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Bringing an AI Product to Market

O'Reilly on Data

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
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Measuring Incrementality: Controlled Experiments to the Rescue!

Occam's Razor

We have to do location-based advertising to squarefour people. We can't forget Mobile advertising. Smart Marketers work hard to ensure that their digital marketing and advertising efforts are focused on the most impactful portfolio of channels. Having read this post what might be the biggest downside to experimentation?

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Digital listening reveals 3 leading innovation drivers

CIO Business Intelligence

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Metaverse Opportunities Advertising: Advertisers see the metaverse as a powerful way to connect with and reach consumers.

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Robust Experimentation and Testing | Reasons for Failure!

Occam's Razor

Since you're reading a blog on advanced analytics, I'm going to assume that you have been exposed to the magical and amazing awesomeness of experimentation and testing. And yet, chances are you really don’t know anyone directly who uses experimentation as a part of their regular business practice. Wah wah wah waaah.

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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning.

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Expectations vs. reality: A real-world check on generative AI

CIO Business Intelligence

Pilots can offer value beyond just experimentation, of course. McKinsey reports that industrial design teams using LLM-powered summaries of user research and AI-generated images for ideation and experimentation sometimes see a reduction upward of 70% in product development cycle times. What are you measuring?

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How to Set AI Goals

O'Reilly on Data

Customer stakeholders are the people and companies that advertise on the platform, and are most concerned with ROI on their ad spend. Technical sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., PyTorch, TensorFlow, reinforcement learning, self-supervised learning).