B2C Growth Rebuild
Part of the AI-First GTM & Marketing practice. Also in the Marketing & GTM Portfolio under Growth & Demand.
End-to-end GTM for an established B2C brand: 7x conversion and 43% lower CPL on flat paid spend.
A relaunch isn"t a redesign. It"s a decision about how a market should understand you. This engagement rebuilt the full go-to-market stack for an established consumer brand whose demand engine had stopped compounding - traffic held, intent didn"t convert, and paid spend carried the number.
The mechanism
Discoverability layer. A 30-page AEO-native, technical-SEO-forward site: FAQ schema, canonical mapping, entity-consistent naming, and build-time SEO validation so regressions fail the build instead of the quarter. Pages were structured to answer the questions buyers actually ask AI assistants, not just to rank.
Narrative layer. A brand and voice system with one narrative source, so site, collateral, and ads stop arguing with each other. Code-based collateral made the system reproducible rather than a one-time design deliverable.
Demand layer. Paid media rebuilt against the new narrative and the new landing architecture - audience structure, creative, and destination pages moved together instead of being optimized in isolation.
The outcome
Conversion improved roughly 7x and cost per lead fell about 43% - on flat paid spend. The gain came from alignment, not budget: the same traffic met a page that matched the promise that brought it there.
Further Reading
Common Questions
- What were the results of the AI-Native GTM rebuild?
- 7x conversion and 43% lower CPL on flat paid spend for an established B2C brand.
- What did the rebuild involve?
- Three layers: a 30-page AEO-native, technical-SEO-forward site; a brand and voice system with one narrative source; and paid media rebuilt against the new narrative and landing architecture.
- Why AEO rather than SEO alone?
- Pages were structured to answer the questions buyers actually ask AI assistants, with FAQ schema, canonical mapping, entity-consistent naming, and build-time SEO validation so regressions fail the build.