Corinium

JUNE 6, 2019

For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments. Also, design thinking should play a large role in analytics in terms of how it will benefit the organization and exactly how people will react to and adopt the resulting insights.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Occam's Razor

MAY 22, 2006

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers. Counter claims?

Experimentation 103

Experimentation Testing Optimization Measurement 103

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively. Pilots can offer value beyond just experimentation, of course.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

CIO Business Intelligence

MARCH 5, 2024

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. Microsoft is heavily investing in AI capabilities and workflow integrations, so CIOs should expect and plan for improved capabilities.

Cost-Benefit 123

Cost-Benefit Advertising Experimentation Software 123

datapine

FEBRUARY 4, 2020

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. That way you can choose the best possible metrics for your case. Regularly monitor your data. 1) Marketing CMO report.

Reporting 280

Reporting Marketing Advertising Metrics 280

Occam's Razor

AUGUST 12, 2013

than multi-channel attribution modeling. By the time you are done with this post you'll have complete knowledge of what's ugly and bad when it comes to attribution modeling. You'll know how to use the good model, even if it is far from perfect. Multi-Channel Attribution Models. Linear Attribution Model.

Modeling 161

Modeling Optimization Marketing Interactive 161

Occam's Razor

JULY 18, 2011

The only requirement is that your mental model (and indeed, company culture) should be solidly rooted in permission marketing. You just have to have the right mental model (see Seth Godin above) and you have to… wait for it… wait for it… measure everything you do! Just to ensure you are executing against your right mental model.

Metrics 137

Metrics Marketing Measurement Cost-Benefit 137

Occam's Razor

SEPTEMBER 15, 2014

They will need two different implementations, it is quite likely that you will end up with two sets of metrics (more people focused for mobile apps, more visit focused for sites). Media-Mix Modeling/Experimentation. Mobile content consumption, behavior along key metrics (time, bounces etc.) First, a quick techie lesson.

Metrics 141

Metrics Reporting Analytics Marketing 141

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. Other estimators, such as those based on matching and subclassification, may benefit from the balancing property, but the discussion of those estimators is postponed to a later post.

Statistics 44

Statistics Optimization Modeling Experimentation 44

CIO Business Intelligence

JULY 8, 2022

After transforming their organization’s operating model, realigning teams to products rather than to projects , CIOs we consult arrive at an inevitable question: “What next?” Splitting these responsibilities without a clear vision and careful plan, however, can spell disaster, reversing the progress begotten by a new operating model.

Cost-Benefit 121

Cost-Benefit Measurement Modeling Metrics 121

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. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges.

Management 110

Management Machine Learning Experimentation Metrics 110

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. I explain three different models (Online to Store, Across Multiple Devices, Across Digital Channels) and for each I've highlighted: 1. That means: All of these metrics are off.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

CIO Business Intelligence

FEBRUARY 3, 2023

More recently, The Royal Mint has evolved its business model in the face of declining cash usage, from its core business of coins and metal manufacturing through to bullion trading, a new consumer business and jewellery line, as well as tentative steps into digital gold and recycling e-waste. “We How do they benefit you?

IT 52

IT Experimentation Scorecard Digital Transformation 52

Corinium

APRIL 25, 2019

Life insurance needs accurate data on consumer health, age and other metrics of risk. Most enterprises in the 21st century regard data as an incredibly valuable asset – Insurance is no exception - to know your customers better, know your market better, operate more efficiently and other business benefits. That’s the reward.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

DataRobot Blog

FEBRUARY 15, 2023

In addition, it’s essential that models comply with regulations and treat customers fairly, making it more important than ever to monitor models in production. The cost of real estate has been a rollercoaster ride in this challenging macroeconomic climate. It is possible to manage the end-to-end AI lifecycle in one solution.

Modeling 52

Modeling Machine Learning Cost-Benefit Metrics 52

AWS Big Data

JULY 26, 2023

Exploring the vector engine’s capabilities Built on OpenSearch Serverless, the vector engine inherits and benefits from its robust architecture. To create the vector index, you must define the vector field name, dimensions, and the distance metric. The vector index supports up to 1,000 fields. The second is to initially provision a 0.5

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

AWS Big Data

NOVEMBER 14, 2023

With data streaming, you can power data lakes running on Amazon Simple Storage Service (Amazon S3), enrich customer experiences via personalization, improve operational efficiency with predictive maintenance of machinery in your factories, and achieve better insights with more accurate machine learning (ML) models.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

or "does this product change benefit users?" Interventional uncertainty : the gap between the true benefit of an intervention arising from a decision, and an evaluation of that benefit. It turns out, they have some mathematical models for how this might play out, so they could do this in silico. This is great.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Domino Data Lab

AUGUST 26, 2019

Data scientists, machine learning (ML) researchers, and business stakeholders have a high-stakes investment in the predictive accuracy of models. Data scientists and researchers ascertain predictive accuracy of models using different techniques, methodologies, and settings, including model parameters and hyperparameters.

Testing 79

Testing Modeling Machine Learning Metrics 79

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation. Worse, the community may act on these ambiguous explanations, incurring real costs. We sliced and diced the experimental data in many many ways.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. It will ultimately help them spot new business opportunities, cut costs, or identify inefficient processes that need reengineering.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. DataRobot is available on Azure as an AI Platform Single-Tenant SaaS, eliminating the time and cost of an on-premises implementation.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

CIO Business Intelligence

MAY 20, 2024

This knowledge, generated through observation, reflection, study, and social interaction, led to a new companywide policy: “Let the grinder warm up for 15 minutes,” resulting in millions of dollars of extra profit at no additional cost. Instead, companies should use metrics other than budget targets for rewards.

Management 109

Management Interactive Measurement Marketing 109

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. We data scientists now have access to tools that allow us to run a large numbers of experiments, and then to slice experimental populations by any combination of dimensions collected.

Experimentation 61

Experimentation Testing Statistics Metrics 61

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber’s DNA as an analytics company At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B. Presto’s cost-based query optimizer, dynamic filtering and extensibility through user-defined functions make it a versatile tool in Uber’s analytics arsenal.

OLAP 90

OLAP Data Lake Data-driven Snapshot 90

O'Reilly on Data

MAY 11, 2020

Not all models are created equal, however: they operate on different principles, and impact us as individuals and communities in different ways. To understand the menagerie of models that are fundamentally altering our individual and shared realities, we need to build a typology, a classification of their effects and impacts.

Modeling 190

Modeling Advertising Recreation/Entertainment Metrics 190