I don't know of any B2B business that doesn't perform some form of contact and company enrichment to make go-to-market decisions. Regardless of the motion, good enrichment is table stakes for a holistic user experience.
There are a couple of very common problems. First, data inaccuracy is prevalent, and second, enrichment costs become very expensive as the business grows. The advent of waterfall enrichment is really just a solution to bad data dressed up as an advanced technique. On the cost side, businesses commonly find themselves suddenly spending $250,000 a year simply because they became successful. This is especially common in product-led growth (PLG) businesses where high volumes of sign-ups require enrichment.
That's us, we're a PLG business and we get a lot of sign ups. We also want to enrich and classify sign ups so that we can then power our lifecycle marketing and sales-assist motions. So we built an AI agent to do it better than we could ever do with enrichment providers.
Using an AI Agent to enrich users
Our agent is designed to function as an autonomous researcher, analyst, and CRM updater—all in one integrated solution. The process begins by categorizing the email address provided during sign-up. Using a sophisticated prompt, our AI agent can determine whether the email is likely to be a work or personal address.
This initial categorization is crucial because while we can enrich both personal and work email addresses, each requires a distinct process. Personal email enrichment undergoes significantly more rigorous verification checks to ensure the validity of our conclusions. This additional scrutiny helps maintain data integrity and prevents the addition of unreliable information to our CRM.
The differentiated approach serves several purposes:
- Work emails typically contain more reliable company-related information
- Personal emails require cross-referencing with multiple data sources for verification
- Enhanced validation helps prevent false positives that could compromise CRM data quality
- The system maintains compliance with data privacy regulations while gathering enrichment data
By implementing these careful distinctions in our enrichment process, we can maintain high data quality standards while still gathering valuable insights from both personal and professional email addresses.
The second phase involves comprehensive data collection about both the individual user and their company. Our Agent employs a straightforward but effective approach to this task.
The Agent begins by utilizing Google search to locate the user's LinkedIn profile through a sophisticated process. It executes multiple targeted search queries to ensure accuracy while employing advanced stack-ranking algorithms to identify the correct profile. The system then performs cross-validation of data points to confirm user identity and implements thorough verification steps to eliminate false matches. This methodical approach offers two significant advantages: it maintains cost-effectiveness compared to traditional data enrichment services, and it ensures high data accuracy since professionals typically maintain current LinkedIn profiles with their latest professional information.
For company information, the Agent conducts a more extensive analysis, gathering comprehensive firmographic data including employee count, revenue, and industry classification, along with recent company developments, news, and organizational changes. It also analyzes market positioning and competitive landscape while tracking notable company milestones and achievements. Going beyond basic company information, the Agent uncovers valuable insights such as recent funding rounds, acquisitions, leadership changes, product launches, market expansion initiatives, and industry recognition or awards. This thorough approach to company research ensures a complete understanding of both the organization's current status and its trajectory in the market.
Finally, the Agent classifies each individual's role into standardized job functions and seniority levels to maintain data consistency. This classification enables precise reporting analytics and provides valuable insights into our user demographics. Beyond basic categorization, this structured approach helps us understand user acquisition patterns, track engagement across different professional segments, and refine our go-to-market strategy based on the types of professionals our product attracts.
What's next
We would like to expand to the users' professional interests and technology investments, particularly their engagement with emerging technologies like AI. By examining their social media activity, including liked posts and shared content, we could better understand their professional priorities and interests.
We'd also like to enhance our company-level enrichment. By implementing intelligent website analysis, we could better classify businesses based on their digital presence, technology stack, and market positioning. This could include analyzing their content strategy, product offerings, and overall digital maturity.
Watch the user enrichment agent in action
