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Customer science: A new CIO imperative

CIO Business Intelligence

In your daily life, how many product/service interactions exceed your expectations? Science is defined by many as the rigorous and systematic identification and measurement of phenomena. Does your organization measure customer experience? On February 21, 2018, Snapchat lost $1.3 Think about it. How many even meet them?

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Top BOB Blog Posts of 2018: Data Science, Machine Learning and the Net Promoter Score

Business Over Broadway

All of my top blog posts of 2018 (most reads) are all related to data science, with posts that address the practice of data science, artificial intelligence and machine learning tools and methods that are commonly used and even a post on the problems with the Net Promoter Score claims. First, the “research” behind the NPS claims is flawed.

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Machine Learning Helps Social Media Marketers Earn Higher ROIs

Smart Data Collective

We talked about some of the AI-driven content generation tools that were available in 2018. You get instant feedback from customers and potential customers and use AI to engage with them more easily Social media is an excellent way to interact with customers, especially if you’re a small business.

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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

Following this, in 2002, it began delivering its knowledge to customers in online format, using dashboards and interactive reports that provided easier and faster access to data and analysis. According to Mohammed, the results of this digital transformation journey are measurable and impressive. js and React.js.

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

A properly set framework will ensure quality, timeliness, scalability, consistency, and industrialization in measuring and driving the return on investment. Newer methods can work with large amounts of data and are able to unearth latent interactions. Fractal’s 2018 Net Promoter Score is greater than 70.

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When models are everywhere

O'Reilly on Data

Many of the models you interact with are mediated through screens, and there’s no shortage of news about how many of us spend our lives glued to them. David Foster Wallace had the general structure of the user–product interaction correct. Let’s start by looking at how models impact us. SCREENS, FEEDBACK, AND “THE ENTERTAINMENT”.

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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., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.