LinkedIn outreach works best when it's personal, but personal outreach is slow. Finding the right people, reading their profiles, writing a note that isn't generic, and keeping track of who replied can take hours every week.
In this guide, we'll show you how to do personalized outbound at scale with AI, from building a prospect list to following up on replies. You'll describe each job in plain English, and the browser will do the clicking, reading, and typing for you.
What is LinkedIn outreach automation?
LinkedIn outreach automation means using software to handle the repetitive parts of prospecting on LinkedIn: searching for people, collecting their details, sending connection requests and messages, and tracking responses.
Most LinkedIn automation tools work from fixed templates. You set up a sequence of steps in advance, and the tool runs the same steps for every person on your list.
An AI browser works differently. It's a web browser with an AI agent built in, so it uses LinkedIn the way you do: in your own browser, logged in to your own account. Instead of building a sequence, you describe what you want in natural language, like "find 50 heads of marketing at Series A startups in New York and add them to a sheet," and the agent reads profiles, makes judgment calls, and moves between LinkedIn, company websites, and Google Sheets until the job is done.
What you'll need
- Polar, the AI browser we'll use in this guide. It's free on Mac and Windows.
- Your LinkedIn account. Open LinkedIn in Polar and log in, or import your logins from your current browser. Sales Navigator works too.
- A Google Sheet or your CRM to hold your list. Polar can create a new sheet for you, or add people straight to a CRM like HubSpot or Salesforce, the same way you would in your browser. The steps below use a sheet, but you can swap in your CRM anywhere.
Most steps below link to a ready-made template. Swap the details in brackets to fit your work.
Step 1: Decide who you want to reach
Good outreach starts with knowing exactly who you're writing to. Before you look for anyone, get specific about the people you want to reach: their job title, the size and type of company they work at, where they're based, and what might make them need you right now, like a recent funding round or a new hire.
If you're not sure yet, ask Polar to help you work it out:
Look at my website [link] and my best customers [names or links]. Suggest three types of people I should reach out to on LinkedIn. For each one, give me the job titles, company size, industry, location, and a sign that they might need us right now.
Pick the one that fits best, and use it for the rest of this guide.
Step 2: Build your prospect list
Now ask Polar to find those people on LinkedIn and put them in a list. You don't need to run the search yourself:
Use LinkedIn to find 30 [heads of marketing at Series A SaaS startups in New York]. For each person, get their name, title, company, location, and profile URL, and put them in a new Google Sheet with a Status column for outreach tracking.
Polar runs the search, reads each person's details, and writes the list to a new sheet.
You don't have to start from a LinkedIn search. You can also start with the companies you want to reach and let Polar find them, for example:
Find me 50 US-based startups that raised money in the last 60 days
From there, ask Polar to find the right people at each company on LinkedIn and add them to the sheet.
Step 3: Research and score each lead
A list of names isn't outreach yet. The next step is learning enough about each person to know whether they're a fit and what to say.
Use the lead scoring template:
Go through my lead sheet [sheet link] and add three columns: fit tier, interesting fact, and outreach angle. For each company, spend a minute on their website and LinkedIn page, then grade them A, B, or C against my ideal customer: [size, industry, signals]. The interesting fact must be specific and recent, with a link. The outreach angle is one sentence connecting that fact to [your product's value].
This is the step that's hardest to do with a fixed template. Polar reads each company's website and LinkedIn page, finds something specific, like a product launch, a new hire, or a recent post, and links to where it found it. If there's nothing worth mentioning, it marks the lead as "thin presence" instead of making something up.
Step 4: Write a personal note for each person
Now turn that research into a short note for each person. Ask Polar to draft the notes in your sheet so you can read them before anything is sent:
For every A and B lead in my sheet [sheet link], write a short connection note in a new column. Use the interesting fact and outreach angle from that row, keep it under 300 characters, and write it in a friendly, direct tone. Don't invent anything that isn't in the sheet or on their profile.
Read through the notes and edit any that don't sound like you. This is the best place to spend your own time: a few minutes reviewing notes is much faster than writing every one from scratch, and it keeps you in control of what goes out under your name.
Step 5: Send connection requests
Once your notes are ready, use the connection request template:
Here is my list of people to connect with: [sheet link]. The LinkedIn profile URL is in [column D] and the note for each person is in [column E]. For each row, check whether I'm already connected or have a pending request. If so, skip it. Otherwise, send a connection request with that row's note. Work in small batches and stop early if LinkedIn shows any warning. Mark each row sent, skipped, or could-not-send.
For each person, Polar opens their profile, checks whether you're already connected, and prepares the request with your note. It shows you each request and asks for your approval before sending, because a sent invite can't be taken back. As it goes, it updates the sheet so you always know who's been contacted.
To make this a daily habit, just say so:
Every day send 25 connection requests to leaders in my industry
Polar sets this up as a scheduled workflow. Each day it finds 25 new people on LinkedIn and adds them to a sheet for your review, and it asks for your approval before sending any requests.
Step 6: Turn it into a workflow
Once you've been through these steps, you don't need to repeat them by hand. Ask Polar to turn the whole process into a workflow:
Turn this into a workflow. Every weekday morning, find 10 new [heads of marketing at Series A SaaS startups in New York] on LinkedIn, research and score each one, draft a connection note, and add them to my sheet [sheet link] for review. Then check my LinkedIn messages for replies, update the sheet, and draft (don't send) a follow-up for anyone who's interested.
Polar saves it as a workflow and sets up when it runs. It can run on a schedule, like every weekday at 8am, or start when something happens, like when new rows are added to your sheet or a new email arrives. You can change the trigger any time by asking, for example: "Run this whenever I add a company to my target list sheet."
Each run does the finding, research, and drafting in the background, so new leads and follow-ups are waiting when you sit down to work. Polar still asks for your approval before it sends any connection requests or messages. If you only want the reply tracking, start from the reply tracker template.
How to keep your LinkedIn account safe
LinkedIn watches for activity that doesn't look human, and it limits how many invitations you can send each week. Automating outreach carelessly is the fastest way to get your account restricted. Here's how Polar is built to work carefully on LinkedIn:
- It paces itself. On larger jobs, Polar spaces out its searches and profile visits instead of moving as fast as it can, and it works through LinkedIn tasks one at a time.
- It stops when LinkedIn warns you. If LinkedIn shows a warning about unusual activity or restricts your account, Polar stops working on LinkedIn and continues with the data it has already collected.
- It checks before it sends. Before sending a connection request, Polar confirms the invite is going to the right person, and it treats the "Invitation sent" message as proof the request went through.
- It asks before anything you can't undo. Polar asks for your approval before sending a message or connection request, and you can watch any task live and take over at any time.
The best protection is still your own judgment. Keep your volume close to what you'd do by hand, make every message worth reading, and stop if people start ignoring or declining your requests.
AI browser vs. LinkedIn automation tools
Dedicated LinkedIn automation tools are good at one thing: running the same sequence of connection requests and messages for a long list of people. If that's all you need, they work.
An AI browser is a better fit when:
- Every message needs real research. Polar reads profiles, company websites, and recent posts, so each note can mention something specific instead of just a first name and company.
- The work spans more than LinkedIn. Prospecting usually means moving between LinkedIn, company websites, Google Sheets, your email, and your CRM. Polar works on any website, so the whole job can be one task.
- The task changes each time. You describe what you want in plain English instead of building a sequence, so it's easy to try a new audience or a new angle.
- You want to stay in control. Polar runs in your own browser, on your own account, and asks before it sends anything.
FAQ
Try it on LinkedIn
For more ready-to-use prompts for prospecting, recruiting, and growing your network, see Polar for LinkedIn.
Polar is free to download and use on Mac and Windows. If you run a lot of tasks, paid plans give you more usage.