Building Predictable B2C Growth With AI-Driven Marketing Ops: A practical playbook for orchestrating data-backed customer journeys, automating ... sales, and products (Practical AI Marketing)

Predictable B2C growth is not a creative problem — it’s an operational one. If your teams have great ideas and best‑of‑breed tools but still struggle to turn experiments into reliably repeatable gains, this book is your playbook for closing that gap.

Building Predictable B2C Growth With AI‑Driven Marketing Ops lays out a pragmatic, hands‑on approach to designing data‑backed journeys, automating campaign execution, and aligning cross‑functional teams around measurable outcomes. It’s distilled from years of experience helping growth, product, and ops teams move from fragmented campaigns to governed growth systems that scale.

What you’ll get
- A clear architecture for growth: identity, decisioning, composable orchestration, and measurement/governance — and how to integrate them.
- Practical frameworks and patterns you can use immediately: event pipelines, canonical customer_id, consent stores, reusable playbooks, and simple decision outputs.
- An operational approach to AI: PDAL (Predict → Decide → Act → Learn), confidence→actions matrices, drift monitoring, and how to keep models useful, explainable, and testable.
- A proven 90‑day plan with weekly milestones, success criteria, and a shipping checklist so you stop building “half‑done” experiments and start producing measurable lifts.

Inside the book
You’ll find concise, actionable chapters covering the full stack and operating model:
- Data foundations: identity, consent, and the unified customer record
- The stack: CDP, CRM, MAP, and event pipelines that actually work together
- Journey design and orchestration: triggers, states, reusable flows, and playbooks
- AI in the loop: prediction, decisioning, generative acceleration, and safe automation
- Acquisition, conversion, retention: practical tactics for media, onboarding, and lifecycle programs
- Measurement and experimentation: randomized tests, MTA/MMM calibration, and KPI hygiene
- Operating model and governance: SLAs, runbooks, and cross‑functional rituals

Why this book is different
This is not theory. It’s a playbook: checklists, runbooks, a compact operational thesis, and concrete tradeoffs you’ll face (centralization vs. speed, real‑time vs. batch, simplicity vs. accuracy). The emphasis is on minimal viable systems that deliver measurable outcomes — not on building perfect models or monolithic platforms before you’ve proven impact.

Who should read it
- Growth and marketing leaders who must align teams around predictable outcomes.
- Marketing ops and product engineers who build event pipelines, orchestration, and CDP integrations.
- Founders and product managers who need a repeatable way to scale acquisition, activation, and retention.
- Data and ML practitioners who want to operationalize models and keep AI grounded in experiments.

Outcomes you can expect
- Faster time to validate a high‑leverage flow (cart recovery, trial activation, onboarding).
- Measurable incremental lifts from governed automation and randomized tests.
- Reduced operational chaos: clearer ownership, SLAs, schema validation, and fewer mis‑sent campaigns.
- A repeatable cadence of experimentation and improvement that compounds retention and LTV.

Read with an experimental mindset: start small, measure, iterate, and scale what works. If you want a ready‑to‑use 90‑day template tailored to your business or to continue the conversation, the author is reachable on LinkedIn: https://www.linkedin.com/in/christianstrutt/. Start by picking one flow to stabilize this week — and measure the difference in 30 days. That’s how predictable growth begins.

Contact me at my digital marketing agency www.MiltonKeynesMarketing.uk or via LinkedIn