Data enrichment: making faster, more informed investments

Your CRM is only as powerful as the data stored in it and how you use that data.

For private capital firms, the adoption of data has quickly become a non-negotiable in the deal sourcing and decision-making process. Automated data capture and enhanced analytics have propelled the shift to data-driven investing. But your own data alone isn’t enough to give VC firms a competitive edge in a private capital market where top firms are winning the lion’s share of high-quality deals. 

Enriching your CRM with sources outside your firm’s internal data can be the key to accelerating deal flow. CRM data enrichment plays a powerful role in helping firms source, manage, and close higher quality deals faster. 

Here’s how.

Key takeaways

• Data enrichment centralizes proprietary and third-party data to improve the accessibility and accuracy of data for VC firms. 
• Harnessing the power of enriched data equips dealmakers with the insights and context they need to improve deal quality and effectively evaluate investment opportunities.
• Data enrichment can be elevated with AI to increase speed to insight and impact future investment strategies.
• CRM and data enrichment tools, like Affinity, simplify data enrichment, empowering your team to make faster data-driven deal decisions.

The power of an enriched CRM

Platforms like Pitchbook and Crunchbase are great sources of information, but raw data, out of context, doesn't always help make decisions. You can review Company A's funding rounds and compare them to Company B's, but that single data point isn't enough to reach out for an introduction or pursue an investment opportunity.

Finding and using all the data available to you means it has to be accessible when you need it. This means being able to review details you already know about a company or person alongside the insights your data vendors have about them, and then being able to instantly update your deal flow pipeline. 

An enriched CRM takes the data your firm already has and automatically augments it with third-party sources. It consolidates relationship, market, and deal intelligence in one central source. It offers dealmakers additional insights and context when making deal decisions while sparing them from the effort of manually adding, sourcing, and accessing that external data—so they can focus on decision-making and relationship-building. 

Having a full picture helps your team identify clearer success signals sooner and make better investment decisions before your competitors.

Thinking about data as a product

When designing physical products for assembly, designers and engineers evaluate them based on a system's form, fit, and function (F3). A similar approach can be used to understand the value of data enrichment in the dealmaking process.

The F3 of data enrichment involves identifying the form the data takes, how it helps you find a good fit, and the day-to-day function of the insights it offers.

1. Form

Your CRM should form your system of record—even where external data is concerned.

Instead of relying on vendor databases, third-party data should be integrated directly within your CRM to enrich your existing records. That way, you can access data from subscription services in the same columns, rows, and fields you use to track your internal data. 

Access to unified datasets together means you can better understand the people and companies you’re talking to. It also makes it easier to maintain comprehensive data in real time. Consider a team member who learns new information on a call and can capture that within a CRM—manually or automatically. By layering these new insights onto enriched CRM data immediately, your team can stay ahead of a vendor’s weekly or monthly data refresh.

2. Fit

For physical products, the “fit” in F3 is about how different parts go together. Your CRM should work cohesively with your existing workflows to fit all relevant data and insights seamlessly into your dealmaking process. 

Almost half (49%) of dealmakers use four to six data sources when evaluating a deal. This quickly halts productivity if dealmakers have to spend time searching for specific insights and researching potential opportunities. Data enrichment helps bring the relevant insights directly to VCs right within the CRM.

3. Function

The function of CRM data enrichment is to create effective and repeatable decision-making processes, so you can be more confident in your day-to-day interactions with deal opportunities. Every stage of decision-making can be shortened without cutting corners.

Enriched data makes it possible for VCs to confidently prioritize, qualify, and respond to potential founders or management teams in every interaction. Quickly review market momentum signals alongside notes about your team's previous interactions. With a click, add these same data points—pulled from multiple sources—into analytics dashboards to compare them against other companies you’re evaluating, generating better informed investment decisions. 

Using AI to enrich your data

AI is transforming how investors are using data throughout the deal process. In the Affinity private capital predictions report for 2025, 64% of dealmakers said they use AI to research companies. While dealmakers aren’t necessarily using AI to directly make investment decisions, it can be a powerful tool for increasing insights from enriched data and elevating deal flow. 

In a webinar with Keith Camhi, Managing Director at Techstars, he highlights, “We don’t rely on AI, but I leverage it in our [investment] processes.”

AI and automation tools can simplify the data enrichment process. Not only can it scrape publicly available data sources and consolidate that information to boost data collection, but it can also analyze and sift through proprietary data to surface relevant deal insights, which streamlines the use of data in the VC deal sourcing workflow.

Similarly, technology has enabled AI-driven deal sourcing with quantitative models capable of ranking potential deals based on past investment successes, market conditions, and other firm-specific criteria. Peter Mitchell, Data Scientist at the University of Oxford and Head of Origination at Future Planet Capital initially developed his firm’s scoring model by pulling data from individual external sources into Google Sheets. By layering his scoring system over a centralized data source, in Affinity CRM, the firm was able to better surface those signals and improve investor decision-making. “[My colleagues] were impressed with some of the data they thought was impossible to collect or identify,” Mitchell shares about their data enrichment efforts and current tech stack.

“What we ended up with was a main juggernaut of a scoring system and a front end that more people could access,” he adds. “With a way to present projects that meet the specific thesis of certain funds.” Future Planet Capital now uses over half a million data points in their investment and lead scoring process. 

The more data points the scoring algorithms have to work with, the stronger the models and outputs. By uncovering these patterns and signals in the data, AI can surface high-potential deals, including those that may have been missed through manual review processes. 

Camhi emphasizes that in his team’s investment strategy, AI doesn’t outweigh human reviews. Rather, it’s used to flag and avoid false negatives—when high-potential opportunities are scored low in the manual review process—particularly when deal flow volume is high. Read our guide to learn more about the ways in which AI is changing private capital dealmaking.

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Improve deal quality with enriched data

Data enrichment helps VC firms paint a better picture of potential opportunities, especially in the early stages of the investment process, where available insights can be sparse. “Every VC, no matter what stage, has to find the signals that get you comfortable to make this huge leap, to take on this enormous risk,” shares Vanessa Larco, Former Partner at New Enterprise Associates, in a conversation focused ondue diligence. 

By bolstering existing data with as much of a company’s growth, funding, and firmographic information as possible, it becomes easier to qualify and prioritize opportunities. You can find thesis fits faster and segment contacts by specific sets of data to build more targeted investment lists.

Being able to refine shortlists and longlists quickly accelerates deal velocity, so you can also source and win more opportunities that fit your thesis.

Beyond initial screening, bolstering your data source allows dealmakers to conduct more thorough due diligence based on their unique investment criteria. "I think every VC, after five or six years, starts finding their own unique way of doing diligence,” says Larco. “At the highest level, we all look at team, team market fit, market size, TAM, and product metrics." 

Ensure you have every base covered with our due diligence checklist.

Use data enrichment to create self-improving systems

An enriched, comprehensive CRM doesn’t end with relationship intelligence, firmographic, and funding data. Your team’s wins, losses, and everything in between can also work to enhance your datasets. 

As you close more deals and see the outcomes of your investment decisions, you can use those learnings to inform your own custom data engine and lead scoring models. The result is a feedback loop where historical results can be used to refine your investment strategy and inform future deals and data needs.

The more a firm uses enriched CRM data the more effective dealmakers are at identifying relevant data insights within the CRM, compounding success over time. Your CRM ultimately becomes a single, connected system of information and action that creates a self-sustaining, upward spiral that supports finding and managing your most important deals.

Make faster, data-driven decisions with Affinity

Affinity’s relationship intelligence platform empowers dealmaking teams with the enriched data and CRM they need to find, manage, and close high-quality deals. 

With Affinity’s data enrichment capabilities, private capital firms can:

Create a centralized data source

Your data’s value is maximized when it’s all easily accessible in one reliable source. Rather than contending with outdated or incomplete information, Affinity helps dealmakers make decisions faster, knowing that all the relevant insights are automatically updated.

Affinity then surfaces those real-time data points in the tools you use every day, such as your browser and email, so your deal teams can access that data directly within their existing workflows.

Reduce time spent integrating data into your CRM

Spend less time manually moving insights around and more time sourcing deals. Automatically integrate your firm’s network and deal data right into your CRM with the Affinity API to generate an up-to-date system of record, complete with unique, hard-to-find data points.

With Affinity, you can create a unified dataset right within your CRM, eliminating time spent toggling between vendors and data sources. 

Access a comprehensive dataset you can trust

Every company and personal profile in Affinity is automatically enriched with firmographic, biographic, and funding data, so you can feel confident in the data you’re using to make deal decisions. 

In addition to Affinity’s proprietary data engine, Affinity seamlessly integrates with over 40 industry-leading data sources, such as Pitchbook, Crunchbase, and Dealroom, enabling dealmakers to access additional data points and analytics reporting right within Affinity CRM.

Using another CRM provider? Affinity for Salesforce transforms the Salesforce experience, helping deal teams unlock relationship insights, activity capture, and data enrichment right within the Salesforce CRM. 

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Data enrichment FAQs

What is an example of data enrichment?

An example of data enrichment is adding the last funding date or a company size to an organization’s profile in a CRM. Another example is adding a person’s phone number and job title to their CRM customer profile. This information can be imported manually or automatically using integrations with data enrichment tools and third-party sources to enable faster, higher-quality deal decisions.

What are the benefits of data enrichment? 

Data enrichment comes with many benefits, such as:

• Improving the quality and completeness of existing data.
• Elevating decision-making with access to additional context and deal-relevant insights.
• Reducing the risk of errors in the dealmaking process.
• Unifying data across multiple data sources.
• Improving customer relationship building with relevant information and data for contacts in your firm’s network,
• Increasing deal productivity by eliminating time-intensive research.
• Personalizing messaging and outreach with relevant company and customer insights.

Purpose-built tools, like Affinity, can help private capital firms maximize the benefits of data enrichment services, such as integrations with trusted third-party data sources, automated activity capture, and APIs for cross-system data sharing.

What is the difference between data enhancement and data enrichment?

Data enhancement primarily focuses on boosting—or enhancing—the quality of the data you already have. For example, when enhancing data, you might replace outdated information, correct data errors, or complete missing data fields. 

Data enrichment focuses on integrating additional data from outside or third-party sources to create more robust datasets that help dealmakers make better-informed deal decisions. For example, adding additional demographics and data fields to customer data profiles.

What is the difference between data enrichment and data cleansing?

Data cleansing is the process of cleaning up your existing data set by removing or replacing redundant, obsolete, or incorrect data points to maintain data quality and data accuracy. For example, replacing old contact information and contact data or outdated LinkedIn profiles with updated, accurate data.

Data enrichment is the process of adding additional data points to the data your firm already owns to offer dealmakers additional context and insights to inform dealmaking decisions. For example, adding technographic insights to company data.