How do I score a list of leads against my ideal customer profile?
You score a list of leads against your ideal customer profile by writing the profile as criteria you can check, verifying each lead against those criteria, and giving every lead a score with a reason attached. Your ideal customer profile describes the companies most likely to buy and succeed with your product, plus the people inside them who make or influence the decision. A typical B2B profile covers company traits, such as industry, employee count, location, funding stage, and the tools a company already uses, and person traits, such as job function, seniority, and title.
The hard part is making the profile testable. "Fast-growing B2B software companies" can't be checked against a lead. "B2B software companies with 50 to 500 employees in North America that raised a Series A or B in the last two years" can. Every vague trait in the profile becomes a judgment call on every lead, so tightening the wording first saves you from scoring the same kind of company differently on different days.
Most CRMs have scoring built in. HubSpot's lead scoring tool, on its Professional and Enterprise plans, lets you add points for property values such as industry, company size, or job title, and keep a fit score separate from an engagement score. Salesforce offers Einstein Lead Scoring, which learns from the leads you've converted in the past. Apollo has its own scoring, built on the contact and company attributes in its database.
These tools score what's already on the record, and that's where they stop. A list from an event, a purchased database, or an old export usually has empty industry fields, missing employee counts, and job titles from a year ago. A rule that adds ten points for "VP of Marketing" will happily score someone who left that job in the spring. Points models also blur the reason for a score: a lead with 62 points could be a perfect company with the wrong person or the right person at a company that's too small, and the number alone doesn't tell you which.
A good result is a list where every score means the same thing and can be defended. Each lead has been confirmed as current, checked against the profile with evidence, and scored with a reason a salesperson can read in a few seconds. The strongest fits sit at the top, and the leads that don't fit are gone rather than buried at the bottom.
Kite does this work for you. It checks each lead against your profile, scores the fit with a reason, and puts the ranked list where your team will use it.
How to get started
Start by giving Kite the list and telling it what you want back:
"Score the 300 leads in our Q4 event list against our ideal customer profile and tell me who to contact first."
Kite is an AI marketer. It researches your business, builds a growth strategy, and ships the work that brings you new customers. You can work with it in the Kite web app or in Slack. During onboarding, Kite researched your company, your customers, and your competitors, and it keeps what it learned in your team's knowledge base, including the profile of the customers you sell to. So Kite already has a starting profile when you ask. It turns that profile into one testable sentence, shows it to you, and asks about anything it can't settle on its own. Confirm the profile or change it, and Kite starts.
Kite can work from a list wherever it lives. Point it at a Google Sheet, name a list or a set of leads in your connected HubSpot or Salesforce account, share a CSV file in Slack, or paste the names and companies straight into the conversation. Connect your CRM or Google account through OAuth when you want Kite to read the list there or write the scores back. The research behind each score uses Kite's built-in sources, such as Apollo, Crustdata, and PredictLeads, so you don't need accounts with any of them.
If Kite can't find a profile in its research and you haven't described one, it asks you for the roles and companies you're targeting instead of scoring against a guess.
How Kite scores leads against your profile
What goes into the profile?
Kite writes your profile as one sentence that can be tested against a single lead, and it uses that same sentence for every lead on the list. It draws the company traits and the person traits from your knowledge base and from the request itself. If you said the list feeds an email campaign, it knows each lead needs a professional email address. If you said it feeds event invitations, it knows location matters.
Kite treats time-sensitive traits carefully. If your profile says "Series A or B," Kite checks the company's latest round of equity funding, because a later loan or grant doesn't change a company's stage. If the profile says "currently runs marketing," it needs current evidence of that, not a title from an old import.
The profile also names who to remove. Kite reads your existing customers, your competitors, and anyone who has opted out of hearing from you, so none of them end up on the list as prospects.
Is the lead still current?
Kite confirms that each person still holds the role at the company before it spends any effort scoring them. It checks the person's current role and employer against a public source, such as their professional profile or the company's own team page. People who have moved on are dropped, and recent title changes are noted, because someone who was just promoted into the role you sell to is often worth an early conversation.
This step comes first because it's the cheapest way to remove bad leads. A list that's six months old can lose a meaningful share of its people to job changes, and there's no point checking company size for a person who no longer works there.
Does the lead match each part of the profile?
Kite checks the lead against the profile's criteria in order of cost, quickest checks first. After confirming the person is current, it applies the simple filters: location, membership in the target group, and the exclusions for customers, competitors, and opt-outs. Then it does the slower research on the leads that are left.
For the company, Kite looks up the domain, industry, employee count, headquarters, funding, and the technology the company uses. For the person, it reads the title, seniority, and job function, and the LinkedIn profile when one is public. When a lead arrives with blank fields, Kite fills them from its research instead of scoring the gap as a miss. When two sources disagree, such as two different funding stages, Kite resolves the conflict before it accepts or rejects the company.
Kite keeps a running record as it goes: which leads passed each check, which failed, and the specific criterion each rejected lead failed. That record is what lets it explain the final count later.
How is each lead scored?
Kite scores every lead that passes the checks from one to five against your profile, and it writes a one-line reason for each score. A five matches the profile on company and person, with evidence for each part. Lower scores mean a lead matches on some criteria and falls short on others, and the reason names the shortfall. A reason reads like a note from a colleague, such as "Head of growth at a 120-person payments company that's hiring two demand-generation roles."
The reason matters as much as the number. It tells a salesperson what to open with, and it lets you spot a scoring mistake at a glance. A score of three with "right company, but the contact is in finance, not marketing" points to a different action than a three with "right person, but the company has 15 employees."
When the list runs past about fifteen leads, Kite splits it into primary and secondary groups, so your team knows exactly where to start.
Which leads are worth contacting now?
Kite separates fit from timing. A strong fit tells you a company could buy, and a recent event tells you why it might buy now. Using Crustdata and PredictLeads, Kite looks for events at each company, such as a new funding round, a jump in headcount, a leadership hire, or a new office. With Apollo, it can also read a company's open job postings.
Kite only counts events from roughly the last 90 days, because an older event is no longer a reason to get in touch today. It records what happened, when, and the source for each one. An event never raises a poor fit into a good one. It only tells you which of your good fits to call this week.
Where do the scores go?
Kite puts the scored list where your team will act on it, and it always posts the table in the conversation as well. Every row carries the person's name, title, company, LinkedIn profile, fit score and reason, and the source that supports it.
- HubSpot. Kite searches your contacts by email address, writes the fit score and its reason into contact properties, and creates those properties if your account doesn't have them yet.
- Salesforce. Kite searches your leads and writes the score and reason into fields on each one, or creates a new lead when a person isn't in Salesforce yet.
- Google Sheets. Kite writes the score, reason, and source into columns beside each lead, or adds the scored list as new rows.
- A CSV file. When you ask for a file, Kite delivers one row per lead with the name, title, company, company domain, LinkedIn URL, email, email status, email source, fit score, fit reason, source URL, and the recent event when there is one.
If you also asked for contact details, Kite adds a professional email for each lead and keeps the provider's verification status exactly as it was returned, whether that's verified, catch-all, risky, or unverified. It leaves out personal email addresses and phone numbers.
What Kite reports back
When the scoring is done, Kite tells you how many leads it delivered against how many it started with, and how many failed each check and why. It says how many rows have a professional email. If fewer leads qualified than you hoped, it shows you exactly where the list thinned out, so you can decide whether to loosen the profile or find more leads.
From there, Kite can write a personalized email for each primary lead, built from the reason and the recent event, and send it from your team's Kite email address or a connected email product once you approve. If you'd like new leads scored as they arrive, ask Kite to run the same job on a schedule, such as every Monday.
What the finished work contains
When Kite finishes, you have a ranked list you can act on the same day, and a clear record of why each lead is on it.
Fit scores
Every lead that passed the checks has a score from one to five, measured against the same written profile.
Reasons
Each score has a one-line explanation that names what matches and what falls short.
Primary and secondary groups
Longer lists are split so your team knows who to contact first.
Recent events
Leads with a funding round, a hiring push, or another event from the last 90 days carry it, with its date and source.
Sources
Every row links to the public page that confirms the person's role and company.
The removals
The summary lists who was dropped and the criterion each one failed, so nothing disappears without an explanation.
Updated records
When you asked for it, the scores and reasons sit in your HubSpot contacts, your Salesforce leads, or your Google Sheet.
Common questions
What's the difference between fit scoring and engagement scoring?
Fit scoring measures how closely a lead matches your ideal customer profile, while engagement scoring measures what the lead has done, such as opening emails or visiting your pricing page. A list of possible buyers who haven't interacted with you yet has no engagement to score, so fit is the score that matters first. Once those leads start responding, engagement tells you who's warming up.
Should I use a points model or a simple scale?
A simple scale with a written reason is easier to trust and act on than a points total. Points models add up many small weights, and two leads with the same total can fit for completely different reasons. A one-to-five score with a reason tells a salesperson both how good the fit is and what to say first.
What if I don't have a written ideal customer profile yet?
Kite can define one before it scores anything. It studies your current customers, your positioning, and your market, and proposes the company and person traits your best customers share. Once you confirm the profile, Kite saves it to your knowledge base and uses it for this list and every list after it.
How often should I rescore my leads?
Rescore a list whenever you're about to work it again, because people change jobs and companies grow, raise money, or shrink. Kite rechecks each person's role and refreshes the details that change, such as headcount and recent events, while keeping the research that's still current.