Use LinkedIn with an AI Browser for Prospect Research

If you use LinkedIn and you regularly need to research a prospect, the bottleneck is usually the same: LinkedIn holds part of the context, but prospect research also needs signals that live outside it - on the public web, in LinkedIn, in news, in other connected apps. Strawberry is built to combine the LinkedIn context with the rest of the browser, and run the full workflow as a companion you can re-trigger every week.

This page describes specifically how Strawberry handles prospect research when LinkedIn is one of the inputs. It names the LinkedIn surfaces involved, the signals the workflow actually needs, an example prompt you can paste, and what a good output looks like.

The job a sales rep, founder, or account executive is trying to do

The goal of prospect research is to decide whether a prospect is worth a calendar slot and prepare a personalised first touch. The success metric is concrete: first reply rate above 8% and a meeting booked in under 14 days from first touch. That definition matters because it shapes what LinkedIn needs to contribute to the workflow.

What signals prospect research actually needs

For each signal below, here is whether LinkedIn can contribute directly or whether Strawberry has to find it via the browser:

• Role tenure and seniority on LinkedIn - LinkedIn stores or surfaces this directly. Strawberry reads it through the connected integration.
• Recent funding rounds or M&A activity - LinkedIn stores or surfaces this directly. Strawberry reads it through the connected integration.
• Headcount growth or layoffs in the last 6 months - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Tech stack and procurement signals - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Recent content the prospect has published or commented on - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Open job postings that reveal team priorities - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.

What Strawberry can do inside LinkedIn

Strawberry can scan profiles to extract role + tenure, watch company pages for funding/hiring signals, and prepare DM drafts; the browser is the only practical interface since LinkedIn has no real public API.

LinkedIn surfaces Strawberry uses for this workflow: profiles, companies, posts, search filters, Sales Nav (if licensed).

How Strawberry runs prospect research with LinkedIn

1. Strawberry opens the LinkedIn profiles that contains the relevant context.
2. The companion pulls related context from LinkedIn (companies, history, attached files) where it exists.
3. For the parts LinkedIn does not store, Strawberry uses the browser - web search, LinkedIn, news, the prospect's website.
4. Strawberry synthesises the output in the shape this workflow needs: A one-page brief.
5. A human reviews before any external action (send, update, post). Then the approved output is saved back to LinkedIn or your system of record.

Example Strawberry prompt

Paste this in a new Strawberry chat with LinkedIn connected. Adjust the specifics to your actual ICP, role, or topic.

Read this LinkedIn profiles and any linked context.
Then run a full prospect research workflow on it. Use the browser to fill any gaps not in LinkedIn.
Return the output in the shape we use for prospect research: A one-page brief: name, role, company, ICP fit (yes/no with reason), top 3 talking points, suggested first message, 1-2 source links.
Do not send anything externally. Save the draft to me to review.

What a good prospect research output looks like

Here is what a finished output for prospect research should look like in practice. The specifics will change for your use case, but the shape should look similar:

• Anna Lindqvist - VP Marketing, Voi Technology
• ICP fit: yes (Series D scooter co, EU expansion, 1500 employees)
• Talking point 1: hired 4 paid-acquisition managers in last 90 days - clear shift toward performance marketing
• Talking point 2: spoke at SuperVenture last month on scooter unit economics
• Talking point 3: company just announced Germany pull-out - retention focus is likely a priority
• Suggested first message: short, references the SuperVenture talk, asks one specific question, no calendar link

Why LinkedIn for this, and where to use a different tool

LinkedIn is strong for this workflow because Strawberry can scan profiles to extract role + tenure, watch company pages for funding/hiring signals, and prepare DM drafts; the browser is the only practical interface since LinkedIn has no real public API.

Where LinkedIn falls short LinkedIn rate-limits aggressive scraping; outbound message sending must be human-approved; Sales Navigator features require a paid license on the connected account.

Consider also a CRM for state and follow-up tracking.

Common mistakes when running prospect research

• Researching prospects who don't match ICP - the brief is wasted
• Generic talking points ("impressive growth") that don't reference any real signal
• Copying public bio text instead of synthesising fit

Connecting LinkedIn to Strawberry

LinkedIn runs through the user's browser session (cookies). No OAuth integration; agent uses tab automation.. Once connected, the companion can read the surfaces above without re-authenticating, and any write action still requires explicit human approval the first time the workflow runs.

Caveats

Do not let any AI agent send emails, update CRM records, or change shared systems without a clear approval step. Strawberry is strongest when the workflow combines browser context with connected-app context and a human review for sensitive actions.