Data 360 (formerly Salesforce Data Cloud) Reviews & Product Details

The biggest strength is being able to fully leverage the data already living inside Salesforce. It unifies data from multiple sources into a single customer profile, which makes it much easier to get a complete, real-time view of customers without building custom integrations. This also makes downstream activities like segmentation, personalization, and analytics far more effective, since everything is built on a consistent, well-governed data foundation. Review collected by and hosted on G2.com.

The pricing is the main downside. Costs can rise quickly depending on data volume and the features you enable, and it's not always easy to predict the total cost as usage scales. This makes it harder to build a clear ROI case up front, especially for organizations that are still evaluating how much data they'll ultimately bring into the platform, so more predictable or flexible pricing would help. Review collected by and hosted on G2.com.

Data 360 excels at creating a unified customer view by integrating enterprise data in real time. It enables Agentforce and AI experiences while bringing CRM, analytics, and reporting together into a single ecosystem.

Its integration across the Salesforce ecosystem is a major strength, allowing organizations to connect CRM, Agentforce, analytics, and AI-driven experiences more seamlessly. The identity resolution and customer data unification capabilities also stand out, helping consolidate multiple records into a more comprehensive customer profile.

I also appreciate the zero-copy architecture options, which let organizations leverage existing data investments without extensive data movement or duplication. Finally, its AI readiness and Agentforce enablement provide a trusted data foundation for intelligent recommendations, grounded AI prompts, analytics, and automation. Review collected by and hosted on G2.com.

Organizations are looking for simpler implementation, clearer governance models, more predictable costs, easier onboarding, and stronger support to manage complex enterprise data landscapes.

A major challenge is implementation complexity, especially around data ingestion, mapping, harmonization, and identity resolution across multiple source systems.

There is also a steep learning curve that often requires specialized knowledge in architecture, data modeling, governance, and administration.

Cost and licensing can be a concern as well, particularly for organizations evaluating multiple environments, companion orgs, large data volumes, and AI-enabled use cases.

Success is highly dependent on underlying data quality, since Data 360 does not inherently solve enterprise-wide governance, data quality, or harmonization challenges.

Teams also face complex architectural decisions, such as choosing between federation, migration, and zero-copy approaches, and defining integration strategies across regions and systems.

Finally, stronger governance and ownership models are often needed. Many organizations require clear business ownership, well-defined operating models, and roadmap alignment before they can scale adoption. Review collected by and hosted on G2.com.

The Zero-Copy architecture is easily the standout feature. Being able to query data directly from external data lakes like AWS or Snowflake without having to build and maintain brittle ETL pipelines saves significant engineering overhead. It natively pulls fragmented customer records into a single profile right inside the Salesforce ecosystem. This allows us to feed accurate, real-time context into Agentforce and trigger outbound flows the exact second a data model object updates, entirely eliminating the reliance on slow overnight batch syncs. Review collected by and hosted on G2.com.

The consumption-based credit pricing model is incredibly difficult to forecast. Because costs scale aggressively with data ingestion and identity resolution, a single unexpected usage spike can easily wreck your monthly budget. Furthermore, the initial data modeling is very unforgiving. If you do not perfectly map out the schema and identity resolution rules before going live, you will inevitably end up with bloated customer profiles, slow query performance, and a messy data structure that is hard to untangle later. Review collected by and hosted on G2.com.

Unified customer view: Brings customer data from multiple sources into one place.

* Better data visibility: Helps users get a more complete understanding of customers.

* Real-time insights: Supports timely access to customer information and insights. Review collected by and hosted on G2.com.

Complex setup: Initial configuration and data integration can be challenging.

* Learning curve: Users may need training to understand Data 360 concepts and capabilities.

* Data quality dependency: Poor-quality source data can affect the accuracy of the unified customer view. Review collected by and hosted on G2.com.

The biggest strength is how it brings data from different sources together and makes it usable within Salesforce. Being able to get a more complete view of customers without requiring everything to live natively in the CRM is extremely valuable. It also unlocks a lot of possibilities for segmentation, personalisation, and automation, while making customer data accessible across different Salesforce products. Review collected by and hosted on G2.com.

There’s a fairly steep learning curve, especially at the beginning when you start working with the data model, identity resolution, calculated insights, and the different ways data can be activated. The terminology and overall setup can feel more complex than you might expect, and it can also be hard to understand exactly how consumption and credits work. The platform is powerful, but getting real value from it really depends on having a clear use case and being willing to invest time in learning how it works. Review collected by and hosted on G2.com.

We use Data 360 as a unified data and activation layer across our Salesforce ecosystem, helping us bring everything together in one place. Review collected by and hosted on G2.com.

What I dislike most about Data 360 is its complexity. Although it provides powerful capabilities for unifying data, creating insights, and activating information across Salesforce, the implementation can require significant architectural planning, data mapping, governance, and ongoing maintenance. Review collected by and hosted on G2.com.

The biggest advantage of Data 360 is its ability to bring together disparate data sources and create a unified customer profile at scale. Its real-time processing, identity resolution, and activation capabilities enable organizations to turn data into actionable insights quickly, improving both operational efficiency and customer engagement. Review collected by and hosted on G2.com.

The biggest challenge is the complexity of setup and maintenance. The learning curve is steep, and managing integrations, data quality, and consumption costs can require significant effort Review collected by and hosted on G2.com.

What I like most about Data 360 is how it brings data from different sources together and makes it usable inside the Salesforce platform. The ability to unify customer data and apply it across Salesforce opens up a lot of possibilities for segmentation, automation, analytics, and AI.

I also appreciate how tightly Data 360 fits into the broader Salesforce ecosystem. For organizations that have already made a significant investment in Salesforce, being able to work with external data without having to move or duplicate all of it can be especially valuable. And as Salesforce continues to expand its AI capabilities, I expect Data 360 to become even more important as the data foundation behind those solutions. Review collected by and hosted on G2.com.

The biggest challenge with Data 360 is the learning curve. Even for someone very familiar with Salesforce, there are many new concepts, terms, and tools to absorb. Data modeling, data streams, identity resolution, calculated insights, and the various ways data can be accessed and activated all take time to understand and feel comfortable using.

It can also be hard to gauge the potential cost and consumption implications of a solution. Since usage can vary significantly depending on the architecture and the specific use case, administrators and architects need to be deliberate in how they design and implement solutions, rather than approaching Data 360 the same way they might approach functionality on the core Salesforce platform. Review collected by and hosted on G2.com.

I really like the data centralization feature in Data 360. It helps us connect all our Salesforce cloud data. I also find the data compliance and 360 data view beneficial, as it makes it easy to align with data compliance and regulations, even within big companies. Review collected by and hosted on G2.com.

The connection with Salesforce Order Management is challenging. The connector isn't very effective, which makes it difficult to connect and use with some systems. The initial setup of Data 360 wasn't easy, though we managed to get it done. Review collected by and hosted on G2.com.

I love the ease of use with the new infrastructure in Data 360. It makes solving business problems much faster than before. The new technology, especially the identity resolution center and automation features, really stands out for me. They allow for more personalized journeys for more people. The personalization factor, the data factor, and the AI prompt-based chart are features I find particularly appealing. The identity resolution center is fantastic at identifying duplicates in the system, ensuring we don't send the same emails to users repeatedly and accurately knowing the true count of users in the CRM. Review collected by and hosted on G2.com.

I think it's less visual, so it requires a lot of training to understand. The initial setup wasn’t easy because a lot of training was needed. Review collected by and hosted on G2.com.