Cost-Benefit Data Collection Experimentation Measurement 
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.
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.
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CIO Business Intelligence
AUGUST 16, 2023
“Waterfall projects may seem easier to understand from an overall point of view, but if it’s about ongoing innovation together with a customer to bring out new effects and benefits, then we need to be iterative even in complex projects,” she says. “At This leads to environmental benefits and fewer transports.
Smart Data Collective
JULY 9, 2023
There are many ways that data analytics can help e-commerce companies succeed. One benefit is that they can help with conversion rate optimization. Collecting Relevant Data for Conversion Rate Optimization Here is some vital data that e-commerce businesses need to collect to improve their conversion rates.
Occam's Razor
JULY 18, 2011
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! For everything you do it is important to measure your effectiveness of all three phases of your effort: Acquisition. You’re trying to measure how well you are doing to: Send emails.
The Unofficial Google Data Science Blog
OCTOBER 12, 2017
Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation.
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. These measurement-obsessed companies have an advantage when it comes to AI.
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