Smart Data Collective

MARCH 11, 2022

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. Analyzing the Reasons of Customer Churn. Customer Retention Analytics.

Customer Analytics 130

Customer Analytics Analytics Key Performance Indicator Big Data 130

Occam's Razor

FEBRUARY 7, 2011

Two other quick things… Churn is a term most closely associated with customers you have acquired (and then failed to retain) and not so much to "fly by night" Visitors on your site. The latter, except in rare cases, is hard to do predictive analytics on unless you are a stagnant business. or non-U.S.),

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

Business Over Broadway

SEPTEMBER 27, 2018

Reducing customer churn requires you to know two things: 1) which customers are about to churn and 2) which remedies will keep them from churning. In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

AWS Big Data

MARCH 26, 2024

It provides strong consistency across datasets, allowing organizations to derive reliable, comprehensive insights about their customers, which is essential for informed decision-making. Amazon Redshift offers real-time insights and predictive analytics capabilities for analyzing data from terabytes to petabytes.

Data Strategy 91

Data Strategy Strategy Data Warehouse Prescriptive Analytics 91

FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.

Statistics 52

Statistics Data mining Visualization Reporting 52

Domino Data Lab

JULY 28, 2021

They have enabled new cross-industry applications, such as in customer analytics and fraud detection. Common examples include creating customer segments and anomaly detection. Reinforcement learning focuses on optimizing a specific decision. Common examples include recommendation engines and self-driving cars.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

DataRobot

DECEMBER 8, 2021

As noted in this report from Forrester®, “four out of five global data and analytics decision makers say that their firms want to become more data-driven and perform more advanced predictive analytics and artificial intelligence projects. Marketing Mix Optimization. AI in Customer Analytics: Tapping Your Data for Success.

Customer Analytics 97

Customer Analytics Analytics Advertising Data-driven 97