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Using IBM Watson to Answer Two Important Questions about your Customers

Business Over Broadway

For our example, to answer our questions, we need to look at two types of analytics: 1) Descriptive and 2) Predictive. Descriptive analytics are used to indicate the current state of the world. I added the three loyalty metrics to the model. The next step is to analyze the data. Low correlations (near 0.o)

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5 Sources of Data for Customer Analytics and Their Benefits

Smart Data Collective

Therefore, you need sophisticated customer analytics to analyze complex customer behavior. This article will go over the concept of customer service analytics and some of the uses and advantages it could provide to a business. What Is Customer Service Analytics? Customer Experience Analytics. Conclusion.

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What Is The Difference Between Business Intelligence And Analytics?

datapine

Try our professional BI and analytics software for 14 days free! In an article tackling BI and Business Analytics, Better Buys asked seven different BI pros what their thoughts were on the difference between business intelligence and analytics. Try our professional BI and analytics software for 14 days free!

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Themes and Conferences per Pacoid, Episode 10

Domino Data Lab

Note that there’s not enough room in an article to cover these presentations adequately so I’ll highlight the keynotes plus a few of my favorites. Then calculate the variance divided by the mean to construct a metric for noise in decision-making. For kicks, try calculating this kind of metric within your own organization.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was. Experts say that BI and data analytics makes the decision-making process 5x times faster for businesses. Let’s look at our first use case.

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What Is Embedded Analytics?

Jet Global

Business End-User Benefits Embedding analytics into essential applications makes analytics more pervasive. As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. Visual Analytics Users are given data from which they can uncover new insights.