skillshare at a glance
Latest daily volume: 793 (as of 2026-11-12) · Locale: EN-US
- vs ~7 days earlier: 17.7%
- vs ~30 days earlier: -16.7%
- vs ~1 year earlier: -50.5%
Topic groups: Online Learning & Education
- In the 12 months to Nov 12, 2026,
skillshareaveraged 1,147 Google searches a day in the United States. - The busiest day was Sep 21, 2026, with 6,098 searches, 5.3× the daily average.
- The 30 days to Nov 12, 2026 had 22,783 searches, down 22% from the 30 days before (29,244).
- Monday is the strongest day of the week, averaging 1,330 searches, 16% above the average day.
- The 45-day forecast expects about 756 searches a day, close to the last 30 days' average.
Every figure is calculated from this keyword's daily Google search volume series. API access is available for subscribers. Check another keyword with the free keyword search volume checker.
Overview
Track interest in skillshare with precise daily data for the United States. Yesterday’s daily search volume was 793, contributing to a rolling average monthly demand of 53,459. The most recent data point is 2026-11-12. Use these benchmarks to plan campaigns, calibrate budgets, and monitor market momentum; benchmark competitors, forecast demand, and optimize.
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Why Is skillshare So Popular?
skillshare most commonly refers to the Skillshare online learning platform: a subscription-based service offering project-led classes across creative, business, and tech topics. In broader use, it can describe peer-to-peer skill sharing in communities or programs named Skillshare.” Searchers display mixed intent: predominantly navigational (brand), plus commercial (pricing, free trial, teams) and informational (courses, reviews).
- Online learning platform: Streamed classes, project workflows, community feedback, and a Teams plan for organizations.
- Generic concept: Local “skill share” initiatives or library/community programs where people teach and learn from peers.
- Applications: Learning design, illustration, photography, writing, productivity, and business skills; onboarding teams; building portfolios through project assignments.
Search Volume Trends
The daily time series typically shows short-term volatility around a stable monthly baseline. Expect recognizable seasonality for learning platforms: New Year goal-setting in Q1, late-summer/back-to-school interest, and promotional peaks during November sales. Campaigns (e.g., influencer videos, email pushes) can trigger 24–72 hour surges that the daily graph surfaces immediately.
- Seasonality: Q1 resolutions, August–September study season, and holiday deal cycles.
- Day-of-week effects: Work-driven queries often concentrate on Monday–Tuesday, with softer weekends.
- Campaign-driven bursts: Sponsored creator content, pricing tests, or app/product updates can create sharp, short-lived spikes.
- Competitive interplay: Interest can lift when rivals run discounts or comparison content trends.
How to Use This Data
Daily granularity turns broad demand into actionable timing. Use it to prioritize topics, schedule launches, and align budgets to when intent is strongest.
For Marketing Agencies and Content Creators
- Time content drops and ads to rising daily curves; shift spend within 24–48 hours when momentum accelerates.
- Prioritize classes/topics that correlate with recent spikes; repurpose creative that rode prior surges.
- Set guardrails: pause/trim when daily demand dips below threshold; reallocate to adjacent keywords capturing overflow.
For DTC Brands
- Treat
skillsharedemand as a proxy for creative-hobby learning intent; schedule partnerships, sponsorships, or promo bundles accordingly. - Adapt SEM bids and affiliate budgets to day-level swings; defend your brand terms when category interest rises.
- Staff support and inventory for trial surges during seasonal peaks and major promotions.
For Stock Traders
- Use daily interest as alternative data for the online learning/creator economy; watch for inflections before news or earnings for listed peers.
- Cross-check with web traffic, app rankings, and social mentions to validate demand shifts.
- Track divergence versus peer platforms to gauge category rotation and sentiment.
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