Analyzes how your campaigns perform across mobile, desktop, and tablet. Identifies where device performance diverges significantly and recommends bid adjustments, campaign splits, or creative/landing page changes to capture the gap. Platform: Google and Meta.
git clone https://github.com/irinabuht12-oss/marketing-skills.git--- name: device-performance-split description: Analyzes how your campaigns perform across mobile, desktop, and tablet. Identifies where device performance diverges significantly and recommends bid adjustments, campaign splits, or creative/landing page changes to capture the gap. Platform: Google and Meta. metadata: platform: Google and Meta --- # 25/ Device Performance Split — Google + Meta ## What it does Analyzes how your campaigns perform across mobile, desktop, and tablet. Identifies where device performance diverges significantly and recommends bid adjustments, campaign splits, or creative/landing page changes to capture the gap. ## How it works Claude segments all your campaign data by device type and compares CPA, CVR, CTR, bounce rate, and average order value. It identifies campaigns where one device significantly outperforms or underperforms others, then determines whether the issue is ad-side (creative not working on mobile), landing-page-side (poor mobile experience), or audience-side (different intent by device). ## Practical example Your B2B lead gen campaigns show desktop CPA at $41 with 3.8% CVR and mobile CPA at $78 with 1.6% CVR. But mobile accounts for 58% of clicks because that's where the impressions are. Claude digs deeper and finds the landing page form has 9 fields that are painful on mobile, and the page load time on mobile is 4.2 seconds vs 1.8 on desktop. Recommendation: create a simplified mobile form (3 fields), fix mobile page speed, and reduce mobile bid adjustments by 25% until the fixes are live to stop the bleeding. ## What you get back - Device performance comparison across all campaigns with key metrics - Campaigns with the largest device performance gaps flagged - Root cause analysis: is the gap from creative, landing page, or audience differences - Bid adjustment recommendations by device per campaign - Campaign split recommendations for cases where devices need completely different strategies ## When to use it - When CPA is higher than expected and you haven't checked device splits - After landing page redesigns to verify mobile experience didn't break - When mobile traffic share increases but conversions don't follow - For ecommerce accounts where mobile browsing vs desktop purchasing creates attribution confusion ## Data access (Ryze MCP) This skill works best with live account data. Connect the free Ryze MCP once and Claude reads your Google Ads, Meta Ads, GA4 and Search Console directly: - claude.ai / Claude Desktop: Settings → Connectors → Add custom connector → `https://connector.get-ryze.ai/mcp` - Claude Code: `claude mcp add ryze --transport http https://connector.get-ryze.ai/mcp` - Cursor: Settings → MCP → add the same URL Setup guide: https://www.get-ryze.ai/how-to-connect-claude-to-google-meta-ads-mcp
1. **Gather Data:** Export device-level performance reports from Google Ads or Meta Ads Manager for the [TIME_PERIOD]. Include metrics like CTR, conversion rate, CPA, ROAS, and spend. 2. **Set Thresholds:** Define your [THRESHOLD_PERCENT] (e.g., 15%) to identify significant performance gaps. Use [PRIMARY_METRIC] (e.g., ROAS or CPA) to prioritize actions. 3. **Run the Analysis:** Paste the prompt into your AI tool and replace [PLACEHOLDERS] with your campaign data. For advanced users, use tools like Google Looker Studio or Meta Ads Manager’s API to automate data extraction. 4. **Implement Changes:** Apply bid adjustments in your ad platform (e.g., Google Ads’ device bid adjustments or Meta’s Advantage+ placements). For campaign splits or creative changes, use your ad platform’s bulk editing tools or a tool like AdCreative.ai. 5. **Monitor & Iterate:** Track performance weekly. Use the AI’s recommendations to refine bids, creatives, or landing pages. Re-run the analysis monthly to catch new gaps. **Tips:** - For large accounts, focus on top-performing campaigns first. Use the AI’s output to create A/B tests (e.g., desktop vs. mobile landing pages). - Combine this skill with audience segmentation (e.g., device + demographic splits) for deeper insights. - If using Meta, leverage Advantage+ placements to let the algorithm optimize for device performance automatically.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/irinabuht12-oss/marketing-skills/tree/main/skills/device-performance-splitCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Analyze the performance of [CAMPAIGN_NAME] across devices (mobile, desktop, tablet) for the last [TIME_PERIOD]. Flag any device where performance (CTR, conversion rate, CPA, ROAS) deviates by more than [THRESHOLD_PERCENT]% from the account average. For each underperforming device, recommend specific actions: bid adjustments (±[BID_ADJUSTMENT_RANGE]%), campaign splits, or creative/landing page optimizations. Prioritize recommendations by potential impact on [PRIMARY_METRIC]. Include a summary table with current vs. recommended device-level metrics.
### Device Performance Analysis for 'Summer Sale 2024' (Last 30 Days) **Current Performance by Device:** - **Mobile:** 6.2% CTR, 3.8% conversion rate, $42 CPA, 4.1x ROAS - **Desktop:** 4.1% CTR, 2.9% conversion rate, $58 CPA, 3.2x ROAS - **Tablet:** 5.0% CTR, 3.5% conversion rate, $51 CPA, 3.6x ROAS **Key Findings:** Mobile outperforms desktop by 51% in CTR and 31% in conversion rate, yet its CPA is 28% lower than desktop. Tablet performance is mid-tier but closer to mobile than desktop. The most significant gap is in **desktop CPA ($58 vs. $42 mobile)**, which is 38% higher than the account average ($45). **Recommended Actions:** 1. **Bid Adjustments:** - **Desktop:** Reduce bids by 15–20% to align with mobile efficiency. Current desktop bids are likely over-optimized for volume rather than profitability. - **Tablet:** Increase bids by 5–10% to capture more high-intent traffic, as tablet CTR and conversion rates are trending upward. 2. **Campaign Splits:** - Create a **desktop-only campaign** with tailored creatives (e.g., longer-form videos, detailed product comparisons) to test if higher-intent users respond better to educational content. - Split mobile traffic into a separate campaign with simplified landing pages and faster load times to further improve conversion rates. 3. **Creative/Landing Page Optimizations:** - **Desktop:** Test landing pages with fewer distractions and clearer CTAs (e.g., 'Buy Now' buttons above the fold). Desktop users may prefer direct paths to purchase. - **Tablet:** Optimize images for larger screens and add interactive elements (e.g., product zoom) to leverage tablet’s tactile advantage. **Projected Impact:** Applying these changes could reduce desktop CPA by 12–18% while increasing tablet ROAS by 8–12%. Mobile performance is already strong, so focus on closing the desktop gap first. **Summary Table:** | Device | Current CPA | Recommended CPA | Current ROAS | Recommended ROAS | Action Priority | |----------|-------------|-----------------|--------------|------------------|-----------------| | Mobile | $42 | $40 | 4.1x | 4.3x | High | | Desktop | $58 | $49 | 3.2x | 3.8x | Critical | | Tablet | $51 | $47 | 3.6x | 3.9x | Medium |
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