Personalized Marketing Technology

Goals

To assess the current state of personalization in marketing technology, to identify key players and strategies, to look at specific strategies and implementations from the data management, decisioning, and delivery perspectives, as well as any details on the tech stacks involved.

Early Findings

PERSONALIZATION IN MARTECH

A quote in Social Media Today states, "marketers in 2020 have finally reached the 'tipping point' where scalable hyper-personalization of marketing activities is not only possible, but is rapidly becoming a requirement in order to stay up with evolving consumer trends"

CONSIDERATIONS IN PESONALIZATION STRATEGIES

  • Engagement — A 2017 study from Epsilon found that "80% of respondents indicated they are more likely to do business with a company if it offers personalized experiences and 90% indicated that they find personalization appealing."
  • Relevance — Get the right message delivered at the right time. "Consumers who believe personalized experiences are very appealing are ten times more likely to be a brand’s most valuable customer."
  • Brand Trust — personalization will work best when combined with brand trust. The Epsilon study indicates that "respondents who believe companies are doing very well on offering personalized experiences shop more than three times more frequently."

IMPLEMENTATION

  • 48% of companies are choosing to utilize one "platform (one primary martech vendor, augmented by specialist providers) over a suite (the whole stack comes from one martech vendor)."

AWARD-WINNING TECH STACK PROVIDERS

  • BlackRock Marketing Tech Stack
  • Earth Networks Marketing Tech Stack
  • Cisco Marketing Tech Stacks
  • Janus Henderson Marketing Tech Stack
  • Element Three Marketing Tech Stack

EXAMPLES of PERSONALIZED MARKETING TECH

  • The Westfield shopping complex in Shepherd's Bush, London has "cameras in and around the mall which use facial recognition technology to determine the age, sex, and even the mood of the shoppers as they move through the buildings. Based on what the system learns, it can then display different ads on the various digital billboards around the mall in order to maximize consumer response."
  • Amazon and Netflix have built highly effective personalized recommendation engines which "work so well that they've catapulted these companies ahead of the rest, because of the way in which they're able to personalize your experience so well when you use these platforms. They know almost exactly what I want to buy or watch next, and can be so accurate that, at times, it feels like they're reading my mind.

Proposed next steps:

You need to be the project owner to select a next step.