This comprehensive suite of services is designed for organizations that want to evolve from tactical programmatic marketing driven by business intuition to developing a sustainable competitive advantage through a quantitative, strategic marketing approach. They need a leader who can translate complex signals into a cohesive, revenue-driving Go-To-Market (GTM) strategy.

Tier 1: Core Fractional Leadership

Strategic Marketing Management: Data-Driven Growth

Service & Description: Holistic marketing planning for growth-stage or enterprise organizations requiring a full-funnel strategy. I focus on the GTM demand generation function anchoring strategic initiatives and tactical programs in quantitative rigor. From planning around media mix optimization, customer segmentation and forecasting to tactics such as competitive take-outs, x-/up-sell, customer acquisition and retention all work is geared towards pipeline optimization.

Use Case Articles:
- The Multi-Channel Force Multiplier: How Bridging Digital Nurture and Direct Outreach Triples Conversion Lift. How coordinating digital nurture with direct sales outreach produces a measurable, compounding lift in conversion rates across the full funnel.
- The Hybrid Forecast: Integrating Field Sales “Expert Opinion” with Deep Learning Ensembles. Why blending field sales judgment with deep learning ensemble models produces more accurate revenue predictions than either method alone.
Professional Use Cases:
- Scaled a $10M revenue engine and a 30-person multi-channel ad agency at Hearst Newspapers, alongside the agile GTM development built for the Career Central startup.
- Built statistical/ML forecasting models to help Finance accurately predict annual revenue in a volatile mid-market environment, resulting in stronger pipeline control, more reliable earnings guidance, and a significant stock-price rebound—recognized externally by SiriusDecisions as an unusually advanced, data-driven engine for targeting, cross-sell/upsell, and forecasting.
- Marketing Mix Optimization improved ROI from 18x to 32x using ML for optimization.
Deliverable: A comprehensive, integrated GTM strategy and brand-performance framework that drives sustainable revenue growth through measurable execution.

Chief Marketing Data Officer (CMDO): Marketing Data & Intelligence

Service & Description: Interim leadership for organizations that have “all the data but no information” because they lack the strategic bridge between technical teams, business operations and the C-suite. I align data quality initiatives, operational reporting requirements and data science investments with corporate growth targets to ensure data-driven insights influence everything from tactical execution to strategic planning.

Use Case Article: From Accounts to Contact Personas: a data-driven framework for B2B targeting and segmentation — when contacts matter. Why B2B targeting breaks down at the account level and how a contact-level segmentation framework sharpens both reach and conversion.
Professional Use Case: Architected and executed a comprehensive Master Data Management (MDM) strategy, building a scalable, multi-domain Data Lake in partnership with IT, enabling centralized analytics across three major BUs.
Deliverable: A strategic growth roadmap and executive-level ROI narrative that translates complex data signals into high-stakes brand and business investments.

Tier 2: Strategic Accelerators

Agentic AI Strategy & Implementation

Service & Description: Most organizations have predictive models that never reach the sales floor. I close that gap by architecting an Agentic intelligence layer that encodes your analytical thinking — making it available to Sales, Finance, Marketing, and Ops through a natural language interface.

The core design principle is Methodology Preservation: the agent loads your proprietary frameworks as its primary context every session, so responses reflect your specific approach rather than generic AI output. The architecture operates on a Consulting Triad — your published methodology, the user’s live business context surfaced through dynamic discovery questions, and an LLM reasoning engine that synthesizes the two into a structured strategic assessment.

Use Case Articles:
- Analytics Shoot-Out: Mike vs. Agentic AI. I stress-tested AI against my own methodology and know exactly where it wins, where it fails, and why human-in-the-loop expertise still matters.
- Mike The Robot: Scaling Expertise into the Singularity. Having understood its limits, here’s how I architected it as a force multiplier rather than a replacement.
Professional Use Case: Personally built and validated the “Mike Agent” as a working prototype — it scrapes a live methodology library at session start, conducts a dynamic five-question discovery interview, and produces a prioritized gap analysis with a phased technical roadmap. In a live B2B churn scenario, the agent surfaced an insight no single-session conversation would have found: it connected a Market Basket Analysis technique from a cross-sell framework to a retention problem because the underlying data pattern was identical. That cross-methodology synthesis is the core value proposition of encoding expertise into an agent.
Deliverable: A custom-built Agentic AI execution layer — from architecture through phased enterprise deployment — that translates predictive model outputs into actionable, department-aware playbooks and automates high-value GTM interventions at scale.

GTM Performance & Pipeline Acceleration

Service & Description: An optimized multi-touch attribution framework and lead-scoring model designed to increase pipeline velocity, sharpen budget allocation, and power cross-sell/up-sell recommender engines.

Use Case Articles:
- The Future Only Depends on the Present: Markov Chains and the Customer Journey. How state-transition modeling replaces broken first/last-touch attribution with a mathematically sound picture of how prospects actually move through the funnel.
- The Demand Generation Workhorse. A ground-level framework for building the repeatable, measurable demand generation engine that underlies every high-performing GTM motion.
Professional Use Case: Developed and deployed advanced lead-scoring models that prioritize high-intent, time-sensitive leads, significantly increasing lead conversion velocity and directly contributing to an increase in the qualified sales pipeline.
Deliverable: An optimized multi-touch attribution framework and lead-scoring model that increases pipeline velocity and sharpens budget allocation and/or a recommender engine for x-/up-sell.

Predictive Customer Lifecycle & CLV Strategy

Service & Description: Maximize the value of every customer by predicting churn and identifying expansion and retention opportunities. I deploy mathematically sound segmentation and propensity models to move the organization from tactical, one-off programs and reactive support to proactive retention.

Use Case Articles:
- My Favorite Segmentation Scheme. Why behavioral segmentation outperforms demographic targeting and how to build a value-based scheme that sales, marketing, and finance can all act on.
- The Financial Side of Marketing: Beyond RFM to Predictive CLV. How to move from backward-looking RFM scoring to a forward-looking Customer Lifetime Value model that ties marketing investment directly to revenue outcomes.
- Plugging the Leak: Gradient Boosting and Survival Analysis for Customer Retention. How combining two advanced statistical techniques identifies at-risk customers earlier and more accurately than traditional churn models.
Professional Use Cases:
- Led cross-functional teams to develop a Marketing Analytics Portal, scaling customer targeting and segmentation; provided advanced analytics and a value-based account segmentation model (based on purchase behavior and XaaS adoption) for Sales Territory Planning and Sales Account Management.
- Built Propensity-to-Churn models that accurately identified at-risk customers and measurably improved retention.
Deliverable: A scalable RFM and Customer Lifetime Value (CLV) model integrated into daily operations to provide a value-based segmentation scheme for targeted retention programs, cross-/up-sell tactics and to predict and proactively mitigate churn.

Tier 3: Technical Foundations

Data Science COE Design & Mentorship

Service & Description: Scaling a high-performing analytics function from the ground up. This involves designing the organizational structure and workflow, hiring/training and mentoring rising technical leaders to improve business storytelling and cross-functional influence.

Use Case Video: How to Launch a Data Science Team Built for Scale. The organizational design, hiring sequencing, and workflow decisions that separate a high-performing analytics function from one that stalls at the proof-of-concept stage.
Professional Use Case: Founded and scaled the Marketing Data Science practice in five different global high-tech companies, driving technical hiring, advanced skill development, and creation of foundational data assets alongside governance protocols that supported enterprise-wide growth.
Deliverable: A world-class Data Science Center of Excellence blueprint that transforms raw data into a sustainable competitive advantage.

Marketing Intelligence Ecosystem Architecture

Service & Description: Technical advisory for architecting the foundational Data Lake and Master Data Management (MDM) processes required to achieve a 360-degree customer view and scale AI execution.

Use Case Podcast: Time To Put on Our DataOps Lab Coat. What it actually takes to build the data infrastructure — governance, pipelines, and MDM — that makes enterprise-scale predictive modeling possible.
Professional Use Case: Championed and executed core Data Strategy and Quality initiatives, establishing the infrastructure required for scalable predictive modeling of customer behavior.
Deliverable: Either an on-prem or cloud-native data governance architecture designed to unify disparate customer data into a single, decision-ready intelligence source. Includes documentation such as a data dictionary and entity-relationship diagram of a master analytic record.

Engagement Philosophy

My engagement philosophy centers on one principle: Operationalizing Intelligence. I do not deliver technical artifacts and walk away — I architect the analytic machine, embed it into daily workflow, and build the operational processes that make insight a repeatable competitive advantage. The distinction matters: code and reports depreciate. A functioning GTM intelligence system compounds.

Where appropriate, I also work directly with sales and marketing teams on tactical program execution — ensuring strategic recommendations don’t stall at the PowerPoint stage.

To discuss an engagement or learn more about my background visit the Resume and Bio pages or my LinkedIn page.

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