BMAD-METHOD/expansion-packs/bmad-trend-insights-platform/tasks/forecast-trend.md

# Task: Forecast Trend

## Objective

Project the future trajectory of a trend over the next 6-12 months, helping users understand where it's headed and time their entry or exit accordingly.

## Instructions

### Step 1: Identify Trend and Forecast Goals

Clarify with the user:

- **Trend name**: What trend should we forecast?
- **Timeframe**: 3 months, 6 months, 12 months, or longer?
- **Decision context**: Why do they need this forecast?
  - Timing market entry?
  - Deciding whether to invest?
  - Planning content strategy?
  - Evaluating sustainability?

### Step 2: Research Historical Data

Gather trend history using web search:

#### Search Trend History

- **Past 12 months**: How has search interest evolved?
- **Year-over-year**: Comparison to previous year
- **Seasonal patterns**: Any cyclical behavior?
- **Growth rate**: What's the month-over-month or quarter-over-quarter change?
- **Peak moments**: When did interest spike? Why?

#### Market Evolution

- **Timeline**: When did this trend first emerge?
- **Adoption curve**: Where are we on the curve?
  - Innovators (2.5%)
  - Early Adopters (13.5%)
  - Early Majority (34%)
  - Late Majority (34%)
  - Laggards (16%)
- **Market growth**: How has the market size changed over time?

#### Media & Social Activity

- **Coverage trajectory**: Increasing or decreasing media attention?
- **Influencer involvement**: Growing or fading?
- **Social conversation**: Volume and sentiment over time

### Step 3: Identify Trend Drivers

Analyze what's pushing this trend:

#### Current Drivers (Why it's trending now)

1. **[Driver 1]**: [Explanation]
   - Strength: [Strong/Moderate/Weak]
   - Sustainability: [Will this continue driving it?]

2. **[Driver 2]**: [Explanation]
   - Strength: [Strong/Moderate/Weak]
   - Sustainability: [Will this continue driving it?]

3. **[Driver 3]**: [Explanation]
   - Strength: [Strong/Moderate/Weak]
   - Sustainability: [Will this continue driving it?]

#### Future Catalysts (What could accelerate it)

- **Positive catalysts**: What could drive faster growth?
- **Inflection points**: Events that could change trajectory?
- **Market expansion**: New demographics or geographies opening up?

#### Headwinds (What could slow it down)

- **Competition**: New entrants or alternatives
- **Market saturation**: Running out of addressable audience
- **Regulatory**: Potential restrictions or regulations
- **Economic**: Macro factors affecting consumer spending
- **Cultural**: Shifting preferences or values

### Step 4: Analyze Comparable Trends

Research similar past trends for pattern matching:

**Find comparable trends**:

- Similar trends from the past
- How did they evolve?
- What was their peak?
- How long did they last?
- What caused them to decline (if they did)?

**Learn from history**:

- What does this tell us about our trend?
- Are there patterns we can apply?
- Are there warning signs to watch for?

### Step 5: Build Forecast Scenarios

Create 3 scenarios with different assumptions:

```markdown
# Trend Forecast: [Trend Name]

**Forecast Period**: [Timeframe]
**Forecast Date**: [Today's date]
**Current Status**: [Current stage and metrics]

---

## 📈 Historical Context

### Trend Timeline

- **Origin**: [When/how it started]
- **Emergence**: [When it became noticeable]
- **Current Stage**: [Where we are now on adoption curve]
- **Age**: [Months/years since emergence]

### Historical Performance

**Past 12 Months**:

- Search interest: [Started at X, now at Y] = [% change]
- Market size: [If available]
- Media mentions: [Trend direction]
- Social conversation: [Trend direction]

**Key Moments**:

- **[Date]**: [Significant event and impact]
- **[Date]**: [Significant event and impact]
- **[Date]**: [Significant event and impact]

### Patterns Observed

- **Seasonality**: [Any seasonal patterns identified]
- **Growth rate**: [Average monthly/quarterly growth]
- **Volatility**: [Stable or spiky?]

---

## 🎯 Current State Assessment

### Trend Health Indicators

| Metric            | Status          | Trend                                 |
| ----------------- | --------------- | ------------------------------------- |
| Search Interest   | [High/Med/Low]  | [↗️ Rising / → Stable / ↘️ Declining] |
| Market Activity   | [High/Med/Low]  | [↗️ Rising / → Stable / ↘️ Declining] |
| Media Coverage    | [High/Med/Low]  | [↗️ Rising / → Stable / ↘️ Declining] |
| Social Engagement | [High/Med/Low]  | [↗️ Rising / → Stable / ↘️ Declining] |
| New Entrants      | [Many/Some/Few] | [↗️ Rising / → Stable / ↘️ Declining] |
| Innovation        | [High/Med/Low]  | [↗️ Rising / → Stable / ↘️ Declining] |

**Overall Health**: [🟢 Strong / 🟡 Moderate / 🔴 Weak]

### Adoption Stage

**Current Position**: [Stage on adoption curve]

- **Penetration**: [Estimated % of potential market reached]
- **Remaining runway**: [How much growth potential left]

---

## 🔮 Forecast Analysis

### Scenario 1: Bullish (30% probability)

**What happens**: [Description of optimistic scenario]

**Key assumptions**:

- [Assumption 1]
- [Assumption 2]
- [Assumption 3]

**Projected trajectory**:

- **3 months**: [Metric projections]
- **6 months**: [Metric projections]
- **12 months**: [Metric projections]

**Catalysts needed**:

1. [What needs to happen for this scenario]
2. [Another catalyst]
3. [Another catalyst]

**What this means**:

- Market size: [Projection]
- Opportunity: [How opportunity evolves]
- Competition: [How competition evolves]

---

### Scenario 2: Base Case (50% probability)

**What happens**: [Description of most likely scenario]

**Key assumptions**:

- [Assumption 1]
- [Assumption 2]
- [Assumption 3]

**Projected trajectory**:

- **3 months**: [Metric projections]
- **6 months**: [Metric projections]
- **12 months**: [Metric projections]

**Expected developments**:

1. [Expected development]
2. [Expected development]
3. [Expected development]

**What this means**:

- Market size: [Projection]
- Opportunity: [How opportunity evolves]
- Competition: [How competition evolves]

---

### Scenario 3: Bearish (20% probability)

**What happens**: [Description of pessimistic scenario]

**Key assumptions**:

- [Assumption 1]
- [Assumption 2]
- [Assumption 3]

**Projected trajectory**:

- **3 months**: [Metric projections]
- **6 months**: [Metric projections]
- **12 months**: [Metric projections]

**Warning signs**:

1. [What could trigger this scenario]
2. [Another warning sign]
3. [Another warning sign]

**What this means**:

- Market size: [Projection]
- Opportunity: [How opportunity evolves]
- Competition: [How competition evolves]

---

## 📊 Most Likely Path (Base Case Detail)

### Next 3 Months

**Expected**: [What will likely happen]

**Opportunities**:

- [Opportunity in this period]
- [Opportunity in this period]

**Risks**:

- [Risk in this period]
- [Risk in this period]

### 3-6 Months Out

**Expected**: [What will likely happen]

**Opportunities**:

- [Opportunity in this period]
- [Opportunity in this period]

**Risks**:

- [Risk in this period]
- [Risk in this period]

### 6-12 Months Out

**Expected**: [What will likely happen]

**Opportunities**:

- [Opportunity in this period]
- [Opportunity in this period]

**Risks**:

- [Risk in this period]
- [Risk in this period]

---

## ⚠️ Key Variables to Monitor

These factors will determine which scenario plays out:

1. **[Variable 1]**
   - **Current status**: [Where it stands now]
   - **Watch for**: [What to monitor]
   - **Impact**: [How it affects forecast]

2. **[Variable 2]**
   - **Current status**: [Where it stands now]
   - **Watch for**: [What to monitor]
   - **Impact**: [How it affects forecast]

3. **[Variable 3]**
   - **Current status**: [Where it stands now]
   - **Watch for**: [What to monitor]
   - **Impact**: [How it affects forecast]

---

## 🎯 Strategic Implications

### If Entering This Trend

**Timing Recommendation**: [Now / Soon / Wait]

**Rationale**: [Explanation based on forecast]

**Optimal Entry Window**: [Timeframe]

**Actions to Take**:

1. **Now**: [Immediate action]
2. **Next 3 months**: [Near-term action]
3. **Next 6 months**: [Medium-term action]

### If Already In This Trend

**Position Recommendation**: [Double down / Hold steady / Prepare to pivot / Exit]

**Rationale**: [Explanation based on forecast]

**Actions to Take**:

1. [Recommended action]
2. [Recommended action]
3. [Recommended action]

### If Considering Exit

**Exit Timing**: [Now / Soon / Can wait]

**Rationale**: [Explanation based on forecast]

**Exit Strategy**: [How to exit thoughtfully]

---

## 🔍 Comparable Trend Analysis

### Similar Historical Trends

We analyzed similar trends from the past:

**[Comparable Trend 1]**:

- **Peak**: [When it peaked]
- **Duration**: [How long it lasted]
- **Outcome**: [What happened to it]
- **Lesson**: [What this tells us about our trend]

**[Comparable Trend 2]**:
[... repeat structure ...]

### Pattern Insights

Based on these comparables:

- [Insight 1 about expected behavior]
- [Insight 2 about expected behavior]
- [Insight 3 about expected behavior]

---

## 🚨 Early Warning Indicators

Watch for these signs that the forecast is changing:

**Bullish Signals** (trend accelerating):

- ✅ [Signal indicating faster growth]
- ✅ [Another positive signal]
- ✅ [Another positive signal]

**Bearish Signals** (trend slowing):

- ⚠️ [Signal indicating slowdown]
- ⚠️ [Another warning signal]
- ⚠️ [Another warning signal]

**Inflection Signals** (trend changing direction):

- 🔄 [Signal of directional change]
- 🔄 [Another inflection signal]

---

## 💡 Bottom Line

### Summary Forecast

**Most Likely Scenario**: [Brief summary]

**Peak Expected**: [Timeframe]

**Longevity**: [How long will this trend last?]

**Opportunity Window**: [When is the best time to act?]

### Confidence Level

**Forecast Confidence**: [High / Medium / Low]

**Why**:

- [Factor affecting confidence]
- [Factor affecting confidence]
- [Factor affecting confidence]

### Final Recommendation

[Clear, actionable recommendation based on the forecast]

---

## 📅 Forecast Metadata

**Trend Analyzed**: [Trend name]
**Forecast Date**: [Today's date]
**Forecast Horizon**: [Timeframe]
**Next Review**: [When to update this forecast]
**Confidence**: [High/Medium/Low]

---

_📊 Want to compare this trend to alternatives? Use `/compare-trends`_
_🔍 Want to explore niches within this trend? Use `/niche-explorer`_
_📈 Want broader trend discovery? Use `/discover-trends`_

---

**Disclaimer**: Forecasts are educated projections based on current data and historical patterns. Reality may differ. Use this as input for decision-making, not as a guarantee of future outcomes. 🔮
```

### Step 6: Provide Decision Framework

Based on the forecast, give clear guidance:

**If forecast is bullish**: "This trend has strong momentum and runway. Consider entering now before competition intensifies."

**If forecast is bearish**: "This trend shows signs of maturity/decline. Exercise caution or look for niche opportunities within it."

**If forecast is uncertain**: "Mixed signals. Consider small tests rather than big bets. Monitor the key variables closely."

### Step 7: Offer Follow-Up

Ask if they'd like to:

- Deep-dive into the trend (`/analyze-trend`)
- Explore niche opportunities that might be more sustainable (`/niche-explorer`)
- Compare this to alternative trends (`/compare-trends`)
- Set up a forecast review reminder

## Success Criteria

✅ Historical context showing trend evolution
✅ Clear identification of trend drivers and headwinds
✅ Three distinct scenarios (bullish, base, bearish) with probabilities
✅ Specific projections for 3, 6, and 12 months
✅ Key variables to monitor identified
✅ Strategic implications and timing recommendations
✅ Honest assessment of forecast confidence
✅ Early warning indicators provided

## Tips for Accurate Forecasting

- **Use multiple data sources**: Don't rely on a single trend indicator
- **Learn from history**: Study similar past trends
- **Identify drivers**: Understand what's pushing the trend
- **Think in scenarios**: Avoid single-point predictions
- **Quantify uncertainty**: Be honest about confidence levels
- **Update regularly**: Forecasts get stale quickly

## Common Mistakes to Avoid

❌ Linear extrapolation (assuming current growth continues unchanged)
❌ Ignoring external factors (macro trends, competition, regulation)
❌ Overconfidence in predictions
❌ Not considering multiple scenarios
❌ Forgetting that trends don't last forever
❌ Missing early warning signs

---

**Remember**: Forecasting isn't about being right - it's about being prepared for different futures. The best forecasts help you make better decisions today, whatever tomorrow brings. 🔮📊