Mailchimp had a recent eCommerce user prioritization, creating a clear focus for some teams but leaving significant gaps in the overall business and product strategy:
The majority of customers (non-eCommerce users) were left without clear prioritization
Product managers, designers and marketers lacked frameworks to understand and serve these customer segments
Leadership struggled with decision-making alignment beyond the core eCommerce focus
Previous segmentation attempts had been unsuccessful, creating organizational skepticism
I led, developed, and implemented a comprehensive three-phase segmentation strategy:
Phase 1: Data-Driven Modeling
Collaborated with data science to analyze product usage patterns
Created a self-coded modeling investigation to identify distinct user groups
Ensured segments were replicable and aligned with both company strategy and market realities
Established quantifiable metrics to define and track segments
Phase 2: Qualitative Exploration
Conducted in-depth interviews with customers across potential segments about product needs and usage
Validated that segments existed beyond product usage data
Mapped behavioral patterns and needs against our core user profile
Discovered nuanced differences in goals, challenges, and success metrics
Phase 3: Quantitative Validation
Designed and deployed large-scale customer surveys
Statistically validated segment existence and distribution
Measured segment size and business impact
Refined segmentation model based on comprehensive data
The segmentation project transformed Mailchimp's strategic direction:
Received unanimous executive approval from founders, CPO, CMO, COO, and CFO
Identified and prioritized a previously undiscovered high-value segment with alignment from leadership (phew.)
Led company-wide education through department-by-department roadshows
Initiated customer decision journey workshops for each segment to deepen organizational understanding
Product Feature
Integrated segment self-identification into customer onboarding process
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I joined Scribd in May 2020. Yeah, during the start of the pandemic lockdowns. Scribd is content on small screens and in ears: books, audiobooks, podcasts, sheet music, magazine articles, documents, Slideshare. Like many digital products, usage changed dramatically, with complexity and difficult pattern recognition. Product use was healthy and increasing, but how to respond was floundering.
I put together a diary study. That informed product strategy, helped make design decisions, provided machine learning teams with behavioral data to refine recommendation algorithms (that is what the balloon represents), and guided content acquisition strategy.
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I am happy to build out case studies around a breadth of different research plans, goals, and methodologies. Here are a couple on building product features including a content carousel with metadata and a mobile-first feature.
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