How to save prospect research to Notion

To save prospect research to Notion, create a database with one row per account and give it properties for the facts you want to compare across accounts. Typical properties are the company name, website, industry, employee count, a fit score, a status such as Researching or Ready for outreach, and an owner. Each row in a Notion database is also a page, so the longer research goes inside it: what the company does, why it fits, who to contact, and what's happening there right now. A database template can give every new row the same headings, so each brief follows the same shape.

Notion helps you collect material along the way. The Notion Web Clipper saves a web page you're reading into a database you choose, which is handy for a company's About page or a news article. Notion AI can summarize what you've pasted in and draft text on a page. What Notion doesn't do is the research itself. It won't tell you which companies match your ideal customer, whether the person you're targeting still works there, or that the company raised money last month.

That's the real work in this job. A good result is a database where every row is an account worth pursuing, the facts are current and sourced, no company appears twice, and the brief inside tells a salesperson why to reach out now and what to say. Research that lives in scattered pages, or in rows with only a company name filled in, rarely gets used.

Kite does that work for you. It finds or researches the accounts, decides which ones fit, and writes each one into your Notion database with the properties filled in and the brief on the page.

Start by telling Kite which accounts you want researched and where the research should go. You can hand it a list:

"Research these 20 companies and add them to our Target Accounts database in Notion."

Or you can ask Kite to find the accounts first:

"Find 25 B2B software companies in the UK with 50 to 300 employees that are hiring for marketing, and save the research to Notion."

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 Kite in your browser or in Slack. Kite already knows your ideal customer profile, your current customers, and your competitors from its research on your business, so it can propose which company traits and job titles to target without a long brief. Confirm the profile or adjust it, and Kite starts.

You'll need to connect your Notion account so Kite can read and write your pages. When you connect, Notion asks which pages Kite may open. Choose the database you already use for account research, or the page where you want Kite to create a new one. You don't need any research tool accounts of your own, because Kite has built-in data sources, including Apollo for companies, people, and work emails, and Crustdata and PredictLeads for funding, hiring, and company news.

Writing research into your own workspace is routine work, so Kite adds the rows and then tells you what it did. If you'd like to see the list first, say so in your request.

Kite puts prospect research in a Notion database when you're tracking more than a handful of accounts, because a database lets your team sort, filter, and assign them. A single Notion page suits one deep account brief before a big meeting, and Kite can write that too, with headings, bullet lists, and tables. If you already have a research database, Kite uses it.

If you don't, Kite creates one under the page you chose. It sets up properties for the company name, website, industry, employee count, location, fit score, the reason for the score, status, owner, and the date it last checked the research. If your existing database is missing a property the research needs, such as a fit score, Kite can add that column.

A Notion database is different from a report Kite publishes. A published Kite report is a separate page on its own shared link, with charts and tables, built for reading. A Notion database is a working list that your team edits, assigns, and moves through stages. For prospect research your team will act on, the database is usually the right home.

Kite decides which accounts belong in the database by checking each company against your ideal customer profile before it spends time on a full brief. When you give it a list, it researches the companies on it. When you ask it to find accounts, it searches by industry, headcount, location, funding, the technology a company uses, and hiring activity, and it can find companies that resemble ones you already sell to.

It removes your existing customers and your competitors. It then scores each remaining account from one to five with a one-line reason, such as "120-person payments company that just opened two demand-generation roles." When the list runs long, Kite splits it into primary and secondary groups so your team knows where to start. If fewer accounts qualify than you asked for, Kite tells you how many it found and why the others fell short.

Kite researches each account the way a careful salesperson would, and it cites a source for every fact. It reads the company's website to learn what it sells and who it sells to. It pulls headcount, industry, revenue, funding, and the technology the company uses, and it looks for recent events such as a funding round, a leadership change, a product launch, or open job postings.

Kite then finds the people worth contacting by job title, function, and seniority. For each person, it confirms they still hold the role and records their title, LinkedIn profile, and a professional email address when the source provides one. It labels anything it inferred, such as a likely priority for the coming quarter, so a reader can tell an inference from a sourced fact.

Kite searches your Notion database before it adds anything, so the same company never appears twice. It matches rows by the company's website domain, which stays the same even when people spell the company's name differently.

When a row already exists, Kite updates it with the new findings instead of creating another. Before it writes, it reads the database's properties to learn their exact names and types, including the select options your team already uses for status or industry. That way each fact lands in the column your team expects, in a format Notion accepts.

Kite writes each account as a row, fills in its properties, and then writes the brief on the row's page. The properties carry the facts your team filters on:

• Company name and website
• Industry, employee count, and location
• Fit score and its one-line reason
• Status, such as Researching or Ready for outreach
• Owner, chosen from the people in your Notion workspace
• The date Kite last checked the research

The page inside the row holds the brief, under clear headings. It explains what the company does, why it fits your ideal customer, what has changed recently and why that makes now a good time to reach out, and who to contact, with each person's title, LinkedIn profile, and email status. Sources sit beside the facts they support. If your database has a template for new rows, Kite follows its headings.

If you keep people in a separate contacts database linked to your accounts database, Kite adds each person as a row there and links it to the account. It can also leave a comment on a row to flag something for a teammate.

When the work is done, Kite posts a summary in the conversation where you asked. It says how many rows it created, how many existing rows it updated, and which accounts it skipped and why. It also links to the database and lists the primary accounts, so you can start with the strongest ones.

From there, Kite can draft a personalized first email for each primary contact using the research on the page. If you want the research kept fresh, ask Kite to run the job on a schedule, such as every Monday, and it will add new accounts that match, update rows whose facts have changed, and refresh the last-checked date.

When Kite finishes, your Notion workspace holds a research database your team can work from, and your conversation with Kite holds the record of what changed.