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Practice paper

Advanced next best offer marketing using predictive analytics

Justin Croft
Applied Marketing Analytics: The Peer-Reviewed Journal, 1 (4), 363-376 (2015)
https://doi.org/10.69554/TBBQ9363

Abstract

Next best offer (NBO) marketing, also known as next best action, prescribes the marketing message with the highest likelihood of success and delivers that next best message within an integrated, measurable marketing environment. This paper proposes a framework for marketers to use in building and launching a successful NBO solution within their own organisation. Topics addressed include ideal analytics team structure, key stakeholder alignment issues, marketing offer types, the predictive analytics technical platform and the importance of multi-channel integrations within a customer experience.

Keywords: next best offer; predictive analytics; model; multi-channel

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Author's Biography

Justin Croft leads a consulting practice around predictive analytics and the application of predictive models to solve business problems. Focusing primarily on customer analytics, optimisation and predictive maintenance, he is responsible for all design and delivery of predictive analytics solutions for Revelwood clients worldwide. Previously, Justin led the big data and analytics team at C Spire Wireless, where he was responsible for driving gross and net sales using predictive analytics. He was recognised by both IBM and InformationWeek for having the most innovative business analytics project of 2014, and is the recipient of the Association of National Advertisers’ 2014 Marketing Analytics Leadership Award. Justin holds two degrees from the University of Mississippi, including a Masters of Business Administration.

Citation

Croft, Justin (2015, October 1). Advanced next best offer marketing using predictive analytics. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 1, Issue 4. https://doi.org/10.69554/TBBQ9363.

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cover image, Applied Marketing Analytics: The Peer-Reviewed Journal
Applied Marketing Analytics: The Peer-Reviewed Journal
Volume 1 / Issue 4
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