Generative AI in Marketing: Less Hype, More Proof
Generative AI has been everywhere for two years. The sticking point: real use cases vs. buzz. Brands are also cautious after backlash. Earlier this fall, J.Crew caught heat for what consumers called "AI slop."
The takeaway is simple. Use AI to speed up the boring parts and keep humans in charge of taste, story, and final approval.
What Actually Works Right Now
- High-volume ad copy and creative variations for A/B tests across Meta, Google, and programmatic.
- Email subject lines, preheaders, and first drafts of lifecycle sequences.
- Product image cleanup, background swaps, and scene generation that still uses real product shots.
- Social captions and short scripts for Reels, Shorts, and TikTok cutdowns.
- Landing page wireframes, hero copy, and FAQ drafts based on VOC data.
- Content repurposing: turning webinars into posts, posts into threads, threads into emails.
- Localization: first-pass translations with brand voice checks.
These save time. They still need a creative lead and a QA pass. That's the difference between "useful" and "AI slop."
How to Avoid "AI Slop"
- Start with a clear creative concept. AI is the assistant, not the strategist.
- Use real product assets. Avoid fake human models and uncanny hands/faces.
- Lock a brand voice guide: tone, banned phrases, examples of "this works" and "this doesn't."
- Fact-check any claims. If legal wouldn't sign it off, don't publish it.
- Label AI-assisted content where it matters for trust.
- Run a bias and safety check, especially for audience targeting and imagery.
A Simple Workflow You Can Run This Week
- Brief: objective, audience, single KPI, constraints, past winners.
- Prompt template: voice, structure, CTA, length, variants, negatives to avoid.
- Generate: 20-50 variants per channel. Keep the top 10 by human judgment.
- QA checklist: brand voice, claims, compliance, image artifacts, readability.
- Test: ship 3-5 variants per channel with clean naming and tracking.
- Review: kill the bottom half fast, scale the winners, and log learnings.
Prompt Structure That Delivers
- Role and goal: "You're a performance copywriter. Goal: increase CTR for X audience."
- Voice rules: tone, banned terms, reading level, brand phrases to include.
- Format: character counts, line breaks, CTA placement, UTM notes.
- Inputs: product benefit bullets, pain points, proof (testimonials, stats), offer.
- Output: number of variants, diversity requirement, and a short rationale for each.
Metrics That Matter
- Time to first concept (hours to minutes).
- Cost per asset and assets per hour.
- CTR and CVR lift per channel.
- CPA change on scaled winners.
- Quality score: editor pass rate and brand-voice adherence.
Team Roles (Lean Setup)
- Creative lead: sets the concept and final call.
- Prompt strategist: builds templates and libraries.
- Editor: voice, clarity, compliance.
- Analyst: test design, readouts, and next steps.
7-Day Pilot Plan
- Day 1: Pick one channel, one product, one KPI. Pull past winning creatives.
- Day 2: Build a one-page voice guide with do/don't examples.
- Day 3: Create prompt templates for copy and images.
- Day 4: Generate 50 variants. Shortlist 10. QA them.
- Day 5: Legal/compliance pass. Final polish.
- Day 6: Launch split test with clean naming and UTMs.
- Day 7: Report results. Keep what worked. Kill what didn't. Plan iteration.
Compliance and Trust
Don't overclaim what AI can do. Keep records of how content was made. If you're exploring provenance and labeling, this spec is worth a look: C2PA. For advertising claims and AI language, see the FTC's guidance: Keep your AI claims in check.
Where to Skill Up (Fast)
If you want ready-to-use prompt templates, workflows, and testing checklists for marketing teams, these resources can help:
Bottom Line
AI is a force multiplier for production, not a substitute for taste. Use it to create more bets, faster. Let your team decide what's worth shipping. Test hard, learn fast, and protect the brand while you scale output.
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