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Bringing an AI Product to Market

O'Reilly on Data

In this article, we turn our attention to the process itself: how do you bring a product to market? Without clarity in metrics, it’s impossible to do meaningful experimentation. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business.

Marketing 362
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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

First, don’t do something just because everyone else is doing it – there needs to be a valid business reason for your organization to be doing it, at the very least because you will need to explain it objectively to your stakeholders (employees, investors, clients). Conduct market research. Test early and often.

Strategy 290
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Experimentation and Testing: A Primer

Occam's Razor

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers. Counter claims?

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Belcorp reimagines R&D with AI

CIO Business Intelligence

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

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13 IT resolutions for 2024

CIO Business Intelligence

He plans to scale his company’s experimental generative AI initiatives “and evolve into an AI-native enterprise” in 2024. This vision represents a fundamental shift, positioning AI as an integral part of our business fabric rather than just an add-on. That’s the case for Yi Zhou, CTO and CIO with Adaptive Biotechnologies.

IT 144
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3 force multipliers for digital transformation

CIO Business Intelligence

While many organizations are successful with agile and Scrum, and I believe agile experimentation is the cornerstone of driving digital transformation, there isn’t a one-size-fits-all approach. billion by 2028 , rising at a market growth of 20.3% Apply agile when developing low-code and no-code experiences.

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Five Data Analytics Mistakes Marketers Make (And How to Avoid Them)

Sisense

If marketing were an apple pie, data would be the apples — without data supporting your marketing program, it might look good from the outside, but inside it’s hollow. In a recent survey from Villanova University, 100% of marketers said data analytics has an essential role in marketing’s future.