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
