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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 362
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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. But it is not routine.

Metrics 156
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Higher-ed CIOs embrace academia’s AI challenges

CIO Business Intelligence

We developed a model to predict student outcomes based on metrics from historical evidence,” he says. “We We expected a couple thousand interactions when we implemented it. We’ve done a lot of experimentation on these adaptive tools that use AI,” says Ventimiglia. But we wound up with over 100,000 the first summer.

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Variance and significance in large-scale online services

The Unofficial Google Data Science Blog

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

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The AIgent: Using Google’s BERT Language Model to Connect Writers & Representation

Insight

There was only one problem: literary agents, the gatekeepers of the publishing industry, kept rejecting the book?—?often Using nothing more than a book’s synopsis, the AIgent can surface similar books, genre tags, and sales proxies. Data Collection The AIgent leverages book synopses and book metadata.

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Analytics On The Bleeding Edge: Transforming Data's Influence

Occam's Razor

The other dimension to consider is most Analtyics teams kick into gear after the campaign is concluded, after the customer interaction has taken place in the call center, and after the funds budgeted have already been spent. The benchmark for the beautiful metric AVOC is 15.3%. More shouting is not really better – and it is expensive!

Analytics 131
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Web Analytics: An Hour A Day

Occam's Razor

I am thrilled to say that my book Web Analytics: An Hour A Day has been published and is now widely available. It has been such an amazing journey to write the book, and for it to come up almost exactly a year after I started this blog. Damini, Chirag and now the book! :). Part One: The book (my side of the story, details).