DTC beauty brand: 22 to 58 in one afternoon
Free check, Shopify guide remediation, rescan
Context
A direct-to-consumer beauty brand running on Shopify does approximately $120K/month in revenue. The founder ran a free Colter check after seeing the industry report data showing 67.5% of stores scoring below 20/100. The initial score was 22/100.
Before and after scores
Before
Can AI agents find your products?
Can AI agents complete purchases?
Is your store safe for automated transactions?
How many AI platforms can interact with your store?
Do AI agents understand your product data?
After
Can AI agents find your products?
Can AI agents complete purchases?
Is your store safe for automated transactions?
How many AI platforms can interact with your store?
Do AI agents understand your product data?
The workflow
Ran a free check on the Colter homepage
Entered the store URL into the free checker. Results returned in under 30 seconds showing a composite score of 22/100 with per-dimension breakdowns.
Reviewed the dimension-level findings
Discovery scored 28/100: the store had basic meta tags but no JSON-LD product schema and an incomplete sitemap. Transaction scored 10/100: no structured checkout metadata. Security scored 42/100: SSL was in place but no Content-Security-Policy headers. Ecosystem scored 8/100: no protocol support detected. Content Quality scored 22/100: product descriptions existed but lacked structured attributes.
Followed the Shopify AI-Ready guide
The report linked directly to Colter's Shopify remediation guide. The founder worked through the steps in order of expected point improvement, starting with JSON-LD structured data.
Implemented remediation steps over one afternoon
The specific changes made are listed in the remediation section below. The most impactful were adding JSON-LD product schema and installing a Shopify SEO app for sitemap generation. Total hands-on time was approximately 4 hours.
Ran a rescan to measure improvement
After implementing all changes, a second Colter check showed the composite score had improved from 22/100 to 58/100. Every dimension showed improvement, with Discovery and Content Quality seeing the largest gains.
Key findings
- --No JSON-LD product schema on any product page
- --Sitemap.xml existed but excluded collection pages and was not submitted to Google Search Console
- --robots.txt had no AI-specific directives
- --No Open Graph product tags beyond basic title/description
- --Product descriptions were present but lacked structured attributes (dimensions, materials, ingredients)
- --SSL certificate was active but Content-Security-Policy and Permissions-Policy headers were missing
- --No ACP or UCP protocol endpoints detected
- --No structured checkout metadata (shipping options, payment methods not machine-readable)
Remediation steps
Added JSON-LD Product schema to all product pages using Shopify's built-in structured data support and a theme code edit (+18 points on Discovery)
Installed a Shopify SEO app that generates comprehensive XML sitemaps including collection pages, and submitted the sitemap to Google Search Console (+8 points on Discovery)
Added AI-specific directives to robots.txt allowing agent crawling of product pages (+4 points on Ecosystem)
Enhanced Open Graph tags on product pages with og:price, og:availability, and og:brand (+6 points on Content Quality)
Rewrote top 20 product descriptions to include structured attributes: ingredients list, size/weight, usage instructions (+12 points on Content Quality)
Added Content-Security-Policy and Permissions-Policy headers via Shopify's proxy configuration (+8 points on Security)
Enabled Shopify's native structured checkout metadata (+10 points on Transaction)
Added a basic llms.txt file to the store root describing the product catalog structure (+6 points on Ecosystem)
Outcomes
- +Score improved from 22/100 to 58/100
- +Discovery improved from 28 to 72 (+44 points)
- +Content Quality improved from 22 to 70 (+48 points)
- +Transaction improved from 10 to 35 (+25 points)
- +Security improved from 42 to 65 (+23 points)
- +Ecosystem improved from 8 to 48 (+40 points)
- +Total remediation time: approximately 4 hours
- +No paid tools required beyond existing Shopify plan
This case study describes a representative workflow based on real data patterns from Colter's batch scan of 363 e-commerce stores. No company names, individuals, or direct quotes are used. Score breakdowns reflect realistic distributions observed in the scan data. This is a pre-launch example, not a customer testimonial.
Run your own audit
Free check, no account required. See your 5-dimension score in under a minute.