Desktop storefront view
Desktop capture of the current brand storefront or homepage.
If the first desktop view lacks category clarity, proof, or contact confidence, colder buyers bounce before product intent compounds.
Founder teardown
Why Outkast Code gets found but still leaves trust on the table.
This is the same internal benchmark scan turned into a founder-facing teardown. It strips the audit down to the parts that matter first: what leaks trust, where the gap is largest, and what gets fixed next.
63Overall readiness
5Premium gaps
62Largest gap (Reputation & social proof)
4Immediate fixes
Mobile storefront view
Mobile capture of the storefront, where many D2C buyers first inspect trust signals.
Mobile friction is usually where discovery-led interest dies first, especially when popups, weak proof, or clutter block the buying path.
Desktop product or collection view
Deeper commerce capture used to inspect product trust, pricing, and buying cues beyond the homepage.
If the deeper commerce surface is thin, buyers may discover the brand but still hesitate at the product decision point.
Mobile product or collection view
Mobile commerce capture used to inspect above-the-fold CTA, trust, and checkout friction closer to real buyer behavior.
If the mobile product or collection view hides the CTA, trust proof, or pricing context, impulse intent dies before the buyer reaches cart.
Desktop cart / checkout view
Desktop cart page attempt — reveals CTA clarity, shipping/return proof, and checkout-friction signals.
If the cart page buries the CTA or lacks trust signals (returns, payment logos, contact proof), checkout abandonment rises sharply.
Mobile cart / checkout view
Mobile cart page — the most common D2C checkout-abandonment surface.
Mobile cart friction is the biggest single revenue leak for most D2C brands — hidden fees, no trust badges, or a slow checkout destroys impulse intent.
Public Instagram profile view
Public Instagram profile capture used to inspect bio clarity, proof surface, and the path from profile to product or WhatsApp.
If the public profile does not explain the category, trust, and next step in seconds, discovery stays social but conversion intent leaks before the site visit.
Link-in-bio / external profile link
External URL found in the Instagram bio — the brand's chosen link-in-bio or product page.
If the link-in-bio is broken, slow, or redirects to an unrelated page, the social-to-site handoff is leaking buyers.
Facebook profile
Facebook profile — public presence and brand page trust signals.
A missing or inactive Facebook profile can reduce social proof for discovery-stage buyers.
X (Twitter) profile
X/Twitter profile — public social presence and engagement signals visible to buyers.
An inactive X/Twitter profile can signal brand neglect to buyers who check social proof before purchasing.
Under Armour is winning your category in AI answers
Under Armour was the most-named brand in your category (73 total mentions across 25 sportswear and athletic apparel buying questions × 5 runs), while you were named 24 times — AI is routing that demand to them. (Measured for the inferred category "sportswear and athletic apparel" in the US and global market. If that's not your category/market, this finding may not apply.)
What changes next: Study the questions where Under Armour is named and you are not, then close those specific gaps (schema, reviews, citable content) and re-scan.
Structured data is thin or missing
Organization, Product, and FAQPage schema is absent. Without complete schema, AI/search systems have to guess what you sell, who you are, and what buyers say.
What changes next: Add product, organization, breadcrumb, FAQ, and review schema so AI/search systems can parse the brand without guessing.
No FAQ schema — AI can't lift your answers
No FAQPage structured data was detected. AI answers are assembled from Q&A-shaped content; without it, engines paraphrase competitors instead of quoting you.
What changes next: Publish an FAQ (shipping, sizing, returns, COD/UPI, care) with FAQPage schema so AI can quote your exact answers.
The call
Add product schema and tighten the product detail surfaces first. This is the cleanest way to improve machine readability without changing the brand story.
The product should keep pushing toward this shape: faster founder comprehension, stronger proof, and a clear implementation path instead of a passive scorecard.
Days 1-7
Trust repair sprint
Make the brand easier to verify before new traffic arrives.
- Add Product, Organization, FAQ, and policy schema where content exists.
- Place review proof near product and inquiry intent.
- Tighten product category, price, shipping, return, and support answers.
Days 8-30
AI and Google authority sprint
Increase entity confidence across Google and AI answer surfaces.
- Build sameAs links across website, Instagram, marketplace, review, and founder/profile surfaces.
- Create answer-ready FAQ and product-support pages for common buyer questions.
- Lift Google trust from 50/100 by adding third-party proof and consistent public profiles.
Days 31-90
Monitoring and compounding sprint
Turn the audit into a recurring visibility and conversion operating loop.
- Run monthly AI/search prompt checks for brand, category, and competitor buying questions.
- Track review growth, WhatsApp inquiry recovery, and product-page trust improvements.
- Convert findings into founder teardown content and approval-gated outreach.