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

What I like best about Salesforce Data 360 (formerly Data Cloud) is how it brings all of our customer data together in one unified view. Before adopting it, our customer information was scattered across sales, service, marketing, and external sources — which made personalization and segmentation really difficult. With Data 360, we finally have a centralized and real-time profile for each customer that’s accessible across the entire Salesforce platform.

The data modeling and identity resolution capabilities are particularly strong. They make it easy to merge duplicate records and maintain clean, accurate profiles without extensive manual work. This has improved the quality of our analytics and given our teams confidence in the metrics they use to make decisions.

Another major benefit is the real-time data updates. Campaigns and journeys now react instantly to customer behavior, which has helped us deliver more timely and relevant experiences. It’s also straightforward to connect Data 360 with other Salesforce clouds (like Marketing Cloud and Service Cloud), which has streamlined our workflows and reduced integration complexity.

Overall, Data 360 has significantly improved how we understand and engage with our customers, making data more usable and actionable across teams. Review collected by and hosted on G2.com.

One of the main challenges with Salesforce Data 360 is the initial setup and learning curve. The platform is powerful, but configuring data streams, identity resolution rules, and data models requires a solid understanding of both Salesforce architecture and data management concepts. For teams without strong technical resources, onboarding can feel complex.

Another drawback is cost. Data 360 is a premium product, and pricing can scale quickly depending on data volume and usage. For mid-sized organizations, this can become a significant investment.

Performance can also depend heavily on how well the data model is designed. If not structured properly from the beginning, you may face delays in processing or difficulty in creating segments. Additionally, troubleshooting data ingestion or identity resolution issues sometimes requires deeper platform knowledge than expected.

Overall, while it’s a very capable solution, it does require proper planning, skilled resources, and budget to fully realize its value. Review collected by and hosted on G2.com.

I have been working with Salesforce Data Cloud for the last six months. So far, I’ve really liked how it makes customer unification easy and straightforward. Before Data Cloud, it was very hard to get a complete view of the customer. Now, having a unified customer view and better segmentation has made targeted marketing much easier for us. Data Cloud feels like a game changer if you’re dealing with multiple data sources and interacting with customers across different channels. Einstein Studio’s custom predictive models are also a very good add-on. Review collected by and hosted on G2.com.

So far, everything works as expected and mostly covers our needs. The pricing feels like too much if you’re not going to use all the features. Great tool overall. Review collected by and hosted on G2.com.

I find Salesforce Data 360 really helpful for segmentation and building data extensions for marketing cloud journeys. It greatly simplifies the segmentation of data from multiple streams, including Snowflake. I also appreciate how it leverages calculated insights for building reports. The data ingress process is very easy; it’s incredibly simple to set up, and I can have it up and running, with data coming in, in less than an hour. Overall, all the features are great. Review collected by and hosted on G2.com.

Data ingress should be free and the segmentation selection should be made easy. Segmentation and calculated insights can be more streamlined. Calculated insights reports should be grouped for dates. Segments selection of related attributes should be more streamlined and easy instead of an endless list of dropdown. Review collected by and hosted on G2.com.

Easy to use, and I like how smoothly the flow runs from ingestion through unification. The way we can connect with other systems is easy and the zero-copy allow us to get more thing without think about the storage capacity. Review collected by and hosted on G2.com.

The calculator still needs some improvements so it can provide a more accurate forecast over time for credit consumption. Review collected by and hosted on G2.com.

What stands out most about Salesforce Data Cloud is its ability to unify diverse customer data sources into a single, real-time customer profile. This comprehensive 360-degree view enables personalized marketing, sales, and service experiences driven by AI and analytics.

Key strengths include:

Seamless integration of data from multiple systems, including CRM, marketing, commerce, and more.

Powerful real-time segmentation and audience activation for targeted campaigns.

Built-in Einstein AI capabilities for predictive insights and next-best actions.

Scalability and flexibility to tailor data models and workflows to unique business needs. Review collected by and hosted on G2.com.

One potential downside of Salesforce Data Cloud is its complexity and learning curve, especially for organizations new to data unification and customer data platforms. Setting up integrations, configuring data models, and leveraging AI-driven insights may require significant initial investment in time and skilled resources Review collected by and hosted on G2.com.

I like the zero copy feature. It helps me reduce historical data costs. Review collected by and hosted on G2.com.

I'd say the one to one, I guess, limitation. So one connecting only one data cloud to one Salesforce. Instance is a huge limitation. Ideally, being able to connect one data cloud to multiple Salesforce instances would be a major selling point. Review collected by and hosted on G2.com.

The zero-copy functionality has proved its value time and time again. Allowing a seamless, cheap and easy way to bring data into your Salesforce instance for segmentation, analytics, AI, or any other purpose. Review collected by and hosted on G2.com.

The party identifcation DMO proves rather difficult to break down and understand, and a good technical understanding of this and the 360 model is needed in order to properly drive unification. At the time we implementated, the documentation was somewhat poor however since then, it has significantly improved, and the online communities such as Data Blazer proved a fruitful source of infomration. Review collected by and hosted on G2.com.

What stands out most is how seamlessly Data Cloud integrates with both Salesforce-native and external data sources like Amazon S3. The platform’s ability to harmonize disparate datasets into a unified customer profile has been a game-changer. Its real-time segmentation and activation capabilities allow us to respond to customer behavior with agility, while the intuitive UI and strong governance features make it scalable across teams. The identity resolution engine is particularly impressive—it’s helped us reduce duplication and improve personalization across channels. Review collected by and hosted on G2.com.

While the platform is robust, the initial onboarding and data modeling phases require a steep learning curve, especially for teams new to CDPs. Some UI components can lag when handling large datasets, and a few connectors for niche third-party tools require custom development. Additionally, documentation around advanced orchestration flows could be more detailed to support complex use cases. Review collected by and hosted on G2.com.

I like the ease of access that Salesforce Data 360 offers, it makes using the platform straightforward. I find the validation feature valuable, which supports my work effectively. The initial setup was easy for my team, which made the transition smooth. Review collected by and hosted on G2.com.

I find dealing with duplication a bit frustrating. There could be improvements in how duplicates are managed, specifically making it easier to merge them. Review collected by and hosted on G2.com.

We use it to surface our messaging and support in-app web chats, as well as GenAI data, and we’re also looking to use it for storing content from crawling. It lets us view and report on data coming from these different sources in one place. Review collected by and hosted on G2.com.

The data consumption is a bit tricky to navigate in terms of costs associations and detailed breakdowns between Prod and Sandboxes to triage usage. Review collected by and hosted on G2.com.