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Bringing an AI Product to Market

O'Reilly on Data

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 361
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What LinkedIn learned leveraging LLMs for its billion users

CIO Business Intelligence

So the social media giant launched a generative AI journey and is now reporting the results of its experience leveraging Microsoft’s Azure OpenAI Service. Fits and starts As most CIOs have experienced, embracing emerging technologies comes with its share of experimentation and setbacks.

IT 139
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Do You Need a DataOps Dojo?

DataKitchen

Centralizing analytics helps the organization standardize enterprise-wide measurements and metrics. With a standard metric supported by a centralized technical team, the organization maintains consistency in analytics. Central DataOps process measurement function with reports.

Metrics 243
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 156
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eCommerce Brands Use Data Analytics for Conversion Rate Optimization

Smart Data Collective

One report found that global e-commerce brands spent over $16.7 Understanding E-commerce Conversion Rates There are a number of metrics that data-driven e-commerce companies need to focus on. It is a crucial metric that provides priceless information about your website’s ability to transform visitors into paying customers.

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Digital transformation’s fundamental change management mistake

CIO Business Intelligence

For example, KPMG reports that 51% of technology executives have not seen an increase in performance or profitability from digital transformation investments. Unfortunately, the business impact of many digital transformations continues to fall short of expectations.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.