2024 CDP Landscape: How to choose + Benchmark

Gain a 360° view of customer interactions

Enrich their customer view with predictive attributes

Facilitate data analysis and define new data-driven marketing strategies

Segment their customer base

Improve the customer experience at every stage of the customer journey through better acquisition strategies, marketing automation and personalization across all channels

Traditional CDPs: These are packaged CDPs (standalone entity) that help collect, store, unify, and activate data to operational tools. They are the historical solutions on the market and are designed to facilitate data exploitation by marketing teams.

Composable CDPs: This category corresponds to a modular association of tools within your infrastructure aimed at collecting, storing, unifying, and activating data from a data warehouse to final tools. Although based on technical tools, Composable CDPs are designed for end marketing users, with no-code features and intuitive interfaces.

Hybrid CDPs: A hybrid CDP is generally a packaged CDP that now offers features to integrate into your existing data infrastructure (as Composable CDPs do).

Martech Suites: This category corresponds to suites offered by software vendors (Salesforce, Adobe, etc.) containing various marketing and data management products, aimed at collecting, storing, unifying, and activating data (most often to suite tools).

Infrastructure Solutions: Solutions that act as data pipelines, both upstream and downstream of a storage base. The solution is not intended for a marketing audience, who do not necessarily have the technical skills to use it.

Available Connectors: The ideal CDP should be able to collect and unify data from different customer touch points to send to various destinations. If the data sources/destinations considered are not common in the market, traditional CDPs may lack connectors to these tools. Conversely, the most common sources and destinations are obviously supported by packaged CDPs.

Data Structuring: The way data is structured affects segmentation, activation, or reporting capabilities. Your CDP's data model should be flexible enough to model your activity (custom tables, metadata, etc.) and properly use your customer data.

Data Quality: A CDP may offer data processing modules, particularly for identity resolution. Some vendors may offer off-the-shelf features or custom ones. Ensure you choose the option that best suits you!

Data Segmentation: A CDP can be used to define audience and/or personalized data segments. Some packaged CDPs do not allow for the simple calculation of new fields or custom scores, showing some segmentation shortcomings. Composable CDPs, on the other hand, allow for the creation of any data segment from SQL queries or visual segment builders directly from your data warehouse.

Data Hosting: With a packaged SaaS solution, customer data stored with a third party may raise security questions. In the case of cloud hosting with a Composable CDP, data control is instead total.

Adaptation to Technical Stack: For the tool to be adopted by all involved teams, it seems simpler to limit changes to the tools used within a company as much as possible. Besides reducing training needs, this precaution prevents potential employee resistance. Simplified connection to the existing technical stack also reduces timeframes and costs.

Implementation: Depending on the chosen solution, implementation time and difficulty can vary greatly. Setting up a traditional CDP generally takes several months, while a composable solution may require only a few hours. Hybrid solutions offer an in-between. You might also consider whether you need an integrator and the training your teams may require.

Tool Maintenance: A traditional CDP has the advantage of not requiring maintenance from a company. This is done by a third party, so the company does not have to worry about potential connection problems or developing new connectors, for example. Conversely, Analytics Engineering skills are required to maintain data quality in a data warehouse (which may limit the adoption of a Composable CDP).

Budget and Time-to-Value: Packaged CDP license fees generally vary depending on the volume of hosted data. It can also be difficult to correctly estimate the cost of setting up a modular CDP if the company has not made the necessary efforts to structure its data in a data warehouse.

However, if the company has already invested in a cloud data infrastructure, using a Composable CDP means that you can start with simple use cases and go from there, ensuring an almost immediate ROI at every stage.

Segment: Initially specialized in event collection (from a website, mobile apps, SaaS, or servers), Segment has expanded to offer the full functionality of a CDP. The “Twilio Engage” suite allows for creating audiences and orchestrating customer journeys directly on the platform. Data is stored with Segment for up to 3 years.

Treasure Data: Initially recognized as a Big Data platform, Treasure Data repositioned itself on the CDP market, covering almost exclusively marketing use cases. More oriented towards Data Management, this traditional CDP focuses on data unification and preparation (aggregation, scoring, segmentation, etc.). It stands out for its unification and profile enrichment features, notably thanks to its proprietary artificial intelligence algorithms.

mParticle: A traditional CDP that focuses primarily on mobile event collection, mParticle allows for understanding user behaviors and activating them to hundreds of destinations. mParticle integrates with its “Cortex” solution, a Machine Learning platform that predicts certain indicators (Next best offer, Next best action, etc.) for customers.

DinMo (🇫🇷): DinMo is the leading European Composable CDP. DinMo makes the power of a CDP accessible to all, quick to implement (a few hours), easy to use, and generating a return on investment from the first month of use. Its key features, such as the Visual Audience Builder, one-click activation, and AI predictions (Next Best Offer, Next best action, etc.), allow marketing teams to launch any marketing strategy independently.

Hightouch: The leading Composable CDP in the United States, Hightouch's platform has evolved beyond its initial Reverse ETL offering by including native data warehouse features such as event collection, identity resolution, and orchestration.

Census : As Hightouch did, Census has evolved beyond its initial Reverse ETL offer, by including new functionalities covering identity resolution, orchestration, etc. Census positions itself as a "Universal Data Platform", which means that its end-users tend to be more technical people.

Salesforce: Salesforce Marketing Cloud is a CDP solution that allows for collecting, reconciling, managing, segmenting, and activating data within the Salesforce ecosystem. For a company primarily using Salesforce tools, this solution is recommended. However, activations to destinations outside Salesforce are rather limited.

Adobe: Adobe CDP is an integrated solution within the Adobe Experience Cloud suite, launched in 2019. The platform allows for creating unified profiles and using them in any other Adobe products in real-time, particularly the marketing suite, enabling personalized experiences. Adobe CDP mainly focuses on Data Management. Note that connectors outside the Adobe suite are rather limited and activation features are not really part of its functional scope. This CDP is especially suitable for large groups with data management expertise.

Imagino (🇫🇷): Initially focused on data management (unification, data enrichment, segmentation, etc.), Imagino is gradually expanding its functional scope by integrating activation components (campaign management, marketing automation, etc.). Imagino offers great freedom in data storage, proposing a hybrid or full SaaS mode. Unlike traditional CDPs, the data model is not imposed, and ingesting and unifying data from multiple sources is thus simplified.

ActionIQ: Able to integrate directly into its clients' data warehouse or offering an internal deployment, ActionIQ is a hybrid CDP. Note that the “data warehouse” integration is more recent and thus less mature. Its main goal is to centralize and unify customer data in a single place to activate it across all marketing channels afterward. The platform offers several features: data collection, audience segmentation, and even real-time triggers.

Rudderstack: A data-oriented solution, Rudderstack is more of a Customer Data Infrastructure (CDI). Rudderstack offers a data infrastructure that focuses on collecting, processing, and storing customer data through its various products: event streaming, ETL, identity stitching, Reverse ETL, and Audience Builder. Rudderstack's primary mission is to help data teams build and maintain their infrastructure rather than a solution designed for marketing. Rudderstack can be implemented to meet CDP use cases, but marketing teams will find it difficult to use autonomously.