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Hyper Personalization

ZineOne incorporates live, streaming data with dynamic personalization to ensure accurate, predictive outcomes that surpass consumers' high expectations.

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Yesterday’s personalization tools cannot keep up with the high expectations consumers have today. The answer lies in a personalization platform that can incorporate live, streaming data, combined with stored and third-party data, powered by highly-accurate machine learning models that allow today’s marketers to dynamically adust how they engage with visitors on-the-fly. Expect this and much more from your personalization platform.

Triggered Personalized Experiences

Timely messages and relevant & engaging interactions can convert a visitor into a customer and keep a customer loyal. 

Today’s marketers need more than segments based on pre-defined rules, they need the ability to define segments based on triggers or events (in-session behavior) such as the sequence of pages visited, the amount of active time spent viewing a certain category of products or a user’s location at that moment, compared to their usual, known location at that time of day. These triggers or events enable you to maximize a visitor’s experience in a highly contextual manner resulting in great user experience, one that is rewarded by their loyalty.

 

Target Users Dynamically

Targeting users effectively involves taking that visitor’s activity into account and applying context to an interaction. Effective context means you must incorporate the time of day, the weather, the location, and compare it to what’s normal or usual for that visitor when making a recommendation. ZineOne’s deep learning and machine learning models incorporate dozens of different variables, form insights, and recommend the best action that is most likely to get the user to respond.

On the right is an example of some of the information we capture to provide personalized experiences.



Target Users Dynamically

Schedule Proactively

TheZineOne platform provides an endless array of options to engage your visitors.  You can define a segment based on demographic and behavioral characteristics and pre-enroll users or let the machine learning models enroll visitors into new or existing segments based on their behavior. You also have the flexibility of defining the rules for when a segment is full and should stop enrolling new members so you are always in control of your promotion budget.

ZineOne has a dedicated and competent team, and they are easy to work with. We have brainstormed ideas with them often.

– Director of Product, Digital in the Retail Industry

Resources

Mapping the Consumer Genome

Nikhil Chandurkar, Formerly of Kohl’s: Automating Retention Strategies in a World of Machine Learning

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Post

AI-Based Personalization Provides 10%+ Revenue Uplift

AI-Based Personalization Provides 10%+ Revenue Uplift

In this case study we delve into how ZineOne enabled a top 10 U.S. retailer to drive online conversions with personalized and relevant in-session interventions.

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Guides and reports

A Definitive Guide to Selecting an AI-Powered Personalization Platform

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*Gartner Peer Insights reviews constitute the subjective opinions of individual end users based on their own experiences, and do not represent the views of Gartner or its affiliates.

Create memorable consumer engagement through predictive intelligence

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