Skip to main content
Mobile
  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations
HS Talks HS Talks
Subjects  
Search
  • Notifications
    Notifications

    No current notifications.

  • User
    Welcome Guest
    You have Limited Access The Business & Management Collection
    Login
    Get Assistance
    Login
    Forgot your password?
    Login via your organisation
    Login via Organisation
    Get Assistance
Finance, Accounting & Economics
Global Business Management
Management, Leadership & Organisation
Marketing & Sales
Strategy
Technology & Operations
Practice paper

More than science fiction: Using artificial intelligence and machine-learning techniques to supercharge your marketing

Korey Thurber
Applied Marketing Analytics: The Peer-Reviewed Journal, 3 (3), 199-205 (2017)
https://doi.org/10.69554/TIPT1765

Abstract

With the rise of data creation, channel proliferation and technologies, today’s marketers struggle to find actionable insights to optimise their marketing spend. In the past few years, machine learning — a form of artificial intelligence — has come to the marketer’s aid by finding patterns, deriving insights and making predictions from tremendous amounts of data. This paper analyses machine-learning capabilities, providers and applicability as they relate to marketing.

Keywords: machine learning; artificial intelligence; analytics; Big Data; predictive analytics; business intelligence

The full article is available to subscribers to the journal.

Already a subscriber? Login or review other options.

Author's Biography

Korey Thurber is Chief Data and Analytics Officer for Harte Hanks, where he manages ideation, development and delivery for customer analytics and data solutions. With more than 20 years’ experience managing large international teams of data scientists, analysts and data solutions providers. Korey has helped many brands adapt and integrate analytics to develop, execute and optimise marketing strategies across diverse online and offline media. His extensive knowledge and experience make him a valuable asset for many clients across multiple industry verticals.

Citation

Thurber, Korey (2017, August 8). More than science fiction: Using artificial intelligence and machine-learning techniques to supercharge your marketing. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 3, Issue 3. https://doi.org/10.69554/TIPT1765.

Options

  • Download PDF
  • Share this page
    Share This Article
    Messaging
    • Outlook
    • Gmail
    • Yahoo!
    • WhatsApp
    Social
    • Facebook
    • X
    • LinkedIn
    • VKontakte
    Permalink
cover image, Applied Marketing Analytics: The Peer-Reviewed Journal
Applied Marketing Analytics: The Peer-Reviewed Journal
Volume 3 / Issue 3
© Henry Stewart
Publications LLP

The Business & Management Collection

  • ISSN: 2059-7177
  • Contact Us
  • Request Free Trial
  • Recommend to Your Librarian
  • Subscription Information
  • Match Content
  • Share This Collection
  • Embed Options
  • View Quick Start Guide
  • Accessibility

Categories

  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations

Librarian Information

  • General Information
  • MARC Records
  • Discovery Services
  • Onsite & Offsite Access
  • Federated (Shibboleth) Access
  • Usage Statistics
  • Promotional Materials
  • Testimonials

About Us

  • About HSTalks
  • Editors
  • Contact Information
  • About the Journals

HSTalks Home

Follow Us On:

HS Talks
  • Site Requirements
  • Copyright & Permissions
  • Terms
  • Privacy
  • Sitemap
© Copyright Henry Stewart Talks Ltd

Personal Account Required

To use this function, you need to be signed in with a personal account.

If you already have a personal account, please login here.

Otherwise you may sign up now for a personal account.

HS Talks

Cookies and Privacy

We use cookies, and similar tools, to improve the way this site functions, to track browsing patterns and enable marketing. For more information read our cookie policy and privacy policy.

Cookie Settings

How Cookies Are Used

Cookies are of the following types:

  • Essential to make the site function.
  • Used to analyse and improve visitor experience.

For more information see our Cookie Policy.

Some types of cookies can be disabled by you but doing so may adversely affect functionality. Please see below:

(always on)

If you block these cookies or set alerts in your browser parts of the website will not work.

Cookies that provide enhanced functionality and personalisation. If not allowed functionality may be impaired.

Cookies that count and track visits and on website activity enabling us to organise the website to optimise the experience of users. They may be blocked without immediate adverse effect.