Strawberry vs Microsoft Copilot for Lead List Building

Microsoft Copilot and Strawberry both show up when teams shop for help with lead list building. They do not solve the same problem. Microsoft Copilot is an AI assistant; Strawberry is an AI browser that lives in your real browser tabs and connected apps. This page is the head-to-head on lead list building specifically - where each one wins, what the output actually looks like, and the price you pay either way.

The short answer

For lead list building, pick Strawberry when the work needs to read logged-in pages and act across multiple apps in your real browser. Pick Microsoft Copilot when you live entirely in Microsoft 365 and the value is inside Word/Excel/Outlook/Teams. If your workflow looks like "open three tabs, judge what matters, write something back into a CRM", Strawberry will close it faster. If it looks like "answer this clean question", Microsoft Copilot is the cheaper tool.

What lead list building actually requires

The job is to produce a clean, enriched, dedup'd list of N contacts who match ICP and have at least one buying signal. Success is measured as: bounce rate below 5%, dedup rate above 95%, and at least 30% of leads with a fresh signal. To do it well, the workflow needs these signals: ICP criteria (industry, size, geo, stack); title match including variants (Head of, VP, Director of); verified email pattern; phone number (when reachable from source). Most of those signals live behind logins or scattered across the open web - which is exactly where the tool choice starts to matter.

How Strawberry handles lead list building

Strawberry runs inside your real browser. It reads the tabs you have open, pulls context from your connected apps (CRM, email, sheets, Slack, Notion, calendar), researches missing signals via the open web, and synthesises a draft in the shape your team uses. A human reviews before any external write. Because the agent sees the same pages you do, you can ask follow-up questions referencing what's on screen and get answers grounded in that context.

Concrete workflow with Strawberry

1. Open the source page (Apollo search, conference attendee list, niche directory) in a tab.
2. Ask Strawberry to extract name, role, company, and LinkedIn URL into a sheet, paginating as needed.
3. Have it enrich with company size, HQ country, and funding stage so you can filter.
4. Apply your ICP filter inside the sheet and discard rows that do not match.
5. Push the filtered list into your sequencer or CRM with the source tagged for attribution.

Use this exact prompt in Strawberry to start the workflow:

I have [tab/app] open. Help me build a verified lead list for [name/company]. Read what's on screen plus any connected CRM and email context. Return: A CSV or sheet with one row per lead: name, title, company, email, LinkedIn URL, signal, source. Anchor every claim to a real signal from ICP criteria (industry, size, geo, stack) or title match including variants (Head of, VP, Director of). Do not invent facts. Stop before any external action - I'll review.

How Microsoft Copilot handles lead list building

Microsoft Copilot's strength is deeply embedded across Microsoft 365 (Word, Excel, Outlook, Teams) with org-wide data access. For lead list building, that pays off when the inputs are already clean and the output is text - drafting messages, summarising notes, answering questions about pasted material. Where it slows down is exactly what lead list building demands at scale: Copilot lives inside the Microsoft ecosystem. Teams using Microsoft Copilot for this end up copy-pasting screenshots, re-typing CRM fields, and switching context every few minutes.

Honest tradeoffs

Pick Strawberry when the work crosses Microsoft and non-Microsoft surfaces (web, third-party CRMs, social, AI tools).

Pick Microsoft Copilot when you live entirely in Microsoft 365 and the value is inside Word/Excel/Outlook/Teams.

Use them together when Microsoft Copilot owns the drafting step and Strawberry owns the browser-side gathering and CRM write-back. Many teams keep both in their stack.

What a real lead list building output looks like

Specific, not generic:

• Goal: 75 Head of Growth contacts at Series A-B SaaS in DACH
• Sources: a CRM-clean filter, a ZoomInfo/Apollo enriched pull, and a LinkedIn sweep with manual review
• Output: Google Sheet 'DACH-growth-2026-W23' with columns name, title, company, work email, LinkedIn URL, signal (hiring or funding), source notes

Strawberry produces this by reading the relevant tabs and apps, then drafting. Microsoft Copilot produces this only if the inputs are already pasted into the chat.

Pricing in context

Microsoft Copilot: $30/mo per user added on top of Microsoft 365. Strawberry: free tier, Intern $20/mo, Part-Time $100/mo, Full-Time $250/mo, with team plans available. The honest comparison is hours of work saved per seat per week against list price, not list price alone. Teams that lean on lead list building weekly usually hit payback in the first month on either tool.

Three mistakes to avoid in lead list building

These bite regardless of which tool you pick:

• Guessing email patterns and getting bounced
• Including duplicates because the source mixes work and personal emails
• Padding the list with leads who don't match ICP just to hit a count target

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.