CIO Business Intelligence

FEBRUARY 14, 2024

People aren’t going back and decluttering because there’s no cost to that — except in your risk profile and your decreased search performance,” says Buckley. The same issues were revealed when Microsoft launched Delve, and before that when the FAST integration brought powerful search to SharePoint in 2010. But it was.

IT 143

IT Metadata Data-driven Management 143

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. For example, imagine a fantasy football site is considering displaying advanced player statistics.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Ontotext

DECEMBER 30, 2022

9 years of research, prototyping and experimentation went into developing enterprise ready Semantic Technology products. We have exciting success stories, including the first and popular mission critical implementation of knowledge graphs – BBC’s website for the FIFA world cup in 2010.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

Ontotext

DECEMBER 30, 2022

9 years of research, prototyping and experimentation went into developing enterprise ready Semantic Technology products. We have exciting success stories, including the first and popular mission critical implementation of knowledge graphs – BBC’s website for the FIFA world cup in 2010.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

Occam's Razor

MARCH 23, 2010

For big success you'll need to have a Multiplicity strategy: So when you step back and realize at the minimum you'll also have to use one Voice of Customer tool (for qualitative analysis), one Experimentation tool and (if you want to be great) one Competitive Intelligence tool… do you still want to have two clickstream tools?

Analytics 118

Analytics Consulting Metrics Experimentation 118

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

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. Make experimentation cheap and understand the cost of bad decisions. This leads to the proliferation of post hoc hypotheses.

Experimentation 61

Experimentation Testing Statistics Metrics 61