The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Occam's Razor

AUGUST 22, 2011

" ~ Web Metrics: "What is a KPI? " + Standard Metrics Revisited Series. "Engagement" Is Not A Metric, It's An Excuse. Defining a "Master Metric", + a Framework to Gain a Competitive Advantage in Web Analytics. Build A Great Web Experimentation & Testing Program.

KPI 124

KPI Metrics Measurement ROI 124

Occam's Razor

JULY 24, 2018

work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more. The Implications of Complexity.

Analytics 93

Analytics Metrics Strategy Measurement 93

CIO Business Intelligence

JUNE 27, 2022

I do still contribute to open-source projects and when I can I try to contribute code to Sentry, but definitely not as much as I want. Tyson: You’re coming up to two years since you added Sentry’s ability to monitor for performance which has some pretty fine-grained metrics in terms of identifying where bottlenecks are located in code.

Software 115

Software Experimentation Testing Marketing 115

CIO Business Intelligence

MAY 1, 2024

Pilots can offer value beyond just experimentation, of course. McKinsey reports that industrial design teams using LLM-powered summaries of user research and AI-generated images for ideation and experimentation sometimes see a reduction upward of 70% in product development cycle times. Now nearly half of code suggestions are accepted.

Cost-Benefit 136

Cost-Benefit Metrics Insurance Measurement 136

O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. This is significant and definitely worth watching over the next few months. But is application deployment the right metric for maturity? Bottlenecks to AI adoption. Maturity by Continent.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

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

OCTOBER 21, 2013

You can read this post to learn how these tools collect data: The Definitive Guide To (8) Competitive Intelligence Data Sources. And of course our Acquisition, Behavior, Outcome metrics. Controlled experimentation. I really loved having this data. See Page Value there? Still non-individualized. But, it is is something.

Optimization 154

Optimization Reporting Experimentation Metrics 154

O'Reilly on Data

OCTOBER 13, 2020

This distinction assumes a slightly different definition of debugging than is often used in software development. Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics.

Management 244

Management Metrics Machine Learning Modeling 244

datapine

FEBRUARY 4, 2020

But first, we will start with a basic definition and some tips on creating these kinds of reports. Structure your metrics. As with any report you might need to create, structuring and implementing metrics that will tell an interesting and educational data-story is crucial in our digital age. Let’s dig deeper. click to enlarge**.

Reporting 280

Reporting Marketing Advertising Metrics 280

Occam's Razor

JULY 18, 2011

You must use metrics that are unique to the medium. Ready for the best email marketing campaign metrics? So for our email campaign analysis let’s look at metrics using that framework. Optimal Acquisition Email Metrics. Allow me to rush and point out that this metric is usually just directionally accurate.

Metrics 137

Metrics Marketing Measurement Cost-Benefit 137

datapine

MAY 20, 2020

To put the power of CRM software (or customer relationship management dashboard software) into a living, breathing, real-world perspective, we’ll explore CRM dashboards in more detail, starting with basic definitions of such dashboards and reports while considering how you can use CRM dashboard software to your business-boosting advantage.

Dashboards 265

Dashboards Reporting KPI Visualization 265

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). In 480 pages the book goes from from beginner's basics to a advanced analytics concepts. Clicks and outcomes.

Analytics 60

Analytics Metrics Marketing Dashboards 60

Occam's Razor

FEBRUARY 26, 2008

1: Implement a Experimentation & Testing Program. # 1: Implement a Experimentation & Testing Program. Experimentation and Testing: A Primer. Build A Great Web Experimentation & Testing Program. # Be it for in vogue metrics like Conversion Rates or for metrics that should be in vogue like Abandonment Rates.

Management 68

Management Experimentation Testing Strategy 68

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. A complete DataOps program will have a unified, system-wide view of process metrics using a common data store. However, the rush to rebrand existing products with a DataOps message has created some marketplace confusion.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Occam's Razor

DECEMBER 9, 2009

They also tend to generate inefficiencies (everyone's doing their own thing after all) be it with tools or work or metrics definitions or testing platforms or… Decentralized organizations optimize for a local maxima and it happens all the time that while individual divisions in a company win, that the company as a whole loses.

Analytics 95

Analytics Data-driven Marketing Sales 95

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. Another pattern that I’ve seen in good PMs is that they’re very metric-driven.

Management 110

Management Machine Learning Experimentation Metrics 110

Corinium

APRIL 25, 2019

Yes, definitely! Life insurance needs accurate data on consumer health, age and other metrics of risk. It definitely depends on the type of data, no one method is always better than the other. Yes, definitely, the only questions in my mind are when and how it comes about. But I’ll give an example in favour of each.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Occam's Razor

NOVEMBER 12, 2006

Stepping back for a moment here is the definition of conversion rate that is recommended: Conversion Rate = Outcomes / Unique Visitors. Focus on the Why (use Surveys or Lab Usability or Experimentation & Testing for example). Is Real Conversion Rate metric a good one? Another reason is that we over estimate what is possible.

Measurement 99

Measurement Analytics Optimization Marketing 99

Occam's Razor

FEBRUARY 28, 2017

To ensure customer delight was delivered in a timely manner, it was also decided that Average Call Time (ACT) would now be The success metric. The success metric, ACT, did go down. That ACT was an activity metric was terrible – if you have a The success metric, it should always be an outcome metric. Another issue.

Key Performance Indicator 106

Key Performance Indicator Metrics Measurement Advertising 106

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

The DS team needed an explicit definition of video quality. They agreed to base their definition on the evaluation of trained raters. Most agreed that Like Rate of a video on the site was in fact a reasonable proxy for this definition of video content quality. We start proxying this measurement via a rating task. Finland).

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

AWS Big Data

JANUARY 24, 2023

The utility for cloning and experimentation is available in the open-sourced GitHub repository. It contains references to data that is used as sources and targets in AWS Glue ETL (extract, transform, and load) jobs, and stores information about the location, schema, and runtime metrics of your data.

Data Architecture 65

Data Architecture Metadata Data Lake Snapshot 65

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

Despite a very large number of experimental units, the experiments conducted by LSOS cannot presume statistical significance of all effects they deem practically significant. The result is that experimenters can’t afford to be sloppy about quantifying uncertainty. In statistics, such segments are often called “blocks” or “strata”.

Experimentation 40

Experimentation Metrics Statistics Measurement 40

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. Brace yourselves for impact. Taking a pulse.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Occam's Razor

AUGUST 12, 2013

In a recent post, Multi-Channel Attribution: Definitions, Models and a Reality Check , I outlined three distinct attribution challenges. From all my experimentation I've found that taking out the last channel (whichever one it is) causes a material impact on the conversion process, so it gets a "good amount of credit."

Modeling 161

Modeling Optimization Marketing Interactive 161

Domino Data Lab

MAY 8, 2019

In contrast, some researchers who are exploring the definitions, possibilities, and limitations of model interpretation point toward more comprehensive views. There’s no one-size-fits-all definition of what’s required across all verticals. Let’s look at two issues, both more social than technical, that bubble to the top of the list.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

MARCH 23, 2010

Because every tool uses its own sweet metrics definitions, cookie rules, session start and end rules and so much more. If you don't kill 25% of your metrics each year, you are doing something wrong. Why do you think introducing a completely different set of numbers is going to make your life easier? Likely not.

Analytics 118

Analytics Consulting Metrics Experimentation 118

Occam's Razor

AUGUST 13, 2012

Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. That means: All of these metrics are off. This is exactly why the Page Value metric (in the past called $index value) was created. Pick metrics that matter. Hopefully soon! Three things.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

By definition, it is hard to disentangle causes and effects in these settings because it is rarely possible to isolate all relevant factors. It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

Occam's Razor

FEBRUARY 7, 2011

But each keyword gets "credit" for other metrics. I have personally had a lot of success using Controlled Experimentation techniques, such as, say, Media Mix Modeling, to understand both current available demand and also segment conversion effectiveness. And this has to be a continuous approach and not discreet.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

Occam's Razor

MAY 27, 2015

It is being hyper-conservative when it comes to creativity and experimentation because of quant-issues. Definitely buy my data books! :). This will definitely get me on the wrong side of many thought leaders in the mobile space, indeed even in the digital space. Please don't have a data-first strategy. And innovation.

Marketing Analytics 153

Marketing Analytics Marketing Analytics Advertising 153

Occam's Razor

OCTOBER 19, 2010

Given the definition above, I am a firm believer in Multiplicity. Mongoose Metrics ~ ifbyphone. I know Mongoose Metrics a bit more and have been impressed with their solution and evolution over the last couple of years. Experimentation and Testing Tools [The "Why" – Part 1]. Second Bit Of Context. Multiplicity.

Analytics 135

Analytics Testing Measurement Optimization 135

Occam's Razor

JANUARY 7, 2014

Before we go too deep, let's get a couple of definitions right first. They are generic mash-ups that tailor to almost no one's needs, and more often than not contain awful things like nine not-really-thought out metrics for one dimension in a report. Pick hard metrics to designate as your key performance indicators.

Data-driven 140

Data-driven Consulting Reporting Marketing 140

Occam's Razor

NOVEMBER 2, 2015

Success Metrics. In my Oct 2011 post, Best Social Media Metrics , I'd created four metrics to quantify this value. I believe the best way to measure success is to measure the above four metrics (actual interaction/action/outcome). It can be a brand metric, say Likelihood to Recommend. It is not that hard.

B2B 167

B2B Metrics Testing Recreation/Entertainment 167

O'Reilly on Data

MAY 11, 2020

It predates recommendation engines, social media, engagement metrics, and the recent explosion of AI, but not by much. The Entertainment” is not the result of algorithms, business incentives and product managers optimizing for engagement metrics. In a long-term sense, definitely not. Some of these have up to 66 million views.

Modeling 190

Modeling Advertising Recreation/Entertainment Metrics 190