What is data enrichment?
Data enrichment is the process of information about your lead that helps you know or understand the lead better, contact them easily, and engage with context. It refers to adding contact data, company data, market data, firmographics, and other such insight that helps sales teams be more precise with their outreach efforts.
Earlier, data enrichment only meant adding phone numbers and email addresses for every lead in your account book.
But the world of sales has changed.
The new way of outbound selling requires you to enrich your contact data with a lot more information and insight. Some data enrichment examples include real-time updates on a lead’s social media interactions, a contact’s recent website activity, or their job changes.
We have a lot more data enrichment examples, data enrichment use cases, and some tips for you to make the best of data enrichment tools for your sales process. Read on!
Benefits of data enrichment
Here’s why data enrichment should be an important part of your go-to-market strategy. Without enrichment and signals, even the best ideal leads lack context, making outreach ineffective.
Here are the other benefits:
Precise sales outreach – Gain insights into roles, interests, and engagement patterns to craft relevant messages.
Lead prioritization – Use intent data and social signals to focus on high-potential prospects.
Updated CRM – Keep CRM data fresh to eliminate time wasted on outdated or incomplete records.
Scalable outbound sales – Enable teams to focus on selling, not data cleanup and CRM update.
Enhanced marketing precision – Create highly targeted and effective campaigns.
Improved customer experience – Engage prospects with relevant, timely, and personalized interactions.
Greater operational efficiency – Reduce manual work and streamline workflows with accurate, real-time data.
Data enrichment examples
Adding any kind of information or insight to a piece of information can be considered data enrichment. In the B2B world, however, data enrichment refers to enhancing and augmenting basic information about a contact or company with other information that helps understand them better.
There are many types of data that can be enriched.
Here are some of the common types of data enrichment you see in a B2B company:
- Customer data: name, phone number, email ids, title/designation, education, previous work experience, LinkedIn url, demographic details, firmographic details, etc.
- Company data: name, domain, industry or sector, employee headcount, company location, company contact details, leadership team, funding details, etc.
- Product data: technology type/tech stack, key features or functionality, etc.
- Transaction data: contract details, invoice number, key points of contact, start date, etc.
- Social data: LinkedIn url, recent activity, new connections, licenses and certifications, skill set, language expertise, LinkedIn posts, enriches: LinkedIn last active date, LinkedIn last activity, LinkedIn followers count, LinkedIn connections count
- Signals: Social engagements such as likes and comments, website visits, event participation, etc.
What are some examples of data enrichment?
The data enrichment process usually includes updating the CRM with information such as:
Contact information
Data that enhances basic details with identifiers and information such as:
- Job titles and roles within the company
- Direct dial numbers or alternate contact methods
- LinkedIn, Twitter, Instagram, and other social profiles
- Professional certifications or affiliations
Company details
Comprehensive details about a company that helps in account targeting and segmentation. Examples include:
- Industry type and focus
- Headquarters location and geographic presence
- Company size, including revenue and employee count
- Names of company leaders and members of the C-Suite and Board of Directors
- Technology stack or tools in use
- Recent funding rounds or acquisitions
Intent data
Information that indicate a prospect’s buying intent, such as:
- Website visits and specific page interactions
- Content downloads, such as whitepapers or ebooks
- Engagement on review sites or industry forums
- Searches for competitor comparisons or product alternatives
Social signals
Activity on social media platforms such as LinkedIn, Twitter, Meta, etc. such as:
- Engagement (likes, shares, comments) with company or competitor posts
- Participation in LinkedIn discussions or Twitter threads
- Following or connecting with specific influencers in the industry
- Sharing relevant articles or thought leadership content
Firmographic data
Specific details that help analyzing and segmenting companies based on attributes like:
- Market position and growth trajectory
- Target customer base or audience segmentation
- Regional or global footprint
- Business model (B2B, B2C, SaaS, etc.)
Behavioral or personality intelligence
Information that helps understand a person better, such as:
- Preferred communication channels (email, phone, social)
- Past responsiveness to campaigns or outreach
- Behavioral patterns and engagement habits
- Personality traits or cultural preferences
Competitive insight and competitor data
Competitor-related information provides valuable context, such as:
- Interactions between your ICP and your competitor
- Gaps in competitor offerings that your product can fill
- Pricing models or discounts offered by competitors
- Engagement with competitor campaigns or events
Customer or usage data
Insights into how customers use your product or service:
- Feature usage patterns or engagement metrics
- Support tickets raised or resolved
- Renewal history and contract timelines
- Satisfaction scores or feedback from surveys
Geographic and demographic data
Factual data enhancing information about the company, including:
- Location-specific details, such as time zones or regional preferences
- Demographics like age, gender, or professional experience
- Regional market trends or cultural insights
Technographic data
Understanding the technology a company uses:
- Cloud platforms, CRM tools, or ERP systems they rely on
- Software solutions they’ve recently adopted or phased out
- Compatibility between their tech stack and your product
Psychographic data
Understanding attitudes, values, and motivations of the person, such as:
- Interests or passions expressed through social media or surveys
- Goals or challenges highlighted in interviews or forums
- Content preferences based on engagement history
Data enrichment sources
The kind of insight you get about a contact depends on the source you go to for data enrichment.
For example, data enrichment using first-party sources such as social media or website visits can give you insight about the lead’s behavior, interest, buying intent, etc. Using other publicly available third-party sources of data enrichment can give you perspective and information about the big picture, such as the company’s business model, revenue goals, etc.
Here are the broad categories and examples of data enrichment sources:
- First-party data: data collected directly from the company's website (forms, downloads), social media, surveys, and email interactions.
- Public data: legally accessible data like legal documents, company websites, news articles, and public forum content.
- Third-party data: Information from vendors specializing in information collection, including sales intelligence tools, public/online databases, and event data.
- Internal databases: Information within the company's systems, such as transaction histories, customer feedback, CRM data, and employee input.
Data enrichment use cases with examples
The data enrichment process is the means to an end, or the goal of achieving better sales outcomes and scaling outbound sales. There are many pieces of information with which you can enrich a lead. For example, you can use AI to enrich a lead with insight such as
- Social and LinkedIn activity
- Recent job change information
- Major topics of interest
- Commonly used keywords
Here are some data enrichment examples and use cases for B2B companies:
Buying signals based on website visits to prioritize leads
One of the best data enrichment examples is augmenting your CRM and basic contact data with buying signals. Tracking buying signals and intent data is now a lot easier with the availability of AI data enrichment tools, so you’ll be able to get the latest data on who visits your website, what pages they track, who else they engage with on social media, etc. Sales teams can use this to prioritize the contacts they reach out to and ensure that they don’t miss out on any leads who are keen on buying immediately.
Social activity insight for personalized conversation starters
Most of your contacts spend a lot of time on social media platforms like LinkedIn engaging with their peers, posting about their professional achievements, or discussing ideas. You can learn a lot about your contacts by observing their social media behavior and tracking activity. This is another excellent data enrichment example. By enriching your CRM with social activity insight about every lead, you will be able to tailor and personalize the conversations you have with them. This will lead to better response rates and better conversions.
Job change tracking for timely outreach
Data enrichment involves supplementing basic information about a contact with anything that might help sales teams reach out to them easily. A perfect example of data enrichment is enhancing basic data with a contact’s career history and job change information. Data enrichment tools can track job changes and alert your team, allowing them to reach out with relevant solutions at the right moment. Your sales team can proactively engage with them and pitch your product.
Technographic information for better solutioning
This refers to enriching company information, and not necessarily an individual’s data. While targeting a particular account. For example, enriching your CRM with technographic data helps sales teams understand what other products the company uses, enabling them to position your product well while making a pitch.
Signals and intent data for clear segmentation and targeting of lead lists
By enriching your CRM with first-party signals and intent data, you can segment your leads better and prioritize your leads based on how likely they are to convert. AI-native tools like Highperformr enable you to enrich your lead lists with real-time first-party data and signals that help you identify and categorize leads, such as hot leads that are ready for a pitch, high-value leads that are not ready to buy now but will buy later, leads that require nurturing, etc.
Data enrichment process
Data enrichment is the process of turning raw data into actionable data by enhancing it with additional information. But data enrichment is usually a multi-step process, and needs to be done on a continuous basis to ensure that the CRM is enriched with real-time data . Here’s what it entails:
Step 1 - Data assessment
Data enrichment begins with evaluating and assessing the quality of data on hand before enriching and enhancing it. This involves cross verifying the data for accuracy and evaluating how relevant it is to your company’s current requirements and what kind of additional information is required to help achieve your company’s goals.
Step 2 - Integration
Once the assessment is done, you will have to select one or a combination of the sources discussed above, and enrich your database with information from the other data sources.
Step 3 - Continuous updates
Data enrichment isn’t a one-time or ad-hoc process. It is critical to keep the CRM updated with real-time first-party data. This requires automating the process of data enrichment and using AI tools to keep every contact or record enriched with the latest information and signals.
Data enrichment best practices
Getting your data enrichment right can make or break your go-to-market strategy. Here are some best practices you can follow:
Use AI and automation
Ai-native tools and data enrichment platforms help with real-time first-party enrichment, easy bulk enrichment at scale, and accurate enrichment of contact and company data.
Define your goals
Know exactly why you're enriching data. As we have seen in the data enrichment examples above, some kinds of enrichment help enhance cold outreach, some help with lead prioritization, and certain other types assist with targeting.
Specify data requirements
Determine exactly what kind of data you need. Is verified contact information critical, do you need competitor insights to put you ahead of others, do you need details on the tech stack, etc.
Use multiple data sources
Each data enrichment source offers a different kind of value. Use data from multiple sources, and also cross-verify information to ensure accuracy and reliability.
Maintain privacy standards
Follow data protection regulations (such as GDPR, CCPA) and be transparent about data usage.
Enable cross-team access
Breaking silos and enabling all go-to-market teams access data enrichment tools ensures that the enriched data syncs seamlessly with all sales and marketing tools.
Update continuously
Data enrichment has to happen in real time to ensure that the most recent and relevant signals about a contact are available for the sales teams. Make data enrichment in your organization an ongoing rather than one-off process.
Data enrichment tools and solutions
A data enrichment tool, also referred to as sales intelligence tools, lead enrichment tools, prospecting tools, or CRM enrichment tools are software products that provide B2B businesses access to databases with information about a person or a company.
We conducted extensive research into the data enrichment tools available in the market today and curated a list of the top 15 data enrichment tools for B2B companies. Here’s a preview of top players like Zoominfo, Apollo, Clay and more.
You will see that the best sales intelligence tool available today is Highperformr. The AI-native sales intelligence and workflow automation platform simplifies and streamlines data enrichment, making it both easy and accurate. It enables businesses to enhance their data with real-time signals and intent insights and also provides precise contact details like email addresses and phone numbers through a reliable waterfall model.
To learn more about how Highperformr helps with data enrichment, schedule a demo with our team today and sign up for a free trial in the meanwhile so you can play around with the tool!
