Turn incomplete records into actionable commercial context. Unify contact data, company attributes, and external signals to eliminate manual research and set a predictable baseline for lifelong revenue growth.
Turn incomplete records into actionable commercial context. Unify contact data, company attributes, and external signals to eliminate manual research and set a predictable baseline for lifelong revenue growth.
Why it matters
Instantly boost contact and firmographic coverage
Revenue teams cannot execute effectively when their underlying account context is thin, outdated, or inconsistent. When enriched data is seamlessly connected to the rest of the customer record, teams can segment audiences accurately, identify the right stakeholders, and make commercial decisions with total confidence. This reliable data foundation supports stronger execution across targeted outreach, account prioritization, and long-term customer management.
Why it matters
Instantly boost contact and firmographic coverage
Revenue teams cannot execute effectively when their underlying account context is thin, outdated, or inconsistent. When enriched data is seamlessly connected to the rest of the customer record, teams can segment audiences accurately, identify the right stakeholders, and make commercial decisions with total confidence. This reliable data foundation supports stronger execution across targeted outreach, account prioritization, and long-term customer management.
Why it matters
Instantly boost contact and firmographic coverage
Revenue teams cannot execute effectively when their underlying account context is thin, outdated, or inconsistent. When enriched data is seamlessly connected to the rest of the customer record, teams can segment audiences accurately, identify the right stakeholders, and make commercial decisions with total confidence. This reliable data foundation supports stronger execution across targeted outreach, account prioritization, and long-term customer management.
The Challenge
Why traditional data enrichment breaks down
Traditional data enrichment breaks down when contact details, firmographic attributes, and external signals are spread across disconnected providers and manual workflows. Teams are forced to rely on repeated data entry, one-off spreadsheet exports, and isolated enrichment tools — making it impossible to trust the data that drives segmentation. The result is a fragmented process where records remain incomplete, follow-ups are delayed, and commercial teams waste valuable hours filling gaps instead of acting on real opportunities.
The Challenge
Why traditional data enrichment breaks down
Traditional data enrichment breaks down when contact details, firmographic attributes, and external signals are spread across disconnected providers and manual workflows. Teams are forced to rely on repeated data entry, one-off spreadsheet exports, and isolated enrichment tools — making it impossible to trust the data that drives segmentation. The result is a fragmented process where records remain incomplete, follow-ups are delayed, and commercial teams waste valuable hours filling gaps instead of acting on real opportunities.
The Challenge
Why traditional data enrichment breaks down
Traditional data enrichment breaks down when contact details, firmographic attributes, and external signals are spread across disconnected providers and manual workflows. Teams are forced to rely on repeated data entry, one-off spreadsheet exports, and isolated enrichment tools — making it impossible to trust the data that drives segmentation. The result is a fragmented process where records remain incomplete, follow-ups are delayed, and commercial teams waste valuable hours filling gaps instead of acting on real opportunities.
the solution
the solution
Unifying enrichment and activation
Planhat brings dynamic data ingestion, profile mapping, Automation triggers, and embedded agents into one connected operating layer — transforming enrichment from a periodic administrative chore into a continuous workflow.
Unifying enrichment and activation
Planhat brings dynamic data ingestion, profile mapping, Automation triggers, and embedded agents into one connected operating layer — transforming enrichment from a periodic administrative chore into a continuous workflow.
Unifying enrichment and activation
Planhat brings dynamic data ingestion, profile mapping, Automation triggers, and embedded agents into one connected operating layer — transforming enrichment from a periodic administrative chore into a continuous workflow.
Unifying data and downstream execution
Planhat ensures that accurate customer context immediately triggers downstream commercial actions — so enriched data does not sit dormant but directly powers the next step in the workflow.
Unifying data and downstream execution
Planhat ensures that accurate customer context immediately triggers downstream commercial actions — so enriched data does not sit dormant but directly powers the next step in the workflow.
Unifying data and downstream execution
Planhat ensures that accurate customer context immediately triggers downstream commercial actions — so enriched data does not sit dormant but directly powers the next step in the workflow.
“
With Planhat, the amount of customization that we can do is unbelievable.”
Tess Okonek
Director of Customer Experience
OnSiteIQ
Watch
“
With Planhat, the amount of customization that we can do is unbelievable.”
Tess Okonek
Director of Customer Experience
OnSiteIQ
Watch
Evaluating your Data Enrichment maturity
Evaluating your Data Enrichment maturity
Low Maturity
Fragmented execution
Data enrichment depends on manual research, scattered spreadsheets, and disconnected third-party vendors. Teams operate with incomplete records, delaying commercial execution.
Low Maturity
Fragmented execution
Data enrichment depends on manual research, scattered spreadsheets, and disconnected third-party vendors. Teams operate with incomplete records, delaying commercial execution.
Low Maturity
Fragmented execution
Data enrichment depends on manual research, scattered spreadsheets, and disconnected third-party vendors. Teams operate with incomplete records, delaying commercial execution.
Developing
Standardized workflows
The business has clear rules for filling account and contact gaps using unified tables, but validating updates and connecting them to downstream actions still relies heavily on manual coordination.
Developing
Standardized workflows
The business has clear rules for filling account and contact gaps using unified tables, but validating updates and connecting them to downstream actions still relies heavily on manual coordination.
Developing
Standardized workflows
The business has clear rules for filling account and contact gaps using unified tables, but validating updates and connecting them to downstream actions still relies heavily on manual coordination.
High maturity
Automation and intelligence
Embedded agents handle repetitive work — such as identifying missing fields, summarizing data gaps, and prompting updates — by combining predefined rules with incoming account data.
High maturity
Automation and intelligence
Embedded agents handle repetitive work — such as identifying missing fields, summarizing data gaps, and prompting updates — by combining predefined rules with incoming account data.
High maturity
Automation and intelligence
Embedded agents handle repetitive work — such as identifying missing fields, summarizing data gaps, and prompting updates — by combining predefined rules with incoming account data.
Best-in-class
Agentic operations
Agents autonomously orchestrate the enrichment process with contextual intelligence — matching enrichment sources, resolving data conflicts, and triggering operational dependencies — intervening only when strategic governance or complex segmentation choices are required.
Best-in-class
Agentic operations
Agents autonomously orchestrate the enrichment process with contextual intelligence — matching enrichment sources, resolving data conflicts, and triggering operational dependencies — intervening only when strategic governance or complex segmentation choices are required.
Best-in-class
Agentic operations
Agents autonomously orchestrate the enrichment process with contextual intelligence — matching enrichment sources, resolving data conflicts, and triggering operational dependencies — intervening only when strategic governance or complex segmentation choices are required.
Enabled by leading capabilities
Enabled by leading capabilities
Progressive automation and agentic operations
Appending data at speed without understanding its commercial context just creates a noisy database full of overwritten and irrelevant fields. In a mature data enrichment process, Planhat's embedded agents need to understand which records actually matter, how external data maps to the internal customer model, and what downstream actions depend on that specific update. By combining traditional Automation rules with this contextual intelligence, they shift teams from manual data administration to strategic execution — autonomously surfacing incomplete profiles, resolving discrepancies, and triggering follow-ups directly from the data layer.
Progressive automation and agentic operations
Appending data at speed without understanding its commercial context just creates a noisy database full of overwritten and irrelevant fields. In a mature data enrichment process, Planhat's embedded agents need to understand which records actually matter, how external data maps to the internal customer model, and what downstream actions depend on that specific update. By combining traditional Automation rules with this contextual intelligence, they shift teams from manual data administration to strategic execution — autonomously surfacing incomplete profiles, resolving discrepancies, and triggering follow-ups directly from the data layer.
Frequently asked questions about Data Enrichment
Frequently asked questions about Data Enrichment
How can enriching customer data improve NRR?
How does Planhat eliminate data silos that limit enrichment effectiveness?
How can data enrichment be scaled as a continuous process?
How does Planhat ensure governance and consistency in enrichment globally?
How does Planhat create alignment across teams through enriched customer data?