Director of Business Intelligence2011 - 2016TheStreet.com
Technologies: Excel VBA, Scikit-learn, Pandas, NumPy, D3.js, R, Python, Oracle, Microsoft SQL Server, Statistical Modeling, Machine Learning
- Built a set of logistic regression models (one per product) for email targeting that improved email response rates by 18%, while maintaining email volume, by improving the relevance of email messaging. I used R (GLM) for the analysis and implemented the solution in SQL Server.
- Built regression and clustering models that identify likely fraud. This lets us proactively cancel fraudulent orders and reduced our chargeback rate by 30%.
- Created an automated reporting tool for landing page testing that makes registration flow optimization quick and accurate.
- Built a set of machine learning classification algorithms (using Python Scikit-Learn) that identify the leads with the highest purchase likelihood for upgrade and cross-sell.
- Created a website (the “Telesales Dispatcher”) that presents the highest quality leads to our telesales agents each day, based on statistical models of purchase likelihood that I developed.
Director of Research and Analytics2007 - 2011eMusic, Inc.
Technologies: Excel VBA, R, Microsoft SQL Server, Statistical Modeling, Machine Learning
- Built a suite of automated database reporting applications, using Excel (with VBA) as a client for SQL Server data, providing visibility into all of the marketing data and company key metrics, including signups, web conversion rates, email open and click rates, site usage, churn metrics, and geo-mapping.
- Built a web scraping tool that retrieves song and album prices from Amazon and iTunes, so that we can strategically price our music catalog to best comparative advantage. This tool improved our overall prices by 15%.
- Developed customer churn and upsell models of our customers via multivariate logistic regression, used for enhanced targeting of our member communications and offers. Improved upsell rates by 13% while improving retention by 8%.
Director of Direct Marketing and Analytics2000 - 2007EarthLink, Inc
Technologies: Excel VBA, SAS, Microsoft SQL Server, Statistical Modeling, Machine Learning
- Developed, implemented, and analyzed the direct marketing strategy for EarthLink’s dial-up products, including both EarthLink’s flagship dialup internet brand and the PeoplePC value brand. Managed a small team of data scientists, and an overall annual marketing budget of $60 million dollars.
- Optimized marketing spend across direct response TV, solo and shared mail, sponsorships, promotions, and field marketing. Generated more than 850,000 members through my channels in 2007, beating our 2007 plan by 10%.
- Created the “FrontLine Strategizer”: a SQL Server database application (with Excel / VBA client) that builds aggregated monthly forecasts out of campaign-level inputs. Integrated with my real-time direct marketing response projections, this tool enabled me to react quickly to campaign performance and optimize budget allocation.
- Managed a team of marketing managers and data analysts distributed across the San Francisco and Atlanta offices, building their direct marketing skills and helping them deliver subscribers on time and under budget. Also managed a stable of marketing and media buying agencies that assisted with all of our direct marketing efforts.
- Built the “MACalyzer” – a SQL Server database application for direct response TV reporting that reduced the member acquisition costs in the television channel by 18%. This tool ties 400+ dedicated phone numbers to their associated advertising spend and identifies the resulting orders so that we can track the ROI and member acquisition cost for each airing of our commercial.
- Developed a direct mail reporting and analysis engine in SQL Server with an Excel user-interface. Wrote all the SQL code that loads mail recipients, matches them to mail respondents, and reports response rates via an OLAP cube with more than 20 demographic and marketing dimensions. This reporting and analysis tool was in use for at least seven years after I built it.
- Built the “Churn Toaster”: An OLAP-style SQL Server application providing visibility into the churn rates during individual calendar months, allowing users to explore each month’s churn along a variety of dimensions (acquisition channel or partner, offer, customer tenure, payment method, and voluntary vs involuntary churn).