R$ 127,14
Retail leaders face a choice: let the swirl of AI hype dictate their priorities, or build repeatable capabilities that turn omnichannel complexity into sustained growth.
This book, Omnichannel Retail Growth in an AI‑First World gives you the latter – practical frameworks, playbooks, and governance advice to move from pilots to predictable, profitable outcomes.
What this book delivers
– A clear operating philosophy: treat omnichannel growth as a capability – not a one‑off project – by combining reliable data, disciplined experimentation, deterministic promises, and human‑in‑the‑loop controls.
– Actionable playbooks you can use immediately: from fixing store truth and local search to deploying personalization that respects inventory and margins, from BOPIS pilots to inventory-aware retail media strategies.
– Measurement and governance that scale: how to prove incrementality, integrate MTA and MMM, and require model cards, lineage, and rollback mechanisms so you can move fast without breaking trust.
Who should read it
– Retail executives and general managers who must prioritize investments across channels and partners.
– Product, data, and engineering leaders building identity, inventory, and decisioning systems.
– Merchandising, marketing, and operations teams launching personalization, fulfillment, and local discovery initiatives.
– Technology and vendor teams evaluating platforms, APIs, and integration patterns.
How the book is organized
The book balances big ideas with hands‑on work plans. Chapters walk through the full omnichannel stack:
– Strategy and value cases for an AI‑first omnichannel approach
– Data foundations, first‑party consent, and governance
– Customer 360, CRM, and lifecycle orchestration
– Local search, “near me” discovery, and Google Business Profile hygiene
– Personalization and merchandising at scale, with candidate + re‑rank patterns
– Unified inventory, promising APIs, BOPIS, and ship‑from‑store
– Journey design, experience operations, and fallbacks for graceful degradation
– Performance marketing, retail media, marketplaces, and attribution
– Measurement, incrementality, and an experiment ladder
– Operating model, COE + federated squads, talent, and model governance
– Technology and partner ecosystem: CDP/CRM, POS/OMS, AI/ML platforms, and integration patterns
A concise, practical roadmap
The book culminates in a conclusion that lays out a 90‑day, 12‑month, and multi‑year roadmap. You’ll find:
– A compact operational playbook with one‑sentence next steps per capability.
– A 90‑day checklist to reduce risk, prioritize 1-2 growth levers, and run a powered experiment that yields causal insight.
– A 12‑month plan to productize pilots: canonical inventory and identity services, feature stores, measurement programs, and an integrated retail media strategy.
– Multi‑year guidance to institutionalize decisioning, MLOps, and federated product teams while meeting MTTR, compliance, and talent goals.
Pragmatic commitments and governance
Christian Strutt emphasizes five commitments: pick one measurable outcome per experiment, treat data and models as products, start deterministic, demand incrementality, and respect store economics. The book prescribes non‑negotiable guardrails—consent, model cards, lineage, circuit breakers, and human review for high‑risk decisions.
Why this book matters now
AI increases both opportunity and risk. The retailers who win will be those who use AI to make dependable promises customers can act on, backed by measurement that proves causal impact. This book is not about feverish prediction; it’s a toolkit for leaders who need to make better decisions today and build capabilities that sustain growth for years.
Use it as a reference, workshop guide, or executive checklist.
| Brand | Edição Inglês por Christian Strutt (Autor) |
|---|
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© E-Commerce Update 2024 - Todos os direitos reservados.
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