DataRobot Blog

OCTOBER 4, 2022

The situation is even more challenging for companies in industries that use historical data to give them visibility into future operations, staffing, and sales forecasting. For this blog, we will be tackling a use case that forecasts sales across multiple retail stores in the U.S. The Dataset. All in One!

Forecasting 59

Forecasting Sales Data-driven Modeling 59

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. The biggest time sink is often around data collection, labeling and cleaning.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

JUNE 6, 2007

Experimentation & Testing (A/B, Multivariate, you name it). If you have no experience with Web Analytics then you'll learn what it is and the nitty gritty of data collection and core metrics such as Visits and Time on Site and Bounce Rate and Top Destinations etc. It is a book about Web Analytics 2.0.

Analytics 60

Analytics Metrics Marketing Dashboards 60

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. As data science work is experimental and probabilistic in nature, data scientists are often faced with making inferences.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 364

Marketing Experimentation Metrics Testing 364

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation.

Experimentation 62

Experimentation Testing Statistics Metrics 62

Occam's Razor

MARCH 23, 2010

Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. If you don't have a robust experimentation program in your company you are going to die. Oh and when I say Experimentation I don't mean testing button sizes (BOO!). Likely not.

Analytics 119

Analytics Consulting Metrics Experimentation 119

Occam's Razor

DECEMBER 12, 2016

You got me, I am ignoring all the data layer and custom stuff! But, at the end of the day presence of a Tag Manager communicates to me that the company is serious about data collection and data quality. with responsibility for every facet of the entire company's data collection, data reporting and data analysis.

Analytics 142

Analytics Data-driven Strategy Consulting 142

Occam's Razor

MAY 27, 2015

It is an investment in numerous report writers or data (puking) automation or hiring a small army in India or Philippines to do that, before investing in any smart Analyst. It is being hyper-conservative when it comes to creativity and experimentation because of quant-issues. Data is important.

Marketing Analytics 155

Marketing Analytics Marketing Analytics Advertising 155

Occam's Razor

APRIL 29, 2013

PS: The phrase "real-time data analysis" is an oxymoron. Real-time data is super valuable if zero human beings are involved from data collection to action being taken. Eight Silly Data Things Marketing People Believe That Get Them Fired. PPS: I've mentioned one exception in the past.

Marketing 166

Marketing Metrics Advertising Measurement 166

Insight

MARCH 12, 2020

sales of Cuckoo’s Calling increased by over 150,000 percent. With breaking this bottleneck in mind, I’ve used my time as an Insight Data Science Fellow to build the AIgent, a web-based neural net to connect writers to representation. Data Collection The AIgent leverages book synopses and book metadata.

Modeling 59

Modeling Metadata Publishing Sales 59