Smart Data Collective

OCTOBER 17, 2022

Email marketing is the most acceptable way to give precise customer data, but you must guarantee your efforts aren’t wasted. Using data analytics help your email marketing strategies succeed. Data Analytics’ Importance in Email Marketing. Types of data analytics. Segmentation.

Marketing 128

Marketing Optimization Data Analytics Analytics 128

Rocket-Powered Data Science

JULY 30, 2018

Behavioral analytics (predictive and prescriptive). Agile analytics (DataOps). To illustrate and to motivate these emerging and growing developments in marketing, we list here some of the top Machine Learning trends that we see: Hyper-personalization (SegOne context-driven marketing).

Machine Learning 199

Machine Learning Marketing Behavioral Analytics IoT 199

Rocket-Powered Data Science

AUGUST 22, 2021

CX has become increasingly data-informed and data-driven, with VoC data being one of the key data sources. Other data sources include purchase patterns, online reviews, online shopping behavior analytics, and call center analytics.

Data-driven 277

Data-driven Interactive Behavioral Analytics Machine Learning 277

datapine

MARCH 25, 2019

This is one of the most important data analytics techniques as it will shape the very foundations of your success. To help you ask the right things and ensure your data works for you, you have to ask the right data analysis questions. Harvest your data. A data analytics methodology you can count on.

Key Performance Indicator 217

Key Performance Indicator Statistics Big Data Visualization 217

CIO Business Intelligence

MAY 20, 2024

From AI and data analytics, to customer and employee experience, here’s a look at strategic areas and initiatives IT leaders expect to spend more time on this year, according to the State of the CIO. A mix of IT mainstays and business differentiators, these “top-of-mind” projects hint at where IT is headed in years ahead.

IT 142

IT Risk Management Machine Learning Risk 142

Smart Data Collective

APRIL 20, 2023

It unifies the capabilities of several different tools, such as: Sandboxing — to test the code in an isolated environment and determine whether it’s malicious User and Entity Behavior Analytics (UEBA) — for identifying anomalies Network Detection and Response (NDR) — to detect known threats within the network of a company Next-Gen SIEM is suitable (..)

Machine Learning 126

Machine Learning Reporting Behavioral Analytics Risk 126

bridgei2i

JULY 14, 2021

Traditionally, retailers tend to use multiple siloed systems to store, manage, and analyze data separately. Leveraging data analytics has enabled retailers to easily unify and connect data from different sources and produce actionable insights. Customer Behavior Analytics.

Analytics 52

Analytics Behavioral Analytics Forecasting Sales 52