Latest Gartner personalisation engine report highlights strengths and weaknesses of platform approaches

Dynamic Yield has once again led Gartner’s annual Magic Quadrant 2022 report analysing personalisation engine platforms in market, followed by Insider, Salesforce, Adobe and SAP.

The latest Gartner report detailed 13 vendor offerings in the personalisation engine space, rating each on three key use cases: Marketing management, and capabilities to deliver the right message to the right audience in the right context; digital commerce, and the ability to tailor content, offers, recommendations and experiences across digital sales channels; and personalising service and support through customer insight, journeys and user feedback.

Core capabilities the analyst firm assessed platforms on included in-session user behaviour tracking, data collection and ingestion, and triggering interactions in real time based on an individual’s actions, context or data or a combination of all three. Also critical to be considered in this category was predictive analytics capabilities supporting content and product recommendations, flexible user segmentation, extensive testing tools and personalisation performance tracking and reporting.

In addition, each vendor had to have at least US$20 million in annual platform revenue and a minimum of 25 net new customers for their personalisation engine in 2021.

In the top right ‘leaders’ quadrant of vendors offering both a strong vision for their platform as well as an ability to execute was Dynamic Yield. Gartner noted the platform’s strengths, such as extensive pre-built testing templates, no-code visual editor, predictive targeting feature and its ‘AdaptML’ feature offering next-best action suggestions. Other pros included stronger integrations for omnichannel personalisation as well as standalone email personalisation.

On the cons side, Gartner said Dynamic Yield’s recent change in ownership to Mastercard, its second change in three years, raised concerns around its roadmap and innovation plans longer term.

Also in the top right leaders quadrant was Insider. Gartner noted the vendor’s product discovery, reporting and regional service as major pluses. Cautions included the level of customisation required, identity management across digital properties and pricing.

Salesforce was on the leaders list and recommended for its robust bandit testing, B2B personalisation support and strong entry-level offering. Cautions included the requirement for user-level metadata, a Salesforce-focused product roadmap and develop resource requirements. SAP, another of the top five leaders, was highlighted by Gartner for its personalisation plus privacy approach, hierarchical triggering templates based on business goals, and results reporting. Negatives included trailing product and content discovery compared to other vendors, a lack of advanced testing and an enterprise-focused roadmap.

Adobe Target was the fifth platform in the top right corner, noted for strengths such as superior testing and experimentation capabilities, robust targeting based on machine learning and rules-based profiling, and platform connectivity. Cautions from Gartner included some performance challenges with interface speed, a lack of out-of-the-box reporting and support.

The Gartner Magic Quadrant for personalisation engines also featured four ‘visionary’ vendors noted for their strong product vision, but a lesser ability to execute it. These were Sitecore, Algonomy, Kibo and Optimizely. The remainder of the vendors listed fell into the bottom left quadrant as challengers and niche players with limited ability to execute. These were Oracle, Coveo, Attraqt and SiteSpect.

In its commentary, Gartner highlighted three trends driving personalisation engine innovation. The first was friendlier user interfaces to drive AI recommendation strategies, while the second was a broader scope of measurement, tied to the growing customer data scope driven by customer data platform (CDP) adoption.  

The third trend is the rise in workflow, content management features and professional services capabilities to help clients better realise success from their personalisation platform investment. Gartner pointed out while many organisations have made significant platform investments, they often don’t invest in the people and process capabilities required to drive ongoing value.

“This leads to inconsistent performance and the perception that personalisation programs are not returning on investment,” the report authors stated. “Organisations lack a holistic approach to personalisation, in most cases lacking an operating model that dovetails into broader content and marketing operations needed to fuel personalisation engines. Personalisation technologies can certainly help, but they must be embedded in marketing operations workflows to truly drive value.”

Gartner first debuted its personalisation engine report in 2018.

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