How Agency Owners Use AI Browsers for Prospect Research

This guide is for agency owners who run prospect research. It explains how an AI browser like Strawberry runs the workflow given the tools a agency owner actually uses every day, what the output should look like, and where the workflow fits in the agency owner's week.

Why this matters for agency owners

A agency owner spends time on this: win new clients, retain existing ones, and produce billable work across multiple accounts with a small team. The pain that makes prospect research feel slow is real: client reporting and pitch decks consume the senior team's time; juniors cannot produce them at quality. The reason an AI browser helps is that agency owners already use multiple surfaces (Slack, Google Workspace, a CRM, HubSpot or Notion for client tracking, Looker Studio or sheets for reporting) to do this work, and the browser is the only tool that can read across all of them and produce a finished output.

What success looks like

The goal of prospect research is to decide whether a prospect is worth a calendar slot and prepare a personalised first touch. For a agency owner, success metric is concrete: first reply rate above 8% and a meeting booked in under 14 days from first touch. A finished prospect research run should look like this: a draft client report, a pitch deck section, or a research brief that is 80 percent there and only needs minor polish.

Signals prospect research needs

The workflow needs these signals: role tenure and seniority on LinkedIn; recent funding rounds or M&A activity; headcount growth or layoffs in the last 6 months; tech stack and procurement signals. For a agency owner the practical question is which signals come from the tools already in the stack (Slack, Google Workspace, a CRM, HubSpot or Notion for client tracking, Looker Studio or sheets for reporting) versus what the browser has to fetch. Strawberry reads the in-stack tools through native integrations and uses the browser for the rest (LinkedIn, news, company websites, search). The agency owner stays in one surface.

Paste-ready Strawberry prompt

I'm a agency owner. Run prospect research for me using Slack, Google Workspace, a CRM and the browser, then save the draft.

What a finished prospect research output looks like

Concrete example, not a placeholder:

• 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

When this works, and when it does not

This workflow is right for agency owners when the work is repeatable and crosses multiple tools. It is wrong when any output the agency cannot defend to the client without a human review pass. In that case, the agency owner should keep doing the work manually until the pattern is clear enough to automate.

Three mistakes to avoid

• 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

Caveats

Strawberry holds back on sending email, updating CRM records, or changing shared systems until a human approves the action. Treat the agent as a fast first-draft author, not an autopilot.

When this is NOT a fit for agency owners

Skip this workflow when any output the agency cannot defend to the client without a human review pass. agency owners should keep doing the work manually until the pattern is clear enough to automate, otherwise you ship a generic prospect research brief that hurts trust.

Three mistakes to avoid

• 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.

Honest tradeoff

Strawberry will not invent missing signals. If the public web does not have headcount data or the CRM is empty, the draft will say "unknown" rather than guess. That is the right behaviour - the workflow is faster, not magic. The win for agency owners is that the first draft is 80% there and the remaining 20% is judgement, not data plumbing. A good run looks like: a draft client report, a pitch deck section, or a research brief that is 80 percent there and only needs minor polish.

What a finished output looks like

• 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