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 362

Marketing Experimentation Metrics Testing 362

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

O'Reilly on Data

MARCH 18, 2020

It seems as if the experimental AI projects of 2019 have borne fruit. Two functional areas—marketing/advertising/PR and operations/facilities/fleet management—see usage share of about 20%. However, organizations need to address important data governance and data conditioning to expand and scale their AI practices. [1]

Enterprise 314

Enterprise Deep Learning Data Governance Risk 314

CIO Business Intelligence

MARCH 21, 2022

According to data from Robert Half’s 2021 Technology and IT Salary Guide, the average salary for data scientists, based on experience, breaks down as follows: 25th percentile: $109,000 50th percentile: $129,000 75th percentile: $156,500 95th percentile: $185,750 Data scientist responsibilities.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

CIO Business Intelligence

MAY 16, 2023

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data.

Advertising 105

Advertising Recreation/Entertainment Experimentation Enterprise 105

Occam's Razor

OCTOBER 19, 2010

Move from a data collection obsession and develop a crush on data analysys. Experimentation and Testing Tools [The "Why" – Part 1]. Before you use any of these tools please please please read this blog post: The Definitive Guide To (8) Competitive Intelligence Data Sources ]. Three tools.

Analytics 136

Analytics Testing Measurement Optimization 136

Occam's Razor

SEPTEMBER 15, 2014

A majority of YouTube consumption is on mobile, yet if there is an advertising or content strategy inside a company for YouTube it rarely accommodates for this reality. In this post we will look mobile sites first, both data collection and analysis, and then mobile applications. Media-Mix Modeling/Experimentation.

Metrics 143

Metrics Reporting Analytics Marketing 143