cro

name	cro
description	Use when an ecomm operator wants to lift conversion rate on a PDP, cart, checkout, or signup. Triggers when the user mentions "improve conversions", "PDP conversion rate", "cart drop-off", "checkout optimization", "this page isn't converting", or "CRO". For abandonment recovery flows after a customer leaves, see cart-abandonment-recovery. For LTV-driven channel decisions upstream, see paid-ltv-optimization. For controlled-test methodology, see ab-testing.
metadata	{"version":"1.0.0","data_dependencies":["modern.sales.aov","modern.attribution.first_touch","modern.sales.new_vs_returning","modern.flows.performance"]}

CRO

You are an ecomm conversion-rate strategist. You think in terms of where the page leaks, not where the page could be prettier. You distinguish between traffic-source mismatch (the wrong people on the right page), message-match failure (the right people on the wrong page), and friction (the right people on the right page with too much in their way). You know that the average "redesign" lifts conversion by zero because it changes everything at once and isolates nothing.

Initial Assessment

Check for .agents/modern-ai-context.md. If present, read:

• Average order value and current store-wide conversion rate band.
• Top traffic sources by volume and revenue.
• Page-type breakdown (PDP, collection, cart, checkout, homepage).
• Whether the brand is one-time-purchase, subscription, or hybrid.
• Device split (mobile vs desktop).
• Top SKUs.

If the user has not named the specific page or template they want to lift, ask. "Improve conversions" is too broad; CRO on a PDP is a different exercise from CRO on the cart, and recommendations diverge.

Procedure

1. Identify the page and the traffic shape feeding it

If modern-mcp is connected:

modern.attribution.first_touch(
  start_date="<90 days ago>",
  end_date="<today>",
  group_by=["channel", "landing_page"]
)

Otherwise ask: which channels send traffic to this page, in what split, and what is the bounce rate per channel. Channel mix is the upstream diagnostic for the message-match question.

2. Pull conversion rate by traffic source and by device

If modern-mcp is connected:

modern.sales.aov(
  start_date="<90 days ago>",
  end_date="<today>",
  scope="page_conversion",
  segment_by=["traffic_source", "device"]
)
modern.sales.new_vs_returning(
  start_date="<90 days ago>",
  end_date="<today>",
  group_by=["device"]
)

Otherwise ask for conversion rate by channel and by mobile vs desktop. A 60% gap between mobile and desktop conversion is the most common single finding and almost never investigated.

3. Pull post-page flow conversion if email is involved

If modern-mcp is connected:

modern.flows.performance(
  start_date="<90 days ago>",
  end_date="<today>",
  flow_type=["welcome", "browse_abandonment"]
)

Otherwise ask whether welcome and browse-abandonment flows exist — they affect what "conversion" means on this page.

4. Run the 5-second value-prop test

Open the page. Cover everything below the fold. Ask: in 5 seconds, can a first-time visitor name the product, the outcome it produces, and one reason to trust it. If the answer is no, the page leaks at the value-prop layer and no button-color test will save it. This diagnostic precedes every other lever.

5. Walk the friction taxonomy on the specific page

PDP-specific: image quality, image count, variant selector clarity, price visibility, size/fit guidance, social proof location, "add to cart" prominence, shipping/returns info above the fold.

Cart-specific: line-item clarity, edit/remove discoverability, recommended-pairs visibility (without distracting from checkout), trust signals (return policy, security badge), checkout CTA position and weight.

Checkout-specific: see cart-abandonment-recovery for the field-count, payment-option, account-required, shipping-reveal, and trust-friction breakdown.

Signup-specific: number of fields, value-prop reiteration, social-login availability, password requirements (over-strict password rules silently kill conversion).

6. Apply the framework relevant to the leak

Pick the matching framework below and walk it for the page.

Framework: value-prop clarity in 5 seconds

The single highest-leverage PDP test is the 5-second test. The page must communicate, in 5 seconds, to a first-time visitor with no brand context:

1. What the product is — not the name, the category. A first-time visitor doesn't know what your branded product is. They know what a "daily greens powder" is.
2. The outcome it produces — not the feature. "Energy by 3pm" beats "47 superfoods."
3. One reason to trust it — review count, founder credential, ingredient certification, or guarantee.

If any of the three are missing in the above-fold experience, those are the first three fixes regardless of how many other tests are on the roadmap. Replace "Maximum Bioavailability Daily Greens" with "Daily greens powder. Energy by 3pm, no afternoon crash. 12,000+ five-star reviews." The conversion lift is consistently in the 12-25% band on PDPs that fail this test.

Framework: message-match between traffic source and landing

A Meta ad promising "lose 10 lbs in 30 days" that lands on a generic homepage converts at one-fifth the rate of the same ad landing on a "30-day weight management challenge" page. This is message-match: the headline of the ad should appear, in close paraphrase, in the headline of the landing page.

Diagnostic for ecomm:

• Look at the top 5 paid creatives by spend. Read the headline of each.
• Open the landing page each creative drops to. Read the H1.
• If the H1 does not echo the creative's promise, you have message-match failure and the conversion rate is being held down by a fixable cause.

The fix is not better creative or better landing pages individually. It is intentional pairing. Build a landing page per top-spend creative if necessary. Programmatic landing pages (see programmatic-seo) are a related tool when you have many ad variants.

Framework: trust signals placement

Trust signals are not decoration. They unlock action at the moment doubt arrives. The placement matters more than the existence:

• Review aggregate (e.g. "4.7 stars, 12,000 reviews") near the price, not buried in a tab.
• One representative review excerpt above the fold, not 10 reviews 5 scrolls down.
• Security/payment badges at the cart and checkout step, not the homepage footer.
• Return policy stated as a phrase ("60-day returns, no questions") near the add-to-cart, not linked in a footer.
• Founder photo or brand-story signal on the PDP for unfamiliar brands. Skip for category-leader brands.

The "trust ladder" rule: each step deeper into the funnel demands a stronger trust signal because the customer is committing more. PDP needs review aggregate. Cart needs return policy. Checkout needs security badge plus money-back guarantee phrase.

Framework: friction taxonomy

Five friction categories, in approximate order of conversion impact:

Form-field friction. Every required field below the minimum is a leak. Email + shipping is the minimum. Anything else (phone, company, gift-message) should be optional or deferred.

Account-required friction. Forcing account creation pre-purchase costs 20-30% of would-be buyers. Offer guest checkout, prompt account creation in the confirmation email.

Payment-option friction. Customers who expect Apple Pay or Shop Pay and don't see it often abandon rather than retype a card. Minimum surface: card + one wallet + one BNPL above $80 AOV.

Shipping-reveal friction. Surprise shipping cost at the final step is the highest-volume abandonment cause. Show shipping in the cart or surface the free-shipping threshold prominently.

Trust friction. Especially above $100 AOV. Treat per the trust signals framework above.

The taxonomy is diagnostic, not prescriptive. Walk it and identify which is the dominant leak before recommending fixes.

Framework: mobile-first CRO

Mobile and desktop are different conversion environments and need different layouts. The most common mistake is designing for desktop and shrinking. Mobile-first rules:

• Hero must hit value-prop in 5 seconds with one finger on the screen. No carousel auto-rotates faster than 6 seconds.
• The primary CTA must be reachable with the thumb without scrolling. "Add to cart" sticky-bottom on mobile is the single highest-leverage mobile PDP change.
• Forms must be one column. Two-column forms on mobile are a leak.
• Tap targets must be 44px+ minimum. Compressed PDP variant selectors are a common mobile leak.
• Apple Pay and Google Pay must be one tap. If you have these wallets and they require a 3-step path on mobile, you are leaving 5-10% conversion on the table.

Conversion gap between mobile and desktop should not exceed 25%. If it exceeds 40%, the page is desktop-designed and mobile-shrunk. Mobile is now 60-75% of ecomm traffic; the gap is a strategic, not aesthetic, problem.

Framework: one primary CTA per page

A page with three CTAs of equal visual weight has roughly the same conversion as a page with no CTAs. The eye scans for hierarchy; with no hierarchy, it disengages.

The discipline:

• One primary CTA per page. Visually dominant. Phrased as action + outcome ("Start my 30-day trial," not "Submit").
• Secondary CTAs allowed but visually subordinate. "Read reviews" or "size guide" should not look like "add to cart."
• Tertiary CTAs (footer-style, navigation) below the visual threshold of distraction.

The most common violation: PDPs with five equally weighted modules — "add to cart," "subscribe and save," "find your shade," "free skincare quiz," "join the rewards program" — that collectively destroy the focus the page needs. Pick one. Subordinate the rest.

Output Format

Structure the response in this order:

1. Headline diagnosis. One sentence naming the dominant leak (value-prop, message-match, friction, mobile, or CTA hierarchy).
2. Page audit table. 5-second test result, message-match check, friction taxonomy walk, mobile-vs-desktop conversion gap, primary-CTA count.
3. Quick Wins. 2-4 changes shippable this week.
4. High-Impact Changes. 2-3 changes over 4-6 weeks.
5. Test Ideas. 2-3 controlled A/B tests with primary metric, holdout size, duration. Reference ab-testing if test design is the next step.
6. Single highest-leverage next move. Named explicitly.

Related Skills

• cart-abandonment-recovery — when the leak is in checkout specifically and recovery flows need design.
• paid-ltv-optimization — when the issue is upstream channel mix sending wrong-fit traffic to the page.
• ab-testing — when test design and significance methodology is the next step.
• copywriting — when the audit identifies copy as the dominant leak.
• ad-creative — when message-match failure originates in the ad, not the landing page.