Gartner defines customer data platforms (CDPs) as software applications that support marketing and customer experience use cases by unifying a company’s customer data from marketing and other channels. CDPs optimize the timing and targeting of messages, offers and customer engagement activities, and enable the analysis of individual-level customer behavior over time. The purpose of a CDP is to centralize data collection and unify customer data from disparate sources into profiles. CDPs enable marketers to create and manage segments and push those segments to priority channels without requiring coding or use of advanced querying techniques. While CDPs originated to serve marketing use cases, interest from data management roles, IT and other customer-facing roles (e.g. sales, service and support) is on the rise. Digital marketing leaders have long used a variety of systems to design, orchestrate and measure multichannel campaigns. While many of those systems also manage customer-level data and audiences for targeting, they do so in a way that makes both data governance and orchestration across channels (and across competitive vendor solutions) a challenge. CDPs aim to address that challenge by collecting and unifying disparate customer data in a centralized location accessible to marketers. The CDP is not a substitute for an enterprise’s master data management, but it can ensure that customer profile data, transactional events and analytic attributes are available to marketing when needed for real-time interactions.
Mobile app analytics tools collect and report on in-app data pertaining to the operation of the mobile app and the behavior of users within the app. These areas of app analytics are defined as follows: Operational analytics: Provides visibility into the availability and performance of mobile apps in relation to device, network, server and other technology factors. Operational analytics are essential to capture and fix unexpected app behavior (such as crashes, bugs, errors and latency) that can lead to user frustration and abandonment of the app. Such analytics should be applied at both the app testing phase and after release of the app into production. Behavioral analytics: Shows how app users interact with the app to gain actionable insights, drive app improvements and improve business outcomes. Behavioral data can be analyzed based on correlating clicks, swipes, views and other usage stats based on user profiles, segmentation/cohorts, retention, funnel/event tracking and A/B testing.