How to build a prospect list with People Data Labs

A prospect list is a set of specific people at specific companies who fit your ideal customer profile and are worth contacting. People Data Labs supplies the raw material for one: a large dataset of professional profiles and a matching dataset of companies, both cleaned into standard fields. To build the list yourself, you write a query against its Person Search API, either in Elasticsearch's query language or in SQL, that filters on fields like job title role, job title level, company size, company industry, and country. Each request returns up to 100 matching records, and you page through the results to get more. You then save the records to a spreadsheet or load them into your CRM with your own script or import.

That route gives you a lot of control, but it asks you to do two hard things well. The first is writing a query that matches the people you mean. Job titles are messy, so a search for "VP Marketing" misses the "Head of Growth" who does the same job. People Data Labs helps by standardizing each title into a role, such as marketing or sales, and a level, such as director or VP, but you still have to know those fields exist and pick the right values. The second is judging the results. The search returns everyone who matches, sorted by how complete each profile is rather than by how well it fits, and each record you pull uses a credit. It also can't tell you who has changed jobs since the dataset was last updated, who's already a customer, or why any one person is worth a salesperson's time.

A good result is a list you could hand to sales today. Every person on it fits your profile, still holds the role, works at a company you'd want as a customer, and carries a work email or LinkedIn profile plus a short reason they were chosen.

Kite does that work for you. It turns your profile into a precise People Data Labs search, qualifies the people it returns, and delivers the list with the research attached.

Start by asking Kite in Slack for the list you want:

"Use People Data Labs to find 50 marketing directors and VPs at US software companies with 51 to 200 employees."

You can also hand it the accounts and let it find the people:

"Here's a CSV of 80 target companies. Find the head of marketing at each one with People Data Labs."

Kite is an AI marketer in your Slack. It researches your business, builds a growth strategy, and ships the work that brings you new customers. That research means Kite already knows your ideal customer profile, your current customers, and your competitors when you ask. It proposes the roles, seniority, company size, industries, and locations to target, along with how many people to deliver. Confirm the profile or adjust it, and Kite starts. Because People Data Labs charges a credit for each record a search returns, the list size you confirm also sets roughly how many credits the job uses.

You'll need to connect your People Data Labs account with its API key, so Kite searches and enriches through your account and your credits. If you want the finished list in your CRM, a Google Sheet, or Airtable, connect that account too. Otherwise Kite delivers the list in the Slack thread as a table and a file.

Kite writes your profile into People Data Labs' standardized fields, because those fields catch the variations that a plain job-title search misses. For the people, it filters on job title role and sub-role to set the function, and on job title levels to set seniority, such as director, VP, or the C-suite. For their employers, it filters on the company size range, company industry, and the person's country or region. When you name a specific title, Kite adds it alongside the standardized fields so the search stays close to what you asked for.

Kite checks its field values against People Data Labs before it runs anything. It reads the schema for person and company records and uses the autocomplete service to find the exact values People Data Labs recognizes for a title, industry, or skill. That way a search for fintech companies uses the industry label the dataset actually stores, instead of a guess that matches nothing.

Kite searches companies first when your criteria describe the account, and people first when they describe the person. A profile like "Series A software companies founded in the last five years" depends on company facts, so Kite runs a company search on fields such as industry, size, founding year, location, total funding raised, and latest funding stage. It then searches for the right people at the companies that match.

When the profile is mostly about the person, such as "VPs of marketing at mid-sized companies in the US," Kite runs the person search directly. When you supply your own list of target companies, Kite first cleans each company name or website with People Data Labs' company cleaner, so every account matches the right record before it looks for people there.

Kite reads how many records a query matches before it pulls the full list. Each search response reports the total number of matches, so Kite can tell when a query is too loose, with thousands of matches for a list of fifty, or too narrow, with only a handful. It tightens or widens the filters until the size of the match fits what you asked for, and only then pulls the records. This keeps your credits on people who could plausibly make the list.

When Kite pulls the records, each one arrives with the person's full name, job title, standardized role and level, current company, company website, company size and industry, location, LinkedIn profile, and work history. A work email appears when People Data Labs has one for that person.

Kite qualifies every person People Data Labs returns, because a search match is not the same as a good prospect. People Data Labs builds its dataset from many sources and updates it in periodic releases, so a profile can lag behind a recent job change. Kite confirms that each person still holds the role at that company, using their public profile or the company's own pages, and it drops anyone who has moved on.

Next, it removes your existing customers, your competitors, and anyone already in your CRM when one is connected. Every person who passes gets a fit score from one to five with a one-line reason, such as "Marketing director at a 140-person payroll software company that just raised a Series B." When the list runs past about fifteen people, Kite splits it into primary and secondary groups so your team knows where to start.

If fewer people qualify than you asked for, Kite tells you how many it found and why the rest fell short. A short list of strong prospects is worth more than a long one padded with weak fits.

Kite fills the gaps in each record with People Data Labs' enrichment services. When a search result is missing a detail, or when you started from names or LinkedIn profiles of your own, Kite enriches up to 100 people in a single request with the bulk person enrichment service. Company enrichment adds the account's employee count, industry, founding year, location, funding, and inferred revenue.

Kite keeps each work email exactly as People Data Labs returns it, and a missing email stays marked as not found rather than guessed. It includes only business details, so personal email addresses and phone numbers stay off the list. Kite can also add a timely reason to reach out from its own research sources, such as a recent funding round, a new marketing hire, or a product launch.

When the list is ready, Kite posts a summary in the Slack thread where you asked. It reports how many people it delivered against how many you asked for, how many have a work email, and who it dropped and why. The full list comes with it as a table you can scan in Slack and a file you can download.

If you connected a destination, Kite also saves the list there. It can add the people as contacts or leads in your CRM, linked to their companies, or write them as rows in a Google Sheet or Airtable base. From there, Kite can draft a personalized outreach email for each primary prospect. If you want fresh prospects regularly, ask Kite to run the same search on a schedule, and it will leave out the people it already delivered.

When Kite finishes, you have a qualified list of people your team can contact right away, and a record in Slack of how the list was built.