Personalization has been touted as the holy grail of marketing programs, promising to tap into billions of customer interactions and demographic data to obtain new insights. The personalization concept has been the topic of many events, papers, and research studies and has spawned hundreds of technology solutions and services. Here, the author discusses how chief data officers can realize the personalization opportunities that massive amounts of available customer data and a variety of other big data sources can offer.
%0 Journal Article
%1 Earley17itpro2
%A Earley, Seth
%D 2017
%J IT Professional
%K 01841 ieee paper ai adaptive user interface information management
%N 6
%P 74--80
%R 10.1109/MITP.2017.4241471
%T The Problem of Personalization: AI-Driven Analytics at Scale
%V 19
%X Personalization has been touted as the holy grail of marketing programs, promising to tap into billions of customer interactions and demographic data to obtain new insights. The personalization concept has been the topic of many events, papers, and research studies and has spawned hundreds of technology solutions and services. Here, the author discusses how chief data officers can realize the personalization opportunities that massive amounts of available customer data and a variety of other big data sources can offer.
@article{Earley17itpro2,
abstract = {Personalization has been touted as the holy grail of marketing programs, promising to tap into billions of customer interactions and demographic data to obtain new insights. The personalization concept has been the topic of many events, papers, and research studies and has spawned hundreds of technology solutions and services. Here, the author discusses how chief data officers can realize the personalization opportunities that massive amounts of available customer data and a variety of other big data sources can offer.},
added-at = {2018-01-15T16:03:09.000+0100},
author = {Earley, Seth},
biburl = {https://www.bibsonomy.org/bibtex/2dbee7a081a3eb22c4780fcf57f3173eb/flint63},
doi = {10.1109/MITP.2017.4241471},
file = {IEEE Digital Library:2017/Earley17itpro2.pdf:PDF},
groups = {public},
interhash = {39b7059138f8b2897e54a2d48cf2b242},
intrahash = {dbee7a081a3eb22c4780fcf57f3173eb},
issn = {1520-9202},
journal = {IT Professional},
keywords = {01841 ieee paper ai adaptive user interface information management},
month = {#nov#},
number = 6,
pages = {74--80},
timestamp = {2018-04-16T11:31:44.000+0200},
title = {The Problem of Personalization: {AI}-Driven Analytics at Scale},
username = {flint63},
volume = 19,
year = 2017
}