O'Reilly on Data

MAY 14, 2020

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

Management 363

Management Experimentation B2B Machine Learning 363

Occam's Razor

JUNE 6, 2007

I am thrilled to say that my book Web Analytics: An Hour A Day has been published and is now widely available. Five Reasons Why You Should Buy Web Analytics: An Hour A Day: Web Analytics: An Hour A Day for the first time provides a Practitioner's in the trenches perspective on web analytics. There I said it.

Analytics 60

Analytics Metrics Marketing Dashboards 60

Occam's Razor

SEPTEMBER 15, 2014

Remember, when someone says mobile analytics, first ask the clarifying question: Do you mean mobile application or mobile website ? Then approach each separately (even though there are tools like Google Analytics that will do both). Media-Mix Modeling/Experimentation. It will save you hours and hours of time, effort and focus.

Metrics 141

Metrics Reporting Analytics Marketing 141

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. Companies that succeed at machine learning tend to build on those existing analytics use cases. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

MARCH 23, 2010

There are more mistruths and F U D about Web analytics out there than I think is reasonable. Web Analytics, this beautiful child, was born just the other day in the midst of tumultuous times, quite literally, when everything changes every day. Here are ten web analytics ground truths… 1. Part of it fueled by Vendors.

Analytics 118

Analytics Consulting Metrics Experimentation 118

Occam's Razor

OCTOBER 19, 2010

What is the first thing you want when you think about web analytics? recommending tools for the complete web analytics 2.0 Disclosure:] I am the co-Founder of Market Motive Inc and the Analytics Evangelist for Google. Web Analytics 2.0. This blog post is about web analytics 2.0. Of course tools. Don't be.

Analytics 135

Analytics Testing Measurement Optimization 135

Cloudera

JUNE 6, 2019

We sometimes refer to this as splitting “dev/test” from “production” workloads, but we can generalize the approach by referring to the overall priority of the workload for the business. Lakshmi Randall is Director of Product Marketing at Cloudera, the enterprise data cloud company. 3) By workload priority.

Metadata 86

Metadata Data Lake Strategy Optimization 86

Occam's Razor

AUGUST 13, 2012

A couple weeks back I'd requested the nice folks following me on Google+ and Facebook to submit their most important digital marketing and analytics questions. The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

datapine

JANUARY 31, 2022

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. Why Is Business Intelligence So Important?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Occam's Razor

JULY 18, 2011

A secondary thing would be to ensure, or your mom will really be mad, that *every* link in your email is tagged with campaign tracking parameters your web analytics solution needs (without this you can’t do the B and O analysis). Most good email providers will do this automatically for whatever web analytics tool you use. That is okay.

Metrics 137

Metrics Marketing Measurement Cost-Benefit 137

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

by ERIC HOLLINGSWORTH A large part of the data we data scientists are asked to analyze was not collected with any specific analysis in mind, or perhaps any particular purpose at all. This post describes the analytical issues which arise in such a setting, and what the data scientist can do about them.

Experimentation 61

Experimentation Testing Statistics Metrics 61

Occam's Razor

JANUARY 7, 2014

Every indicator we have is that companies are investing more in every facet of analytics. There is an analytics ladder of awesomeness each company needs to climb, and it just takes time. First… it is important to realize that big data's big imperative is driving big action. You know what your Return on Analytics is!

Data-driven 140

Data-driven Consulting Reporting Marketing 140

Occam's Razor

APRIL 29, 2013

Here's why… Real-time data is very expensive. It is expensive from a systems/platforms/data processing/data reporting perspective. You end up paying substantial amounts of money to your analytics/big data vendor – for questionable value. PPS: I've mentioned one exception in the past.

Marketing 166

Marketing Metrics Advertising Measurement 166

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Like this blog, it will be particularly relevant for those who are in digital analytics and digital marketing. Years and years of practice with R or "Big Data."

Marketing 136

Marketing Analytics Machine Learning Strategy 136