Customer data platforms (CDPs) are software applications that support customer experience use cases by unifying a company’s customer data from marketing, sales, service, commerce and other sources. CDPs unify customer data to facilitate its output to coordinate profiles between cross-functional systems, create segments and/or audience targets, optimize offers and/or decisions, and inform analysis while distributing insights that create triggers for other experiences.
Gartner defines multichannel marketing hubs (MMHs) as software applications, primarily delivered as SaaS, that orchestrate personalized campaigns and event-driven customer journeys across marketing channels. These applications leverage customer data, predictive models and real-time insights to optimize the timing, channel and content of interactions. MMHs apply advanced analytics, AI and prescriptive intelligence to help marketing and technical teams manage the end-to-end life cycle of customer journeys. Although MMHs overlap with customer data platforms (CDPs) and personalization engines, their primary focus is enabling marketing users to manage large-scale consumer interactions, particularly in owned media channels such as email and app push. Multichannel marketing hubs empower marketers to deliver personalized media and orchestrate customer journeys, thus driving revenue, engagement and loyalty. These SaaS applications unify customer data, predictive insights and real-time decision making to optimize interactions across digital channels. MMHs enable multidisciplinary teams to manage campaigns and event-driven journeys via advanced analytics, artificial intelligence/machine learning (AI/ML) and prescriptive intelligence.
Personalization engines use knowledge about customers to create and deliver an optimum experience for them and measure the impact on customer experience. These engines apply AI, advanced analytics and business rules to create meaningful experiences across channels that facilitate customer engagement and drive revenue. Personalization engines create a relevant, individualized interaction between two parties designed to enhance the recipient’s experience. A recipient can be a prospect, customer (known or anonymous) or employee (engaging with a customer or prospect). In commercial settings, the engines apply advanced analytics to interpret customer data — whether known or anonymous, behavioral or contextual — and adjust engagement based on where the customer is in their journey and how they’re interacting. The engines adapt content, offers and interactions in real time that facilitate the customer’s journey.