My musings on measurement, media, models, and malarky.

Led team of 3 Analysts and 1 Senior Data Scientist to serve a team of 24 globally; scope increased to include full Lifecycle analytics across Hardware Sales, Cross-Sell, Subscriber Lifecycle, Churn Prevention, and App comms.Tested & launched journeys across product onboarding, transactional comms, member engagement, and churn prevention programs through Email, In-App, Push, and SMS, growing Lifecycle contribution to Peloton hardware sales from 4.4% in FY22 to 8.6% in FY23. Key achievements: Browse Abandon, FaaS Buyout Personalized Promo, Next Best ActionSupported comms strategy for Peloton’s launches in Germany, Australia, and Austria, including consent requirements Added & managed a Data Science function to centralize support for personalization and targeting models, increasing the annual revenue from net-new initiatives from $6.8M in FY23 to $7.2M in FY24, representing 37% of total Lifecycle incremental revenue.Championed the creation of a Lead Gen focused role within Lifecycle Marketing, growing team contribution to Peloton hardware sales from 8.6% in FY23 to 17% in FY23.

Supported growth from a 4- to a 10-person multichannel Lifecycle marketing team through multiple product launches and cross-functional projects with Growth Marketing, Marketing IT, Enterprise Data, and eCommerce organizations.Developed and implemented data-driven marketing strategies that resulted in a significant increase in bike and tread sales from 3.9% to 4.4% in FY22.Built a robust Test & Learn practice within Lifecycle Hardware Acquisition Marketing, establishing the group as the authority for test designs, longitudinal measurement, and tracking all data-driven hypotheses and learnings over time.Collaborated with stakeholders to set OKRs, prioritize resources, and revamp forecasting tied to company sales metrics, achieving +/-3% margin of accuracy for team hardware forecasts each quarter, and demonstrating Lifecycle’s growing value amid declining overall sales.Drove Lifecycle strategy for launch of Tread+, Tread, Guide, and Row products, as well for all Bike product expansions (Rental, Refurb, Financing) by efficiently deploying market and pricing tests, analyzing customer data, and evaluating marketing performance metrics to leverage the unique reasons to buy that resonate with Lifecycle channels.Led and mentored a team of analysts, scaling the team from 1 to 3 members, supporting data-driven decisions across Growth Marketing.

Managed and developed a team of 3 Analysts & 2 Data Scientists through AGILE work processes to plan, conduct, analyze, and iterate on testing initiatives & new models across email, push, and in-app message marketing communications.Led development and execution of data-driven CRM strategies, optimized customer engagement through A/B testing and personalization, and improved campaign effectiveness and loyalty by collaborating cross-functionally and managing a team of analysts.Tested a new ML model targeting Loyalty Program (VIB) members with personalized promotions when they were identified as being at risk of lapsing their status, resulting in a 12% increase in incremental annual sales and targeting truly incremental customers more efficientlyImproved test design to accurately assess impact of a Product Replenishment prediction model, resulting in saving development costs of a multi-million-dollar pipeline and the successful launch of a user-driven in-app product that continues to drive incremental sales.

Forecast and Plan MAU and DAUCommunicate results and action opportunities to senior leadership & wider orgCreate reporting suite via Chart.io for Lifecycle teamDevelop Engagement metrics, norms, and forecasts for short and medium term planningDesign and implement email & in-app messaging tests

Forecast and Plan MAU and DAU and regularly communicate results and contribution to senior leadershipCreate reporting suite via Looker for Engagement division, including automating forecast models end to end from BigQuery through Python to LookML to visualizationsDevelop Engagement metrics, norms, and forecasts for short and medium term planningLead weekly results and planning for 20+ analysts, engineers, and marketing managersCoordinate new tracking initiatives with EngineeringDesign and implement product and email tests affecting 75 million users

Built eComm & Catalogue team's first behavioral segmentation testing roadmap and scaled segmentation tests to Catalogue strategy that drove $2M in annual production cost savings without sacrificing incremental sales.Developed & managed store, region, and country-level customer retention and frequency reporting to develop sales quota guidance and drill down to behavior level OKRs for salespeople (# of outreach messages to send monthly, etc) as well as automating client outreach list generation for all North American salespeople.Partnered with Merchandising to selectively reduce Charms assortment breadth to improve margin across Charms business, optimizing assortment strategy in-store vs online to minimize unsold units.Partnered with Director of Brand Management on Tiffany brand watch launches and Tiffany T launch to provide timely analytics across channels on creative performance. Assisted with database architecture initiatives, data hygiene initiatives, and data unification effortsDeveloped & managed eCommerce reporting and analytics to assess customer behavior onsite and impact of advertising spend

Analyzed media performance data and provided actionable insights, working on Brand Effect (IAG), RFM modeling, and Ratings Prediction projects for Networks & Advertisers.Conducted Brand Lift, Sales Lift studies for advertisers and networks. Key clients included: A&E Longmire Season 2, Nissan product placement, Geico, Budweiser’s “Very Superstitious” campaign, Disney’s Frozen TV campaignLiaison for ML team to build feature dataset for a predictive model for Telenovela ratings, scoring a large portfolio of TV shows across 6 content dimensions and accurately predicting ratings after season 3, improving data-driven decisions for cancellation or development.Contributed to development of RFM product for advertisers to help them optimize their advertising spend by networkAutomated report production for Nielsen Music’s Artist Profile product, developing consumer insights profiles for Luke Bryan and Eric Church before automating a generic form of the report as a sales product.Made programming length & content recommendations based on minute-by-minute tune-in/tune-out data for WWE Monday Night RAW and Nickelodeon’s Kids’ Choice AwardsOwned quarterly viewing report & insights deck for Disney Channel, providing a competitive assessment of the TV viewing habits of children under 18 to help them leverage their strengths and improve upon opportunity areas

First full-time hire at ex-McKinsey startup; pitched and raised financing from Sheryl Sandberg, Lubna Olayan, Susan Lyne, and Gina Bianchini.Directed editorial content partnerships; planned for, edited, and managed 150 regular contributors Managed site analytics, used traffic data to create pitch decks and maximize user loyalty Built wireframes and worked with CTO + Eng team to build a custom portal to connect Millennials to a Gen X & Boomer network to help mentor and sponsor their career development. Hosted weekly interview show with high-profile businesswomen to inspire and energize Millennials through the economic downturn and to help them find empowerment no matter their skillset.

• Provided industry expertise, insight, data, analysis; responsible for Firm’s industry overview fact-packs and quarterly updates in the Cable, Broadcast TV, Recorded Music, Film, Radio, Online, and Publishing industries• Managed team’s relationships with more than 90 data providers and gained comprehensive familiarity with analyst reports and white paper cycles in each industry covered by M&E team• Published weekly Media Reader for 500 consultants, including 25 Partners and Directors