Category: Marketing Data Science
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Why Propensity-to-Buy Prospecting Matters GTM Bottom Line1. The gap is real, and it’s bigger than it looks. A blended model says relationship history is worth almost nothing (+0.0125 AUC). Split the file in two and the true gap is 0.113 AUC — nine times larger. 2. Prospects still convert — just not for the reasons…
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What is Generative Engine Optimization (GEO) and why does it change how content is discovered? The rise of Dataism: Are writers becoming interfaces for algorithmic agents? I studied English Lit as an undergrad, before getting into analytics. My passion was writing and I always wanted to understand my audience, which is how I got into…
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Why Pipeline Optimization Matters: Executive Summary Introduction The Operational Challenge This final installment transitions our purchase-likelihood and segmentation models from a research artifact into a production-ready revenue engine building upon some of the methodologies and techniques in past articles: “Data science is not just about building models; it is about putting those models to work…
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🛑 STOP WAITING FOR PERFECT DATA The most persistent myth in applied AI is that your data needs to be pristine before it’s useful. It doesn’t. In fact, waiting for “perfect” data is costing most organizations more in lost ROI than the “noisy” data ever would. I recently joined Nav Thethi on his Cracking the…
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Why Propensity Scoring Matters for Pipeline Management Executive Summary Introduction The Lead Scoring Challenge In Part 1 Accelerating the Revenue Engine, I explored our B2B Salesforce pipeline through exploratory data analysis — profiling deal velocity, mapping funnel conversion rates, and segmenting accounts with RFM. We learned what the pipeline looked like. Part 2 is about…
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Pipeline management is rarely a linear path. While current views focus on meeting the quarter’s revenue targets, in my experience true pipeline health requires a “human-in-the-loop” approach that monitors leading indicators up to three quarters out to allow for proactive adjustments. To truly optimize revenue, organizations must orchestrate the entire journey—from lead generation to final…
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Why Collaborative Filtering (CF) Matters Executive Summary In modern B2B or B2C marketing, the “Discovery Problem” is the primary barrier to growth. Collaborative Filtering addresses this by: This is the third and final installment in my series on recommender systems, presented in the order I first applied them in B2B marketing. Fourteen years ago, my…
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In a previous article, I explored the Analytics Shoot-Out: Mike vs. Agentic AI. Today, I’m shifting the lens from competition with AI to integration of AI to provide a scalable extension of my personal marketing methodology. Perhaps the most profound realization in building this agent is the ability to have a specialized ‘staff’ at one’s…
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Why Recommender Systems Matter Introduction In my first article on recommender systems entitled Recommender Systems: Market Basket Analysis & Next-Likely-Purchase in Cross-Sell, I explored Association Rules (Market Basket Analysis), which identifies which products tend to be purchased together in a single transaction. It’s a powerful “snapshot” tool and is built on deep historical data, like…
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Why Recommender Systems Matter Introduction In the first article of this series entitled My Favorite Segmentation Scheme (https://mikesdatamarketing.com/2025/12/10/my-favorite-segmentation-scheme/) I identified the Loyal or High-Potential Customer segment and postulated a strategic portfolio management strategy to migrate the HiPo customers to Champions through cross-sell and up-sell. Here is a data visualization for the customer base in that…
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Analytics Shootout
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Why Statistical and ML Forecasting Matters Introduction I am always surprised when I join a company to find that the GTM and Finance functions are still relying solely on Excel spreadsheets and field sales “expert opinion” (the Delphi Method) for forecasting. This persists despite the wealth of statistical, machine-learning, and deep-learning methods available today. Often,…
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Why Marketing Mix Optimization Matters Introduction The Problem: Beyond the “3+ Rule”: It is widely accepted that a synergistic media mix will always outperform a single media vehicle. Historically, the industry adhered to the “3+ rule”—popularized in the 1970s—which suggested that three exposures to a message were required to influence a purchase. In the digital…
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Why Contact Targeting Matters Introduction & The B2B Modeling Hierarchy In my experience, B2B contact data lacks the predictive weight found in B2C or subscriber databases. Having managed contact data at Hearst, Cisco, and DellEMC, I’ve seen firsthand that while contact attributes (PII, job titles, and history) are essential for execution, they are often secondary…
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In this article, I demonstrate how to use the IBM Telco dataset with XGBoost and Survival Analysis (Lifelines) to identify at-risk customers and predict the timing of churn to protect business revenue.
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Why Customer Lifetime Value Matters Introduction My previous articles on RFM analysis and propensity-to-buy modeling explored stand-alone frameworks for segmentation and targeting. However, these models also serve as the foundational inputs for the ultimate metric in account prioritization: Customer Lifetime Value (CLV). While I have typically used CLV with subscription-based B2C models or B2B IT…
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Why Propensity-to-Buy Targeting Matters Introduction The “workhorse” of modern demand generation is a family of binary classification models. These models are designed to predict a specific response, such as “…whether a customer buys, whether a customer stays with the company or leaves to buy from another company, and whether the customer recommends a company’s products…
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Why RFM Segmentation Matters Introduction As I recall from school, the idea of optimizing a portfolio of B2B accounts goes back as far as Boston Consulting Group’s growth/share matrix and the initial list scoring techniques of direct marketers — and although the technology we use to segment customers has changed (i.e. Machine Learning) the underlying…