In anticipation of their upcoming conference co-presentation, The Quest for Labeled Data: Integrating Human Steps, at Predictive Analytics World San Francisco, May 14-18, 2017, we asked Ashish Bansal, Senior Director, Data Science and John Schlerf, Data Scientist at Capital One, a few questions about their work in predictive analytics.
Q: In your work with predictive analytics, what behavior or outcome do your models predict?
Q: How does predictive analytics deliver value for your customers – what is one specific way in which it actively improves operational outcomes?
A: Customers expect their bank to know the merchants where they shop. By expanding that knowledge beyond just the merchant name, we can improve our customers’ brand perception and loyalty. This also lowers operational call center costs, as customers can access more details about where they made a purchase.
Q: Can you describe a quantitative result, such as the predictive lift of your model or the ROI of an analytics initiative?
A: We increased our library of known restaurants by over 10% in less than 1 week.
Q: What surprising discovery or insight have you unearthed in your data?
A: We were quite surprised by the vibrancy of the communities of micro-workers. They take real pride in their work, and deliver very high quality output.
Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.
A: Human judgement is often the best source of labeled data for training and testing complicated models. Collecting such data at scale can be daunting. This talk focuses on building automated data pipelines that integrate manual labeling steps.
Don’t miss Ashish and John’s conference co-presentation, The Quest for Labeled Data: Integrating Human Steps on Wednesday, May 17, 2017, from 11:15 am to 12:00 pm at Predictive Analytics World San Francisco. Click here to register to attend. Use Code PATIMES for 15% off current prices (excludes workshops).
By: Eric Siegel, Founder, Predictive Analytics World
Eric Siegel is the founder of Predictive Analytics World (www.pawcon.com) — the leading cross-vendor conference series consisting of 10 annual events in New York, Chicago, San Francisco, Washington DC, London, and Berlin — and the author of the award-winning book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die – Revised and Updated Edition, (Wiley, 2016).