Most product pages are built once and forgotten. Someone writes a description, uploads photos, sets a price, and moves on. Months later, the page is still converting at 1% and nobody’s touched it because “it’s fine.”
The problem is that a good product page isn’t one skill. It’s copywriting, conversion rate optimization, visual design, and brand consistency all at once. No single AI prompt holds all of those disciplines in focus simultaneously.
I’ve written about the adversarial agent approach before — assembling specialized AI agents into a team, giving each one a scoring rubric, and iterating until they all agree the work is good. I recently applied this to a real Shopify product page with a four-agent team: a copywriter, a CRO specialist, a branding expert, and a visual designer. The conversion rate doubled in seven days.
Here’s how to adapt this for your own pages.
Score First, Then Build a Task List
The key adaptation for product pages is turning agent feedback into a concrete task list you can work through.
Point your agent team at the current page and have each specialist score it out of ten against their rubric. You’ll get feedback like: “6/10 — Add to Cart button blends into the background, social proof is buried below three scrolls” from the CRO agent, and “5/10 — product descriptions are feature lists, not benefit statements” from the copywriter.
Combine all of their recommendations into a single prioritized list. This is your improvement backlog. The types of changes that consistently surface across e-commerce pages:
- Primary action prominence — more contrast, higher placement on mobile, larger touch target for the CTA. Almost always the highest-impact change.
- Mobile layout — product images eating too much vertical space, pushing price and CTA below the fold.
- Benefit-oriented copy — shifting descriptions from “what this is” to “what this does for you.”
- Social proof repositioning — moving reviews and trust signals closer to the point of purchase decision.
- FAQ expansion — every unanswered objection is a reason to leave the page.
Work through the list with yourself in the loop. Don’t hand everything to the AI and walk away. Agents occasionally recommend changes that score well on their rubric but don’t fit your broader context — aggressive urgency tactics that feel off-brand, or rewrites of sections you’ve crafted for a specific reason.
After each batch of changes, re-score. You’ll see numbers climb, and you’ll see new issues surface that weren’t visible before. If you’re not familiar with the challenges of split testing, this iterative approach with agent scoring is a practical alternative — you get structured feedback without needing statistical significance on every change.
Build Features Instead of Buying Apps
One thing that came out of this process: AI agents can build small features that would normally cost $10 to $20 a month as a Shopify app.
CRO agent suggested a social proof notifications — the little popups showing recent purchases. Instead of installing an app, an AI agent wrote a script that pulls real order data from the Shopify API, stores it in metafields, and displays it with a liquid snippet. Twenty minutes of agent time, no monthly fee, no bloated JavaScript, no third-party tracking.
This works for a surprising number of app store features. Countdown timers, stock warnings, cross-sell blocks, announcement bars. If the feature is simple enough to describe, an agent can build a lightweight version that does exactly what you need. This is the same growth engineering approach I’ve been using across my marketing stack — treating your code editor as the platform instead of buying SaaS for everything.
Then Work on the Economics
A better-converting page is only half the equation. If margins are thin and average order value is low, you can’t scale paid advertising profitably.
Once conversion improvements stabilize, shift the agent team to pricing structure. Have them model bundle configurations, free shipping thresholds, COGS at different quantities, pick and pack costs, and shipping rates across weight breaks. The goal is maximizing contribution margin per order while maintaining conversion rates.
What came out of this for me was more aggressive than I would have tested on my own. The AI ran the numbers without the emotional anchoring that comes from having set the original prices yourself. No bias. Just math.
The structural changes worth considering:
- Bundle incentives inside the cart — present options the moment someone adds a product, not on a separate page.
- Tiered thresholds — make each additional item feel like an obvious deal. Free shipping at one level, a percentage off at the next.
- Higher price points — if your page is now doing its job with strong copy and visible social proof, customers may tolerate more than you assume.
Measure Patiently
Page layout changes show results fast. My conversion improvements were clear within the first week.
Avoid changing too much at the same time. It’s hard to isolate what changes were improvement and which were duds.
Give it a shot on your site – let me know how it goes.