Use AI to connect content and campaign performance data to the assets that produced it so marketers can identify what headlines, offers, images, formats, and audiences are working, repurpose winners, and feed performance learnings back into the next round of creative variants and optimizations.
Marketers must interpret the insights, decide what counts as success, choose which audiences and channels matter, and determine which optimizations support the brand and business goals.
AI links performance metrics to specific headlines, images, offers, and CTAs so teams can see which creative elements are driving clicks and conversions.
Adobe GenStudio / Adobe AnalyticsAI detects when paid social creative is losing effectiveness and proposes fresh copy and asset variations for relaunch testing.
Adobe GenStudio / Meta Ads ManagerAI reviews ad-account metrics and top-performing assets to explain which hooks, formats, and offers likely drove the best results before the next production cycle.
Triple Whale / ChatGPTI help companies navigate AI adoption -- from strategy to production. Whether you are building your first LLM-powered feature or scaling an agentic system, I can help you get it right.
Design and build LLM-powered products and agentic systems
Go from idea to production with a clear implementation roadmap
Build AI with human-in-the-loop in regulated environments
Today at Cannes Lions, we unveiled Canva Grow 2.0, and with it, a new way for marketing teams to create, launch, and learn from ads – all without leaving Canva.
I don't know why more ecom founders aren't using AI to write their ad copy, landing pages, and email flows. Here's the exact workflow I use to build creatives across all my businesses:
1. Download all your customer reviews, your website, your competitors' reviews, and your top-performing advertorials. Everything goes into one place. The more raw input you give it, the better the output gets on the other side. Codex and Claude Code can build a trust pilot scraper within one prompt.
2. Run deep research with a proper prompt (e.g., “create me everything I need to know about my customer to do future marketing”). Remember that your prompts probably need to be twice as long as you think in this day and age.
3. You now have a customer doc - this is your source of truth for all future copy, so treat it like one and keep coming back to it.
4. Take that customer doc and give it the structure of the advertorial you want to write with a proper prompt, including a proper mechanism and solution mechanism.
5. Don't give it one massive prompt. My YT script prompting cycle is 14 prompts long because AI doesn't handle large blobs of data well. Give it 12 angles first, select the best ones, then prompt it with questions about what you already know about your customer, feed the answers back, and build from there.
6. Loop the results back in. The top creative in your ad account is the new input, and that performance data goes straight into the next round of prompts.
The problem with ecom used to be time. Finding products took weeks, building stores took weeks, shooting content took weeks.
But AI broke that barrier. You can now build 10 advertorials in a day, and that volume negates luck.
TLDR: Use more AI.