The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

The Unofficial Google Data Science Blog

JUNE 30, 2016

It should be noted that inverse probability weighting is not generally optimal (i.e., We do this by describing the methods in terms of loss functions whose expectation is optimized at the true value of the propensity score. In the presence of model misspecification, the estimator $hatpsi$ is inconsistent.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Rita Sallam

JULY 22, 2016

Like when Oracle acquired Hyperion in March of 2007, which set of a series of acquisitions –SAP of Business Objects October, 2007 and then IBM of Cognos in November, 2007. Reeboks made it possible for aerobics classes to become main stream beyond its dancer beginnings. In BI we have had our seminal moments too.

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. But it is not routine.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

The Data Visualisation Catalogue

AUGUST 15, 2019

Back in 2007, Harvard argued (in a review) that the customer experience was starting to spread into other areas of business. Actionable insights provide a better model for CXOs to use when improving the customer experience. This allowed for the better optimization of all marketing channels.

Visualization 47

Visualization Dashboards Interactive Marketing 47

Occam's Razor

MARCH 12, 2012

All the way back in 2007, I was evangelizing the value of moving away from the "small data" world of clickstream data to the "bigger data" world of using multiple data sources to make smarter decisions on the web. Here's the "bigger web analytics data" picture from 2007… Multiplicity!

Big Data 127

Big Data Data-driven Unstructured Data Marketing 127

Occam's Razor

AUGUST 22, 2011

Key To Your Digital Success: Web Analytics Measurement Model. Web Data Quality: A 6 Step Process To Evolve Your Mental Model. The Awesome Power of Visualization 2 -> Death and Taxes 2007. Podcast: Competitive Analysis Best Practices, Competency Judgement Model. Search Engine Optimization (SEO) Metrics & Analytics.

KPI 124

KPI Metrics Measurement ROI 124

Occam's Razor

SEPTEMBER 19, 2011

How do you get over the frustration of having done attribution modeling and realizing that it is not even remotely the solution to your challenge of using multiple media channels? We have to do Search Engine Optimization. We have to do Email Marketing. We have to do Paid Search. We have to have a robust Affiliate network.

Measurement 119

Measurement Advertising Testing Marketing 119

The Unofficial Google Data Science Blog

JULY 22, 2020

In practice, one may want to use more complex models to make these estimates. For example, one may want to use a model that can pool the epoch estimates with each other via hierarchical modeling (a.k.a. These MAB algorithms are great at maximizing reward when the models are perfectly specified and probabilities are accurate.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Grooper

AUGUST 19, 2019

ISL eliminates data literacy by modeling the way we learn spoken language. These requirements include fluency in: Analytical models. A classic example often cited is John Deere’s innovative investment in a new way of optimizing inventory called “direct de rivative estimation of non-stationary inventory.” Simulations.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Edwin Chen

MARCH 13, 2011

This is a summary of Bell and Koren’s 2007 Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights paper. Another way of thinking about this is that we are simply building a regression model. I’m now (very slowly) trying to clean up my notes and put them online. Bob likes Kate Winslet).

Optimization 40

Optimization Modeling Cost-Benefit Measurement 40

Domino Data Lab

FEBRUARY 4, 2019

Lately there’s been lots of dialog about bias in machine learning models, though considering the noise part of the equation is an important corollary. Problems with training ML models efficiently. Frédéric Kaplan, Pierre-Yves Oudeyer (2007). Plus, these models are being simulated through the use of neural networks.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Occam's Razor

FEBRUARY 7, 2011

The best option is to hire a statistician with experience in data modeling and forecasting. Brian Krick: Best way to measure and communicate "available demand" from available channels (social, search, display) for forecast modeling. Alex Cohen: How to optimize with sparse data! Please see the advice above. and finally 3.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

Occam's Razor

OCTOBER 15, 2012

I spend 70% of my time in the US and for those discussions I'm primary looking at speed (connection above), mobile penetration (yes, 2007 was the year of mobile!), Think of it as attribution modeling. :). Drive overall business outcomes by combining online and offline consumer touch points optimally.

Advertising 136

Advertising Marketing Strategy Insurance 136