Turn scattered customer information into a reliable operational foundation. Unify customer, End User, Conversation, and usage data so teams can act with clearer context, reduce reactive work, and set a predictable baseline for lifelong revenue growth.
Turn scattered customer information into a reliable operational foundation. Unify customer, End User, Conversation, and usage data so teams can act with clearer context, reduce reactive work, and set a predictable baseline for lifelong revenue growth.
Why it matters
Take more decisive action through a unified view
Revenue teams cannot act confidently on information they do not trust or cannot access in one place. Data consolidation is the critical operational layer that connects customer context with reporting, handovers, and renewals. When data is unified, blind spots are eliminated and commercial execution becomes more proactive and consistent over time.
Why it matters
Take more decisive action through a unified view
Revenue teams cannot act confidently on information they do not trust or cannot access in one place. Data consolidation is the critical operational layer that connects customer context with reporting, handovers, and renewals. When data is unified, blind spots are eliminated and commercial execution becomes more proactive and consistent over time.
Why it matters
Take more decisive action through a unified view
Revenue teams cannot act confidently on information they do not trust or cannot access in one place. Data consolidation is the critical operational layer that connects customer context with reporting, handovers, and renewals. When data is unified, blind spots are eliminated and commercial execution becomes more proactive and consistent over time.
The Challenge
Why traditional data consolidation breaks down
Effective data consolidation breaks down when customer information lives across disconnected systems, inconsistent identifiers, and separate team workflows. Revenue, usage, CRM, and support data often require manual reformatting and reconciliation before they can support day-to-day execution. This creates a fragmented process where reporting becomes unreliable, handovers lose critical context, and teams remain reactive because the underlying data foundation is incomplete.
The Challenge
Why traditional data consolidation breaks down
Effective data consolidation breaks down when customer information lives across disconnected systems, inconsistent identifiers, and separate team workflows. Revenue, usage, CRM, and support data often require manual reformatting and reconciliation before they can support day-to-day execution. This creates a fragmented process where reporting becomes unreliable, handovers lose critical context, and teams remain reactive because the underlying data foundation is incomplete.
The Challenge
Why traditional data consolidation breaks down
Effective data consolidation breaks down when customer information lives across disconnected systems, inconsistent identifiers, and separate team workflows. Revenue, usage, CRM, and support data often require manual reformatting and reconciliation before they can support day-to-day execution. This creates a fragmented process where reporting becomes unreliable, handovers lose critical context, and teams remain reactive because the underlying data foundation is incomplete.
the solution
the solution
Unifying data and visibility
Planhat brings data ingestion, dynamic mapping, health visibility, and embedded agents into a single connected operating layer — transforming data consolidation from a one-time import exercise into an ongoing operational process.
Unifying data and visibility
Planhat brings data ingestion, dynamic mapping, health visibility, and embedded agents into a single connected operating layer — transforming data consolidation from a one-time import exercise into an ongoing operational process.
Unifying data and visibility
Planhat brings data ingestion, dynamic mapping, health visibility, and embedded agents into a single connected operating layer — transforming data consolidation from a one-time import exercise into an ongoing operational process.
Unifying processes
Planhat connects data readiness directly with proactive customer management — ensuring consolidated data immediately supports commercial execution rather than sitting dormant in a warehouse.
Unifying processes
Planhat connects data readiness directly with proactive customer management — ensuring consolidated data immediately supports commercial execution rather than sitting dormant in a warehouse.
Unifying processes
Planhat connects data readiness directly with proactive customer management — ensuring consolidated data immediately supports commercial execution rather than sitting dormant in a warehouse.
“
I had my own Notes pages that I was tracking data for different customers going into different sources of communication, whether it was email or Teams or Slack. And with Planhat, it's all kind of integrated into one place.”
Kelly Poydence
Director, Customer Success
Basis Technologies
Watch
“
I had my own Notes pages that I was tracking data for different customers going into different sources of communication, whether it was email or Teams or Slack. And with Planhat, it's all kind of integrated into one place.”
Kelly Poydence
Director, Customer Success
Basis Technologies
Watch
Evaluating your Data Consolidation maturity
Evaluating your Data Consolidation maturity
Low Maturity
Fragmented execution
Customer data is spread across spreadsheets, CRM fields, and manual exports. Teams spend significant time cleaning records, resulting in delayed reporting and reactive decisions.
Low Maturity
Fragmented execution
Customer data is spread across spreadsheets, CRM fields, and manual exports. Teams spend significant time cleaning records, resulting in delayed reporting and reactive decisions.
Low Maturity
Fragmented execution
Customer data is spread across spreadsheets, CRM fields, and manual exports. Teams spend significant time cleaning records, resulting in delayed reporting and reactive decisions.
Developing
Standardized workflows
The business has shared identifiers and defined steps for organizing data types, but progress still depends heavily on manual coordination and repeated validation across teams.
Developing
Standardized workflows
The business has shared identifiers and defined steps for organizing data types, but progress still depends heavily on manual coordination and repeated validation across teams.
Developing
Standardized workflows
The business has shared identifiers and defined steps for organizing data types, but progress still depends heavily on manual coordination and repeated validation across teams.
High maturity
Automation and intelligence
Embedded agents handle repetitive tasks — such as flagging missing fields, mapping records, and summarizing consolidation status — by combining rules with contextual data.
High maturity
Automation and intelligence
Embedded agents handle repetitive tasks — such as flagging missing fields, mapping records, and summarizing consolidation status — by combining rules with contextual data.
High maturity
Automation and intelligence
Embedded agents handle repetitive tasks — such as flagging missing fields, mapping records, and summarizing consolidation status — by combining rules with contextual data.
Best-in-class
Agentic operations
Agents autonomously orchestrate the consolidation process with contextual intelligence — cleaning incoming streams, mapping operational dependencies, and updating unified profiles — intervening only when complex architectural judgment is required.
Best-in-class
Agentic operations
Agents autonomously orchestrate the consolidation process with contextual intelligence — cleaning incoming streams, mapping operational dependencies, and updating unified profiles — intervening only when complex architectural judgment is required.
Best-in-class
Agentic operations
Agents autonomously orchestrate the consolidation process with contextual intelligence — cleaning incoming streams, mapping operational dependencies, and updating unified profiles — intervening only when complex architectural judgment is required.
Enabled by leading capabilities
Enabled by leading capabilities
Progressive automation and agentic operations
Syncing data at high speeds without contextual mapping just populates systems with noisy, unusable errors. In data consolidation, embedded agents need to understand how customer records, source systems, and business rules connect before they can take useful action. By combining traditional routing rules with contextual intelligence, Planhat's embedded agents shift teams from manual data administration to strategic execution — autonomously monitoring consolidation progress, surfacing missing fields, and keeping the data foundation aligned with how the business operates.
Progressive automation and agentic operations
Syncing data at high speeds without contextual mapping just populates systems with noisy, unusable errors. In data consolidation, embedded agents need to understand how customer records, source systems, and business rules connect before they can take useful action. By combining traditional routing rules with contextual intelligence, Planhat's embedded agents shift teams from manual data administration to strategic execution — autonomously monitoring consolidation progress, surfacing missing fields, and keeping the data foundation aligned with how the business operates.
Frequently asked questions about Data Consolidation
Frequently asked questions about Data Consolidation
How can eliminating fragmented customer data improve NRR?
How does Planhat reduce the administrative burden caused by data silos across Sales, Customer Success, and Product teams?
How can data consolidation be operationalized as a scalable process?
How does Planhat ensure consistent data governance across regions and teams?
How does data consolidation in Planhat enable alignment across internal teams and with customers?