# Trend Log — Quality Checklist and Performance Tracker

## Part 1 — Trend Adaptation Quality Checklist

Use before creating trend content to verify the adaptation is worth executing.

### Category 1 — Trend Timing (4 items)
- [ ] Trend discovery timing documented (Day 1 / 2 / 3 / etc.)
- [ ] Current use count checked (under 500k preferred)
- [ ] Trend not yet saturated in your specific product niche
- [ ] Production and posting deadline set to catch the window

**Score — __ / 4**

### Category 2 — Relevance Assessment (5 items)
- [ ] Genuine product connection identified (not forced)
- [ ] Audio emotional tone matches brand/product message
- [ ] Trend is appropriate for your brand (no sensitive associations)
- [ ] Target audience is using this trend (not just unrelated demographics)
- [ ] Product appears naturally — not as an obvious ad within a trend

**Score — __ / 5**

### Category 3 — Adaptation Brief Completeness (6 items)
- [ ] Trend mechanics understood (setup, payoff, why it works)
- [ ] Product connection point clearly stated
- [ ] Script or shot list written before filming
- [ ] Hook written (first 3 seconds specifically planned)
- [ ] CTA included in the brief
- [ ] Production notes provided (setting, lighting, filming style)

**Score — __ / 6**

### Category 4 — Production Standards (4 items)
- [ ] Multiple hook variants planned (2–3 options)
- [ ] Text overlays planned for accessibility (watching without sound)
- [ ] Audio timing mapped (key beat or moment identified for visual match)
- [ ] Native/UGC quality planned (not over-produced for a trend format)

**Score — __ / 4**

**Total pre-production score — __ / 19**
- **17–19**: Good to proceed
- **13–16**: Address flagged items first
- **Below 13**: Reconsider whether to participate in this trend

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## Part 2 — Trend Performance Log

Record each trend participation for pattern learning over time.

| # | Date Posted | Trend Name/Audio | Format Type | Product | Timing (Day X of trend) | Uses Count When Posted | Views at 24h | Views at 7 days | Hook Rate | Completion Rate | Comments | Result vs. Baseline |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 001 | [Date] | [Audio/format name] | [POV/GRWM/Audio/etc.] | [Product] | Day [X] | [Uses count] | [Views] | [Views] | [%] | [%] | [Count] | [+/-% vs. avg] |
| 002 | | | | | | | | | | | | |
| 003 | | | | | | | | | | | | |
| 004 | | | | | | | | | | | | |
| 005 | | | | | | | | | | | | |

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## Part 3 — Pattern Learnings

### Timing Learnings
- What day of trend are you consistently posting? ___
- At what day do results start declining? ___
- Your optimal adoption window based on data — ___

### Format Type Learnings
- Best performing format types for your product — ___
- Worst performing format types — ___
- Format types not yet tested — ___

### Product Fit Learnings
- Which product benefits work best as trend punchlines? ___
- Which trends felt forced and underperformed? ___
- Which trend formats produced comments vs. silent views? ___

### Audio Tone Learnings
- Audio tones that match your brand well — ___
- Audio tones that created dissonance — ___

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## Part 4 — Trend Adaptation Decisions Log

Record decisions to skip trends and the reasoning — helps build instinct for fit vs. mismatch.

| Date | Trend Considered | Reason Skipped | Was the skip correct? (Review after 1 week) |
|---|---|---|---|
| [Date] | [Trend] | [Poor fit / saturated / timing / brand safety] | [Yes/No — did skipping the trend prove right?] |

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## Part 5 — Trend Source Performance

Track which discovery sources identify trends earliest for your niche.

| Source | How often it found early trends first | Notes |
|---|---|---|
| FYP personal observation | [Frequency] | [How early relative to other sources] |
| TikTok Creative Center | [Frequency] | [Usually lags 24–48h] |
| Competitor monitoring | [Frequency] | [Which competitors move fastest?] |
| Creator alerts (followed accounts) | [Frequency] | [Which creators are best early signals?] |

Use this over time to prioritize your trend monitoring effort on the highest-yield sources.