The eMetrics videos are filmed at the eMetrics Marketing Optimization Summit and brought to you by Online Behavior.
The web/digital analytics industry is still young, very young in the scheme of things. When compared to the discipline of statistics with hundreds of years of development, there is so much that web analytics professionals can learn.
Andrew Bakonyi and Gary Angel discuss the uses of online customer surveys in gaining insights into customers and sales at HP. They give examples of how these surveys have affected company policy, and explain why online surveys are often a better choice than behavioral analytics, particularly for issues of customer analysis and sentiment.
Chris Goward, Co-Founder & President of WiderFunnel Marketing Optimization, presents tips and cases studies on Conversion Optimization and describes how to get results.
Using examples from LinkedIn's dataset, as well as from day-to-day life, Scott Nicholson discusses the process of going from a dataset to helping companies, consumers, and the world as a whole.
Jack Koch of Electronic Arts describes how his company built an advertiser analytics system which is scalable, cross-platform, and actionable.
Professor Peter Fader (Wharton), Dr. Sharron Silva, and Janet Couperthwaite discuss the process of getting the best data analytics program possible to encourage Red Cross disaster donors to become sustaining donors.
Feres Alhlou, the founder of E-Nor, discusses some of the more useful optimization tools that have come out recently: ShufflePoint, a data integration hub; SiteApps for SEO on Google Analytics and Qualaroo (formerly Kissinsights).
Hila Strong describes the basics of optimization, explaining that the intent of the customer is key, and that ideally, optimization functions to help the customer achieve their goals.
To really get insight into customer behavior, it's important to gather data across all of the channels, digital and offline, integrate the data automatically, and give marketers and salespeople a clear image of the customer.
April Wilson explains that more data and more processing doesn't necessarily translate into better results. She believes that the crucial factor is critical thinking on the part of the data analyst/scientist.