Your product has seasonal usage patterns with predictable dips
If usage dips predictably (holidays, summer, end of quarter), run a campaign specifically designed to maintain engagement during that period.
When to use
Your product has predictable seasonal usage dips.
Hypothesis template
If we run a [seasonal campaign] during [slow period], usage decline will be [target]% less because we proactively combat the predictable dip.
Method
The problem: Every December, summer, or end-of-quarter, your metrics dip because users are busy with other priorities.
How to do it:
- Identify your seasonal dips from historical data
- 2 weeks before the dip, launch a campaign: challenge, retrospective, or planning prompt
- Examples:
- December: "Year in review - your growth experiments recap"
- Summer: "Summer experiment challenge - run 3 experiments in 3 weeks"
- Q4: "Plan your Q1 growth experiments now"
- Send 2-3 emails during the campaign
- Offer a small incentive for participation
- Track: engagement during campaign vs same period last year
Key insight: Seasonal dips are predictable and preventable. A proactive campaign during the expected dip period can reduce the decline by 30-50%.
Success metrics
- •Usage during campaign vs same period prior year
- •Campaign participation rate
- •Churn during slow period
- •Feature engagement during campaign
Prerequisites
- Historical data showing seasonal patterns
- A campaign theme relevant to the season
- Email and in-app notification capability
Common pitfalls
- •Running the campaign too late (start 2 weeks before the dip)
- •Making it feel forced
- •Running the same campaign every time
- •Not tracking against historical baselines
Source: Spotify Wrapped, GitHub Skyline. Seasonal campaigns reduce predictable usage dips by 30-50%.
Suggested ICE scores
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