Predictive Analytics World – coming Feb 16-17 to San Francisco – is bursting at the seams with compelling, detailed, revealing case studies from brand-named companies.
For a quick, meaty snapshot of PAW’s agenda, as well as a review of the hottest work going on in predictive analytics, check out my recent webinar:
Archived BetterManagement webcast: “Predictive Analytics: Hot Trends for 2010”
Available to view any time, on-demand: Click here to access the webcast now
Businesses around the globe have deployed analytics for the business impact it delivers. Across many industries and departments, predictive analytics has been applied to address a vast range of business challenges. What’s next?
Trend #1: Innovative applications
Trend #2: New data sources
Trend #3: New methodologies (e.g., uplift – see below)
Most of this webinar is spent on the first: innovative applications. Data-driven models predict new things such as the reliability of hardware and corporate processes alike, and drive all kinds of organizational decisions, for the likes of air traffic management, military operations, mobile consumer applications, and startup investment strategy.
Click here for more information and to view the webinar
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One of Trend #3’s hottest tickets, uplift modeling (a.k.a., net lift modeling), will covered by this keynote address at February’s PAW:
“Response Modeling is the Wrong Modeling: Maximize Impact With Net Lift Modeling”
Keynote Speaker: Kim Larsen of Charles Schwab
The true effectiveness of a marketing campaign isn’t response rate! It’s the incremental impact – that is, additional revenue directly attributable to the campaign that would not otherwise have been generated. Yet traditional targeting criteria are often designed to find clients that are interested in the product, but would have bought it whether or not they received a promotion. In such cases, the incremental impact is insignificant and the marketing dollars could have been spent elsewhere.
Net Lift Models are designed to maximize incremental impact by targeting the undecided clients that can be motivated by marketing. These “swing customers” are akin to the swing states of a presidential election; data miners could learn a lot from presidential campaigns.
Click here for the complete keynote description