Spot product users who are ready for sales

You define a product-qualified lead by finding the usage your paying customers had in common before they paid, because that usage is different for every product. For a design tool, it might be sharing a file with a client. For a data product, it might be connecting a second data source. For a team tool, it's often inviting the third teammate.

Kite finds that pattern in your own data. With PostHog or Supabase connected, it lines up what each user did in their first weeks with whether they went on to pay, and it looks for the actions paying customers took far more often than everyone else. Typical signals include:

• Depth of use. The user completed your product's core job more than once, such as publishing a second report or running a fifth project.
• Spread across a team. The user invited colleagues, or several people from the same company signed up on their own.
• Steady return visits. The user came back on several different days in a week, not just once.
• Pressure on the free plan. The user reached a usage limit, tried a paid feature, or looked at your pricing page more than once.

Kite then combines the strongest signals into a definition you can read in a sentence. One example is "anyone on the free plan who has invited two teammates and created three projects within their first 14 days." Kite shows you how many of your past users met that definition and how many of them paid, so you can judge whether it's too strict or too loose. Once you agree, Kite saves the definition to your team's knowledge base. If your team uses Mixpanel, it can also record the definition in the notes your team keeps in Mixpanel about what your events mean, so everyone reads "sales-ready" the same way.

Kite finds the users who meet your definition while they're still active, because a personal note lands best in the same week someone is deep in the product. It can do this in two ways.

The first is a scheduled check. Every weekday morning, for example, Kite queries your Supabase tables or reads your analytics to find the users who crossed the line since the last check. In PostHog, it can save the definition as a cohort, a saved group of users that updates its membership on its own. In Mixpanel, it builds the same kind of cohort from what users did. In Amplitude, it can read a cohort your team already saved or save the users it identified as a new one. Kite delivers each morning's list to a Slack channel, by email from your team's Kite address, or as a conversation in the Kite web app.

The second is an event trigger. Kite gives you a web address for a workflow, and your product or PostHog calls it when something important happens, such as a user inviting a third teammate. Each call starts a fresh piece of work for Kite with that user's details. Kite sets up the connection in PostHog itself where it can, and otherwise gives you the steps.

Kite can also mark each flagged user inside your analytics, so your team sees the same list there. In PostHog, it sets a property on the person's profile. In Amplitude, it updates the user's properties. In Supabase, it can write a value such as a fit score into the rows you already have.

Your founder should reach out to the users who are both deeply engaged and a good fit to buy, and Kite checks the second part before anyone writes a word. Heavy usage on its own can come from a student, a competitor, or a freelancer who will never need a team plan. A product lead at a company that looks like your best customers is a different conversation.

For each flagged user, Kite starts with their work email domain and researches the company behind it with its built-in sources. That gives it the company's industry, headcount, location, funding, and recent news such as hiring or a new product launch. Kite then looks up the person's public professional profile to confirm their title, seniority, and how long they've been in the role.

Kite compares all of that with your ideal customer profile and scores each user from one to five, with a short explanation. A typical morning list might read like this:

• Score of five. The head of operations at a 180-person logistics company. This person invited four colleagues this week and has hit the free plan's project limit twice, and their company just announced a new warehouse.
• Score of three. A marketing manager at a 12-person agency who uses the product every day but works alone in it.
• Score of one. A heavy user with a personal email address and no company Kite could confirm. Kite notes how little it found and leaves the decision to you.

Kite separates facts it found from conclusions it drew, so you can see why each person made the list. The top of the list goes to your founder for a personal email. Everyone else stays in your regular onboarding emails.

Kite writes each email as a short, plain-text note from your founder, because a personal message from a real person is the one people answer. The note refers to the specific thing the user did, asks a real question, and offers one useful next step.

Kite builds each email from your product data, its research on the person, and what it knows about your product, positioning, and brand voice. A draft might read:

Hi Dana,

I noticed your team at Ridgeway set up three shared workspaces this week, and that you're bumping into the free plan's project limit. That usually means it's becoming part of how a team works.

I'd love to hear what you're using it for. If it would help, I'm happy to get on a 20-minute call and show you how other operations teams set up their projects. I can also extend your trial while you decide.

Sam

Each email is signed by the person you name, usually the founder, and only makes offers your team has agreed to, such as a trial extension or a call. With Gmail connected, Kite sends from your founder's own address, so replies land in their inbox. If your founder prefers to send each one by hand, Kite leaves the emails in the Gmail Drafts folder, ready to adjust and send. Without Gmail, Kite can send from your team's Kite email address.

Kite shows you each email before it goes out. Approve it with the button in the conversation or with a reply, and Kite sends it.

Kite records each product-qualified lead in your CRM, so the reason someone was contacted stays with their record. With HubSpot connected, Kite searches for the person and their company first, then creates or updates the contact and company records and links them together. It can store the reason the user qualified in a custom property, add a note summarizing their product usage and research, and create a follow-up task for your founder. When a user agrees to a call, Kite can open a deal and place it at the right stage of your pipeline.

Many replies come from the second message, so Kite follows up in the original Gmail thread when someone hasn't answered after a few days. Once Gmail is connected, Kite also checks the inbox every two hours and tells your team's owner when a product-qualified lead replies with a question or asks for a call.

Kite judges the program by whether the users it flagged became paying customers, because that shows whether the definition is right. A few weeks after the first emails go out, it checks who replied, who booked a call, and who moved to a paid plan, using your Supabase tables, your analytics, or your CRM.

Kite then compares the users it flagged with similar users who weren't flagged. If people who invited teammates upgraded at a high rate but people who hit the project limit rarely did, Kite proposes tightening the definition to favor the first signal. It records what it learned in your team's knowledge base, so the next round of flags and emails starts from those results.