Direct-to-consumer ecommerce · Vancouver, BC · ships across Canada · 6 months

VP of Marketing, Canadian D2C ecommerce brand (~C$5M–C$15M GMV range)

A Canadian D2C ecommerce brand wanted to recover declining brand-name SERP visibility and start showing up in AI engine product comparisons. We ran a six-month schema citation lift program covering Product, Offer, Review, and AggregateRating schema, plus a product-page SEO sprint.

Editorial note: Anonymized per our editorial policy. No fabricated client names or quotes. All metrics are directional and qualified with attribution; client-reported figures are labelled.

Service & engagement

Service
Schema citation lift program + product-page SEO
Engagement length
6 months

The challenge

The brand had a healthy paid-acquisition program but declining organic share-of-voice. Brand-name searches increasingly returned competitor comparison pages above the brand's own listing. AI engine searches for the brand's category were returning competitor brands at 3–5× the citation rate. The engineering team had limited bandwidth and the marketing team had no SEO specialist.

Approach

  1. 1
    Audited schema coverage across 200+ product pages. Found Product schema on roughly 40% of pages and AggregateRating schema on under 10%. No Review schema connected to verifiable third-party review sources.
  2. 2
    Worked with the engineering team to ship complete Product + Offer + AggregateRating schema across the catalog in weeks 3–6, sourcing review data from the existing third-party review platform and validating at scale.
  3. 3
    Rebuilt the brand and category page copy with comparison-aware framing: 'how we differ from [generic category]' content rather than 'about us' content. Six pages over two months.
  4. 4
    Set up monthly AI engine brand-citation tracking covering ChatGPT, Perplexity, Gemini, and Google Shopping AIO. Established a competitor-citation benchmark in month 1.
  5. 5
    Ran a refresh sprint on the top 30 product pages, adding richer descriptions, FAQ schema for category-defining questions, and improved internal linking from category pages.

Outcomes

40% → 95%+
Schema coverage on indexable product pages
verified in Rich Results Test
approx. 4× lift
Estimated AI engine brand-citation share (category queries)
measured against same competitor set, monthly
approx. +60%
Organic-sourced revenue (M6 vs M0, client-reported)
GA4 + Shopify attribution, last-non-direct-click model
Restored on 18 of 22 priority queries
Brand-name SERP visibility (own listing above first competitor)
monthly position tracking

Reflection

Schema is the single most under-invested SEO lever for D2C ecommerce. The engineering effort to ship complete Product + AggregateRating + Review schema is real but bounded — usually 2–4 weeks of one engineer. The compounding effect on AI engine citations and Shopping graph eligibility is disproportionate. We have multiple D2C clients now where schema work alone justifies the retainer cost.

EcommerceSchemaAEOD2CVancouver

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