Tycoon solutionAI CMO runs continuous ad creative testing cycles. Weekly: generates 10-20 copy variants (headlines, body, CTAs) for each active campaign, coordinates design asset variants with your designer (or Midjourney), ships via social/Google/LinkedIn, monitors performance, kills losers, scales winners. You review weekly, approve major changes, and spend 80% less time on ad ops.
How it runs
- Active campaign audit
AI CMO connects to social ads Manager, Google Ads, LinkedIn Campaign Manager. Catalogs every active ad: creative, audience, spend, performance (CTR, CVR, CPA, ROAS). Flags fatigued creatives (CTR declining 20%+ over 14 days), declining campaigns, and untested positioning angles.
- Variant generation
For each priority creative, AI CMO drafts 10-20 variants: different headlines (benefit-led, curiosity, pain point, specific number, question), different body copy (short vs long, feature-focused vs outcome-focused), different CTAs (action-oriented, low-commitment, urgency). Variants grounded in your voice, brand, and past high-performers.
- Asset coordination
Copy variants paired with matching visual assets. For brands running Midjourney/image generation, AI Head of Content generates 5-10 image variants per copy direction. For brands with designers, AI COO briefs the designer with the copy variants and design direction. Ad-creative-pairs queued for upload.
- Launch via ads manager
AI CMO uploads variant sets to social/Google/LinkedIn via their APIs. Each variant gets UTM tagging, audience assignment, and a 5-7 day test window with adequate budget for statistical significance. Launches ship Tuesday morning; the rest of the week is learning.
- Mid-cycle monitoring
Daily AI Data Analyst check: any variant performing 2x+ above baseline gets flagged for scale consideration; any variant performing <30% of baseline gets flagged for kill; any audience x creative combo underperforming gets diagnosed. Saves your week — you don't have to check ads manager hourly.
- End-of-cycle winner decision
Friday: AI CMO reports each test's results — variant A vs variant B vs baseline, statistical significance, CPA delta, ROAS delta. Winners recommended for 2x budget scale; losers recommended for cull; tied tests flagged for further iteration. You approve or adjust.
- Learnings archive
Every test gets archived with its hypothesis, result, and takeaway ('benefit-led headlines outperform feature-led for audience X by 40%'). This archive informs the next round of variant generation. Over 3 months you have a meaningful body of 'what works for our brand' intelligence that competitors without systematic testing don't have.
Who runs it
- hire/ai-cmo
- hire/ai-head-of-growth
- hire/ai-data-analyst
What you get
- 10-20 new ad variants launched per week across active campaigns
- Creative fatigue caught within days vs weeks
- Winning creatives identified and scaled 2-3x faster than manual testing
- ROAS improvements of 15-40% within 60 days on ongoing campaigns
- Testing discipline maintained regardless of week-to-week founder availability
- Archive of brand-specific learnings that compounds over time
- Paid spend efficiency rises as the creative portfolio sharpens