Solutions** (2-4 per opportunity) | Potential product solutions that address the outcome |
| **Assumption Tests** (1-3 per solution) | Cheapest experiment to validate the riskiest assumption |

### Solution generation rules