Gartner’s first MQ report on Personalization Engines points to the category’s robust evolution
Descendents from product recommendation engines, personalization platforms are growing into experience deciders and managers for all environments.
“Personalization” is almost synonymous with marketing these days, since automation, AI and addressable content make individualized material a tantalizing capability.
To help sort out the facilitating tools, Gartner has released its first Magic Quadrant report on Personalization Engines. (It’s available for free, with registration, from several of the vendors mentioned in the report, including Evergage and Qubit.) As with Gartner’s many other MQ reports, this one characterizes leading vendors according to their position on two axes, Ability to Execute and Completeness of Vision.
Although almost every marketing tool these days promises some kind of personalization, Gartner attempts to narrow its scope by defining these platforms as providing “a relevant, individualized interaction” that employs the recipient’s personal data and individual/aggregated behavioral data to “deliver an experience to meet specific needs and preferences.”
In particular, the report focuses on personalization tools that allow marketers to test, target, trigger and optimize brand interactions across marketing, digital commerce and the “emerging use case” of customer experience.
Such personalization engines, the report notes, exist as standalone software, as well as embedded capabilities in other platforms. But standalone tools have the edge when marketers want to integrate or manage their “best of breed” crop of solutions through a single dashboard.
35% revenue increase
In the top quadrant of Leaders, the report places Dynamic Yield, Evergage, Monetate, Certona, Adobe and Qubit as vendors that excel in both execution and vision.
Placing as Visionaries — tops in vision but less so in execution — are Episerver, SAS, Oracle, IBM, IgnitionOne and RichRelevance, while Niche Players are Acquia, Boxever, BloomReach and Strands. Challengers are Reflektion and Emarsys.
As the report points out, this booming category saw a 35 percent increase in revenue just from 2017 to 2018. The central technology of these personalization engines, and a factor that distinguishes these tools from other “personalizing” solutions, is a decisioning engine that not only segments audiences, but decides — instantly — what to deliver to whom and how often.
Gartner points out that, although personalization engines are descended from product recommendation engines, the new generation of decisioning engines has the potential to do much more — including possibly tailoring offline experiences in physical locations like stores or hotels, or in new personalizing environments, like call centers.
Key drivers of this evolution now include the trend toward a unified view of the customer, such as with Customer Data Platforms (CDPs), broad-based testing, automation balanced with user control, the ability to immediately execute decisioning and the increasing drive for privacy management. Of course, powering all of these drivers is the growing presence of artificial intelligence and its cousin, machine learning, which are offering new powers like machine vision, natural language processing, machine-generation of content, plus targeting that improves its accuracy over time.
Since unified customer data is so central to personalization, Gartner notes that some vendors — such as Certona, Evergage and Monetate — are increasingly becoming like CDPs, since they natively have the capability for bidirectional data flow of enriching profiles. The more personalization engines take on the responsibilities of customer data management, the more likely they are to become the centerpieces of marketing suites.
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