Understanding employee headcount data accuracy

For private capital investors, employee headcount is more than a datapoint. It’s a directional signal of company momentum, hiring activity, and operational scale. Whether you’re sourcing new opportunities, qualifying leads, or benchmarking peers, understanding team size helps you prioritize efforts and map the market more effectively.

We recently introduced a new enrichment column: LinkedIn Headcount. It gives you direct visibility into the number of profiles associated with a company on LinkedIn, refreshed monthly across the Affinity platform. 

This new enriched column complements our existing Number of Employees column, a curated estimate we’ve offered for years, designed specifically for private capital workflows. While both are rooted in LinkedIn data, they serve different purposes:

• LinkedIn Headcount reflects the number of profiles connected to a company on LinkedIn, providing a transparent, widely understood signal.
  
• Number of Employees applies additional filters to remove inconsistencies or noise to provide an estimate that is useful for workflows like diligence, benchmarking, and reporting.
  

Now, in Affinity, you can choose between two enriched headcount signals inside Affinity, or view both side by side for added context. By offering both, we’re giving your team more flexibility so you can apply the right level of signal strength depending on the task at hand.

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How LinkedIn Headcount works 

In private markets, headcount data is difficult to find. Many companies don’t disclose it publicly, which makes signals from sources like LinkedIn especially important. 

LinkedIn Headcount is based on profile data contributed by LinkedIn users and updated by the platform. It is built in two steps:

1. Profile matching: LinkedIn connects user profiles to companies based on self-reported employment history.
   
2. Profile aggregation: Once matched, those profiles are totaled to estimate company size. In some cases, tenure and public or company-reported data are also factored in.
   

LinkedIn periodically revises its headcount figures based on updates to public records and company-submitted information. These adjustments, typically applied retroactively, happen about twice a year. 

Where context adds value

LinkedIn is one of the most valuable data sources in private capital. Its scale, reach, and user participants make it a powerful signal, especially for top-of-funnel workflows. When greater accuracy is needed, additional context can be valuable. Throughout work with thousands of private capital firms, we’ve identified areas where raw estimates can benefit from further refinement. 

Profile quality varies

Not every LinkedIn profile is accurate, active, or complete. In fact, we’ve found that only 10-20% of profiles truly reflect real-world, up-to-date employment. In hot sectors, inflated or duplicate profiles are common. This can skew company size estimates. 

Loose employee matching

LinkedIn’s default matching relies on self-selected employment fields. In cases where users don’t explicitly choose a company page, LinkedIn may rely on text-based matching, which can introduce inconsistencies. 

Aggregation of parent and subsidiary companies

LinkedIn typically rolls all subsidiary employees into the parent company’s headcount. That’s helpful for scanning broadly, but it can mask meaningful differences in structure, growth, or focus – especially in corporate venture or strategic M&A scenarios. 

Affinity’s approach: Built for high-confidence investment decisions

To support deeper evaluation workflows, we created the Number of Employees column. A curated estimate designed to offer investment-grade data. It starts with LinkedIn but adds additional context and filtering based on our decade of experience supporting private capital customers. 

Here’s how our Data Team approaches the column:

Signal quality filters

We exclude profiles with incomplete information or employment histories that don’t pass basic validation. These profiles are rare in isolation but can distort data, particularly for fast-growing startups or sectors with lots of attention. 

Verified company matching

Instead of relying solely on company name matching, we match records to verified domains and cross-check them with other public and social signals to ensure the right entity is being enriched. 

Subsidiary distinction

We separate parent and subsidiary entities, providing a more detailed view of organizational structure. This helps with:

• Evaluating strategic acquirers and venture arms.
• Understanding competitive dynamics.
• Mapping market expansion opportunities.
• Benchmarking companies more accurately.

When to use each signal

Each signal serves a purpose. Here’s how we recommend using them across different workflows: 

Choosing the right signal

LinkedIn Headcount and Number of Employees each offer value, depending on what your workflow requires. LinkedIn Headcount is a familiar and straightforward signal that’s useful for scanning company size, spotting trends, or getting a sense of scale. We recommend using it in extensions like Affinity Pathfinder or Affinity for Outlook to support sourcing, early qualification, and portfolio monitoring through research and interactions.

Number of Employees is curated by Affinity to meet the demands of private capital workflows like diligence, benchmarking, and reporting. We recommend adding it to your deal pipeline lists, Monday Morning Meeting Kanban boards, and your dashboards in Affinity Analytics.

You can access both columns throughout your Affinity workspace, helping you apply the right context to every stage of your process.

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