"We have a great tool, but the data is disparate and unusable." This is the wall that many teams run into after a few months of using HubSpot. Whether you're taking leads with Marketing Hub, managing deals with Sales Hub, or getting support with Service Hub.A situation in which “one customer image” cannot be seen as each data is dividedIn this case, neither AI nor automation can demonstrate their true potential. Operations Hub—rebranded as “Data Hub” at INBOUND in September 2025—is a dedicated engine that eliminates this “data fragmentation” and runs the entire HubSpot on a unified data platform. In this chapter, we will explain its design philosophy, overall functional picture, plan comparison, and criteria for deciding whether to introduce it.
There is a common pattern among organizations that ``data utilization does not progress'' even after introducing HubSpot. Marketing enters leads into CRM, Sales updates opportunity information, and CS handles tickets.The situation continues where each person “only sees data from their own hub”--In other words, it's data siloing. As a result, there are problems such as duplicate contact records, the concepts of "MQL" and "customer" that are defined differently by different teams, and the accuracy of automation not improving because the training data for AI is incomplete.
The rise of RevOps (Revenue Operations) is an organizational answer to this problem.By having the Marketing, Sales, and CS teams working on the same data platform, we can achieve a consistent customer experience from leads to renewals and maximize revenue.——Operations Hub is the engine for building and maintaining that "common infrastructure."
① Data separation——Marketing, Sales, CS, and Finance data exists in separate systems, and no one can see a “single customer image.”② Data contamination——Duplicate records, inconsistent formats, and missing fields contaminate AI training data and reduce automation accuracy.③ Limits of automation——Complex business logic (territory management, complex routing, external system integration) that cannot be handled using standard no-code workflows remains to be done manually.
At INBOUND in September 2025, HubSpot officially launches Operations Hub Rebranded to “Data Hub”did. This is not just a name change, but a fundamental shift in product positioning.
Data Hub is offered in four plans.AI duplicate detection/automatic mergingIt is important to choose based on ``Do I need programmable automation?'' ``Do I need to integrate data with Data Studio?'' ``Do I want to integrate with a data warehouse?'' - Answering these three questions will determine your plan.
The biggest value of Professional is"Programmable Automation" and "Data Studio"// Required: exports.main is the execution entry pointHowever, in many cases, Starter is sufficient for integration needs that can be replaced by external tools such as Zapier or Make.com.Criteria to justify investing in Professional: (1) There is complex business logic that cannot be written using standard workflows, (2) Analysis that combines external data sources (Google Sheets, Snowflake, etc.) and CRM data is required, (3) Business costs due to duplicate records and inconsistent formats exceed 10 hours per month.If any of these three apply to you, it is worth investing in Professional.
The biggest features of Data Hub are:Acts as the "data foundation" for HubSpot's other five hubs (Marketing, Sales, Service, Content, and Commerce)// Extract domain from email
It is difficult to determine which plan is suitable for your organization just by reading the feature list. With the checklist belowDifferent field names/different data types/conversion requiredBy checking the following, the optimal plan and implementation priority will become clear.
| Number of checks | Recommended plan | first thing to do |
|---|---|---|
| Left column: 1 to 3 pieces | Starter | First connect one or two major apps with Data Sync and check that two-way synchronization works correctly. |
| Right column: 1 to 3 pieces (Pro items) | Professional | Data quality automation Start with WF (name normalization/duplicate merging), then implement one programmable automation |
| Right column: 1 or more Enterprise items | Enterprise | First, create an environment for configuration verification in the sandbox, then design the connection with the data warehouse. |
Data Hub's functionality is the largest in the series. If you try to set everything up at once, you're likely to end up with nothing working three months later.“Resolve your single most painful problem (e.g. explosion of duplicate records / morning manual synchronization with Salesforce / complex manual lead routing) within 90 days.”Starting with this policy is the fastest way to see ROI. Once you solve one problem, the next problem will appear.
The essential role of Operations Hub is to eliminate data silos in Marketing, Sales, and CS and create an environment where all teams can work with the same clean data. As data quality improves, the accuracy of AI increases, the accuracy of automation increases, and a cycle is created that is directly linked to revenue.
Inherits all the functionality of Operations Hub while adding Data Studio, Data Agent, and Smart Properties. Shifting from a "behind-the-scenes tool for engineers" to a "data utilization platform that can be used directly by Marketing, Sales, and CS." Seamless transition for existing users with no price change.
1) Do you have complex business logic that cannot be written using standard workflows (Professional criteria)? 2) Do you want to integrate and analyze external data sources and CRM (Do you need Data Studio)? 3) Do you want two-way synchronization with a data warehouse (Enterprise criteria)? These three questions will determine your plan.
Breeze AI makes more accurate predictions, Sales Hub lead scores work, and Service Hub health scores reflect reality all because of a clean, unified data foundation. Investments in Data Hubs circulate to improve the accuracy of all hubs.
Scenario 3: Sync “Only customers with purchases of JPY 30,000 or more” from Shopify to HubSpot
Even if other hubs are enriched, if data remains contaminated and fragmented, the accuracy of AI functions will not increase, automation will increase false firings, and reports will become less reliable. The long-term answer is to view the investment in Data Hub not as an "additional cost" but as an "infrastructure investment to maximize HubSpot's overall performance."