MarTech operating framework for B2B SaaS stacks - built for clarity, speed, and measurable impact

Phase 1: Identifying Challenges & Goals

Before we touch tools, we run a deep-dive discovery to align business needs with measurable outcomes.

What we’ll clarify:

The marketing and sales pipeline problems we’re solving (attribution, payback visibility, activation, handoffs).

Success metrics and target thresholds (LTV/CAC, payback, demo→SQL→Win rates, retention/expansion).

Scope, constraints, stakeholders, and decision criteria (buy vs. build, compliance, security, budget).

📌 Why this matters: It anchors the stack to business outcomes, not features - so every next step is decisionable.

Phase 2: Creating a Personalized Onboarding Timeline

With goals set, we design a realistic, dependency-aware onboarding plan.

We build:

Systems inventory & dependency graph (CRM, MAP, CDP, analytics, DW/ETL, ads, enrichment).

RACI and approval flows (Marketing, Sales, Product, RevOps, Security).

Risk & assumptions register, with clear rollback paths and QA gates.

📌 Outcome: A step-by-step roadmap aligned to team capacity, what ships, when, and why.
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↪️ Key outputs: Onboarding timeline, RAID log, milestone review schedule.

Phase 3: Data Planning & Strategic Guidance

At this stage, we define the data architecture and implementation strategy, ensuring that every touchpoint is aligned with your business goals.

We define:

Event taxonomy & data contracts (product events, marketing events, lifecycle states).

Identity resolution (user/account keys, anonymous→known stitching, consent & governance).

Attribution & modeling logic (UTM standards, touchpoint collection, payback/cohort math).

Segmentation framework (ICP tiers, lifecycle stages, PQL/MQL scoring, intent thresholds).

👉 NOTE: This is where my expertise makes the difference. Your data tracking and automation logic will dictate how you gain insights, optimize engagement, and drive conversions. I ensure that your data structure is built to support long-term business objectives.

↪️ Key outputs: racking plan spec, schema docs, dashboard requirements, naming conventions, etc.

Phase 4: Implementation & Technical Execution

Once the data framework is finalized, we move into the technical implementation phase.

We execute:

Tag manager & SDK setup (web/app events, server-side collection, consent mode, cookieless fallbacks).

Integrations & syncs (CRM↔MAP↔CDP↔DW, enrichment, webhooks, ad platform audiences).

Data quality & governance (PII handling, access controls, error monitoring, replay/repair paths).

QA workflow (spec-to-event tests, schema validation, dedupe rules, alerting for drift).

📌 Outcome: A trustworthy, fully connected stack that powers analytics, automation, and targeting.

↪️ Key outputs: Integration matrix, QA evidence, runbooks, access policy.

Phase 5: Orchestration, Activation & Revenue Programs

Turn clean data and integrations into predictable, cross-channel revenue programs, without adding chaos. Execution is stack-agnostic (marketing, sales, product, analytics) and tied directly to attribution and the metrics your leadership tracks.

Key Deliverables:

Event-driven, cross-channel activation (email, in-app, web, ads, CRM)

Uses clean events, identities, and segments (MQL/PQL/SQL, lifecycle, ICP tiers).

QA & governance runbook: tests, seed users, rollback/kill-switches, consent mapping.

Reporting dashboards: tailored dashboards mapped to your sales, marketing and growth KPIs

📌 Outcome: Trusted, real-time data powering confident decisions across marketing, sales, and growth.

↪️ Key outputs: Consolidated MarTech stack and activation architecture built to scale.

Phase 6: Ongoing Maintenance & Optimization

Great MarTech runs on cadence - monitor, learn, adapt.

Standardized review cycles. Channel → cohort → payback dashboards; exception reporting.

Data reliability: freshness SLAs, schema checks, anomaly alerts, fix-forward playbooks.

Scale & evolve: new events, segments, and programs as the product and GTM mature.

↪️ Key outputs: Monthly ops pack, backlog & roadmap, governance updates.

Why this process works

Tailored to your GTM motion (PLG/SLG/hybrid)

Clear implementation plan. Defined and properly delegated ownership, QA gates, and rollback paths reduce risk.

Scalable architecture. Built to grow across products, segments, and regions.

Operational cadence. A rhythm that sustains impact long after “go-live.”