Seasonal Content Planning

Plan content around seasonal search trends

Use historical Search Console data to identify seasonal traffic patterns across your site, then build workflows that recommend which pages to refresh, create, or promote ahead of each seasonal peak.

Seasonal Demand Planner· running
Plan our Q4 holiday content - which pages need refreshing first?
read_search_console-Loaded 3-year query × URL history (1,247 pages)
decompose_seasonality-STL decomposition · isolated Q4 amplitude per URL
compute_lead_time-Modeled re-index lag · 9-14 days median
project_demand-47 seasonal URLs · 4 missing pages · ranked by lift potential
Build a 12-week ship plan that maximizes Q4 capture.
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SerpAPISearch ConsoleAI Overview & Snippet Capt…
Claude Sonnet
AI-generated answers can be wrong or incomplete. Verify anything important before you rely on it.

Illustrative preview - actual platform experience may differ.

How it works

How it works

Historical data meets forward planning for seasonal SEO.

01

Analyze historical patterns

Search Console data reveals which pages and queries see seasonal spikes. Workflows identify recurring traffic patterns across your content.

02

Plan ahead of peaks

The AI recommends which pages to refresh before each seasonal peak, which new content to create, and when to start preparing.

03

Execute with timing

Run pre-season refresh workflows on the pages that matter most. Give Google time to re-index updated content before demand surges.

Capabilities

What you can do

Seasonal pattern detection

Workflows analyze historical Search Console data to identify pages and queries with recurring seasonal traffic spikes. See which content follows predictable cycles.

Pre-peak refresh planning

The AI recommends which pages to refresh before each seasonal peak, giving your team time to update content and give Google time to re-index before demand surges.

New content opportunity identification

Identify seasonal queries where you have no existing content. Plan new pages ahead of upcoming peaks rather than scrambling when traffic is already rising.

Historical trend analysis

Compare performance across multiple seasonal cycles to understand whether your seasonal content is gaining or losing ground year over year.

Segment-level seasonal insights

Analyze seasonal patterns by site section or content type. Discover that your blog peaks in January while product pages peak in November, and plan accordingly.

Timing recommendations

Ask the AI to recommend when to start preparing for each seasonal peak - factoring in content production timelines and Google's re-indexing schedule.

FAQ

Frequently asked questions

How does Morrison detect seasonal patterns?

Morrison workflows analyze historical Search Console data to find pages and queries with recurring traffic spikes. By looking at multiple years of data, it identifies which content follows predictable seasonal cycles – holidays, industry events, tax seasons, and more.

How far ahead should I plan for seasonal content?

The ideal lead time depends on your content production cycle and how quickly Google re-indexes your pages. Most teams benefit from starting seasonal content refreshes 4-8 weeks before expected demand peaks, giving search engines time to discover and rank updated pages.

Can Morrison predict future seasonal trends?

Morrison identifies historical patterns rather than predicting new trends. If a page has spiked every November for three years, it's likely to do so again. This pattern-based approach is more reliable than trend forecasting for planning purposes.

Closed Beta

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Morrison helps your team manage and optimize content at scale. Join the waitlist to get early access.

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