The Practice
Three disciplines, one orientation: the coherence of the brand across surfaces, calibrated for AI-mediated commerce.
Lifecycle Strategy
The infrastructure behind retention. Lifecycle Strategy addresses how customers are recognized, segmented, and engaged over time — the work that determines whether growth compounds across a relationship or quietly erodes between transactions.
The discipline draws on a decade of operational depth in CRM, email, SMS, and customer journey design at premium consumer brands. What changes in AI-mediated commerce is not whether lifecycle matters — it does, more than ever — but how lifecycle systems must produce coherent signal across surfaces that AI will read and recommend from. Lifecycle is no longer only a retention function. It is a substantiation function.
The work includes:
- CRM architecture and segmentation strategy
- Customer journey design across owned and AI-mediated surfaces
- Email and SMS programs built for retention and recommendation
- Customer intelligence translation — turning behavior, reviews, and signal into operational decisions
- Experience diagnosis where brand promise and lifecycle execution have drifted apart
AI-native Growth
How brands are discovered when the discovery surface itself is changing. AI-native Growth addresses the strategic and technical work required for brands to surface accurately in AI-mediated discovery — and to convert that surfacing into sustained growth.
This is not a rebrand of SEO. The work begins from a different premise: that customers are increasingly receiving recommendations rather than searching for options, and that the systems producing those recommendations operate by a different logic than search engines did. Brands that succeed in this environment are not the brands that have produced the most content. They are the brands that have made themselves understandable to systems that read for meaning rather than match for keywords.
The work includes:
- AI readiness assessment across owned surfaces
- Strategy for conversational commerce and AI-mediated discovery
- AI ad readiness for emerging paid media channels
- Content and positioning calibration for how AI systems construct brand impressions
- Cross-platform visibility analysis — what AI is actually saying about the brand, and where
Brand Distribution
The strategic placement of the brand across surfaces beyond what it owns. Brand Distribution addresses the evolution of affiliate, partnership, and editorial work into something more substantive: the architecture of where, how, and through whom a brand becomes visible in contexts the brand does not directly control.
This is the discipline most often neglected by brands that have invested heavily in owned channels. In AI-mediated commerce, the brand’s representation in third-party contexts — editorial coverage, partner positioning, retail attestation, user-generated discussion — contributes substantially to how AI systems construct recommendations. A brand absent from these contexts is a brand harder to recommend with confidence.
The work includes:
- Affiliate and partnership strategy beyond commodity placement
- Editorial and press positioning for AI-readable third-party substantiation
- Retail and marketplace context evaluation
- Influence strategy that distinguishes authentic substantiation from coordinated content
- Cross-surface coherence audits — does the brand read the same way everywhere it appears
LMA works selectively with brands across luxury, hospitality, wellness, beauty, considered fashion, and adjacent categories where positioning is part of what is being purchased. Engagements are scoped to the specific work required.