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Amplitude helps financial services organizations like Square meet customers in the moment, with real-time experiences that drive engagement, improve conversion and bolster retention. Amplitude helps teams to bring these experiences to life by providing them with quantitative and qualitative insights, recommendations and predictions about what customers are doing and why across the entire customer journey. And because Amplitude standardizes, governs and centralizes data across all sources, teams can confidently use these insights to drive the best results.

mParticle is the customer data platform (CDP) of choice for the world’s leading multi-channel consumer brands. Leading business-to-consumer (B2C) companies use mParticle to create a unified, real-time customer data pipeline that enables them to win in key moments of the customer journey.

Tealium connects customer data– spanning web, mobile, offline, and IoT devices— so brands can connect with their customers. Tealium empowers brands to create a unified, real-time customer data infrastructure. The Tealium Customer Data Hub makes customer data more valuable, actionable, and secure.

Enable LiveRamp's foundational identity solutions, including identity resolution and transcoding, for AWS. Generate a common ID for all customers within a collaboration to more accurately match and analyze across shared datasets, supporting privacy-enhanced media planning, insights, data enrichment, media activation, and measurement use cases.

Aqfer's Marketing Data Platform is designed to be an organization's primary data repository for all types of marketing-related data. MDP ingests, collates, resolves, and analyzes massive volumes of marketing-related data; it also re-factors data for rapid distribution.

Brands, agency, and publishers want to collaborate through clean rooms to build audiences, generate new customer insights, and measure/optimize the impact of marketing. However, collaborators often struggle with low match rates between data sets due to the unprecedented challenges of data deprecation, scarcity, and fragmentation of data.