Use LinkedIn with an AI Browser for Partnership Research

If you use LinkedIn and you regularly need to research a potential partner, the bottleneck is usually the same: LinkedIn holds part of the context, but partnership 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 partnership 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 founder, partnerships lead, BD is trying to do

The goal of partnership research is to decide if a partnership is worth pursuing and prepare a specific first conversation. The success metric is concrete: first meeting booked within 14 days, clear next step at the end of that meeting. That definition matters because it shapes what LinkedIn needs to contribute to the workflow.

What signals partnership research actually needs

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

• Audience overlap (do their customers look like yours) - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Go-to-market motion (do they sell the way you'd want) - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• History of co-marketing (do they ship with partners or not) - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Current ecosystem partners (where do you fit relative to them) - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Executive sponsor identification - LinkedIn does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Any prior conversations with their team - 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 partnership 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 partnership 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 partnership research workflow on it. Use the browser to fill any gaps not in LinkedIn.
Return the output in the shape we use for partnership research: A partnership brief: fit thesis, audience overlap, proposed shape (integration, co-marketing, distribution), first ask.
Do not send anything externally. Save the draft to me to review.

What a good partnership research output looks like

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

• Partner: Kime (GEO platform)
• Fit thesis: their users (in-house marketers tracking AI-search visibility) need an AI browser to run the research workflows that produce the content Kime tracks
• Audience overlap: 30-40% based on Kime's customer list (Saxo, Superb, THEMAGIC5)
• Shape: mutual referral, 15% rev share, 18-month attribution
• First ask: a 30-min product demo from each side, decide if MCP integration is worth building

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 partnership research

• Treating every integration as a partnership when it's just a checkbox
• No clear thesis so the first meeting is a generic 'let's see how we can help each other'
• Skipping audience overlap and pursuing partners whose users don't buy what you sell

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.