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Prospect Research in 30 Seconds: Using Claude Code to Build Account Dossiers

ยท 13 min read
MarketBetter Team
Content Team, marketbetter.ai
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๐ŸŸข Series Difficulty: BASIC (Part 2 of 10) โ€” No AI experience needed. This is your first hands-on use case.

Every SDR knows the drill. You get a name and a company. Maybe a job title if you're lucky. And then the clock starts: LinkedIn profile, company website, recent news, Crunchbase, BuiltWith, G2 reviews, LinkedIn posts... fifteen tabs later, you've spent 20 minutes and you're still not sure if this person is worth calling.

Now multiply that by 50 accounts a day.

This is the research bottleneck, and it's the single biggest destroyer of SDR productivity. Not because the research isn't valuable โ€” it absolutely is. Personalized outreach based on real intel dramatically outperforms generic messaging. The problem is that the time investment doesn't scale.

Until now.

In this post โ€” Part 2 of our 10-part Claude Code + MarketBetter series โ€” we'll show you exactly how to use Claude Code to build complete account dossiers in 30 seconds or less. And how to pair that with MarketBetter's visitor identification signals so you're never wasting research time on the wrong accounts.

If you haven't read Part 1 yet, start there โ€” it explains what Claude Code is, why SDRs should care, and the overall thesis behind this series. But if you're ready to get your hands dirty with your first real AI workflow, this is where it starts.

What You'll Needโ€‹

Before we dive in, make sure you have:

  • Claude Code installed and ready to use (your team's sales ops or RevOps lead can help with setup โ€” it takes about 5 minutes)
  • MarketBetter account with visitor identification enabled (book a demo if you don't have one yet)
  • A list of accounts you want to research (even 3-5 will do for your first try)

That's it. No coding skills. No special training. If you can type a sentence, you can use Claude Code.

The Old Way vs. The New Wayโ€‹

The Old Way: Manual Research (15-25 Minutes Per Account)โ€‹

Here's the typical SDR research workflow:

  1. LinkedIn Profile (3-5 min) โ€” Find the contact, read their bio, check recent posts, look at career history
  2. Company Website (3-5 min) โ€” About page, product pages, recent blog posts, press releases
  3. News & PR (2-3 min) โ€” Google the company name, check for recent funding, acquisitions, partnerships
  4. Tech Stack (2-3 min) โ€” BuiltWith or Wappalyzer to see what tools they use
  5. Hiring Signals (2-3 min) โ€” Check their careers page or LinkedIn jobs for relevant openings
  6. Social Presence (2-3 min) โ€” Twitter/X activity, any podcast appearances, speaking engagements
  7. Compile Notes (2-3 min) โ€” Write it all up in your CRM or a doc

Total: 15-25 minutes for a single account.

At 50 accounts per day (a typical SDR target), that's 12-20 hours of research. More hours than exist in a workday. So what actually happens? SDRs skip the research and send generic outreach. Response rates drop. Pipeline suffers. It's a vicious cycle.

The New Way: Claude Code + MarketBetter (30 Seconds Per Account)โ€‹

Here's the same workflow, reimagined:

  1. MarketBetter alerts you that Acme Corp visited your pricing page twice this morning
  2. You paste one prompt into Claude Code:

"Research Acme Corp (acmecorp.com). I need: company overview, recent news (last 90 days), their tech stack, current job openings (especially in sales/marketing), key decision makers with LinkedIn profiles, and any personalization hooks I can use for cold outreach. Format it as a one-page brief."

  1. Claude Code delivers a complete dossier in 20-30 seconds
  2. You scan the brief, pick your angle, and reach out โ€” with the same quality of personalization that used to take 20 minutes

That's not hypothetical. That's the actual workflow. Let's break down exactly how to do it.

Step-by-Step: Building Your First Account Dossierโ€‹

Step 1: Start With a Signal (Not a Cold List)โ€‹

The biggest mistake SDRs make with AI research tools is researching the wrong accounts. If you research 50 accounts but only 3 of them were actually in-market, you wasted time on 47 accounts.

This is where MarketBetter comes in. Instead of guessing who to research, you start with confirmed intent signals:

  • Website visitors โ€” Companies visiting your site, especially pricing or product pages
  • Return visitors โ€” Someone who came back after going dark (a huge signal โ€” see Part 9: Never Let a Lead Go Cold)
  • Person-level identification โ€” Not just "someone from Acme Corp" but "Sarah Chen, VP of Sales at Acme Corp" visited your site

When you know who's looking at your site right now, your research has immediate, actionable value. You're not building a dossier for "someday." You're building a dossier for a call you're about to make.

For more on how intent signals work, read our guide to intent data.

Step 2: Craft Your Research Promptโ€‹

The quality of your dossier depends on the quality of your prompt. Here's a template that works consistently:

The Basic Dossier Prompt:

"Research [Company Name] ([domain]). Give me:

  1. Company overview โ€” what they do, size, funding stage, HQ location
  2. Recent news from the last 90 days โ€” funding, product launches, partnerships, executive changes
  3. Their tech stack โ€” what tools/platforms they use, especially [your category]
  4. Current job openings โ€” focus on [relevant departments]
  5. Key decision makers โ€” [target titles like VP Sales, CRO, Head of Marketing] with LinkedIn profile URLs
  6. 3 personalization hooks I can use for cold outreach

Format this as a scannable one-page brief. Keep it concise."

The Deep-Dive Prompt (for high-value accounts):

"Deep research on [Company Name]. I sell [your product/solution] to [your ICP].

I need:

  1. Full company profile โ€” founding year, employee count, revenue range, funding history, key investors
  2. Their current go-to-market approach โ€” how do they sell? Do they have an SDR team? What does their outbound look like?
  3. Pain points they're likely facing based on their size, growth stage, and recent activity
  4. Competitive landscape โ€” who else are they likely evaluating?
  5. Recent content from their executives โ€” LinkedIn posts, blog articles, podcast appearances, conference talks
  6. Tech stack analysis โ€” current tools, potential gaps where [your solution] fits
  7. Champion mapping โ€” who would be the buyer, influencer, and end user for [your product]?
  8. 5 personalized outreach angles ranked by likely effectiveness

Be specific. Use real data. Flag anything you're uncertain about."

Step 3: Review and Refineโ€‹

Claude Code will return a structured brief. Here's what a typical output looks like:


ACCOUNT DOSSIER: Acme Corp

Company Overview

  • B2B SaaS, marketing automation platform
  • ~350 employees (LinkedIn), HQ in Austin, TX
  • Series C ($45M, led by Sequoia, June 2025)
  • Growing ~40% YoY based on job posting volume

Recent News (Last 90 Days)

  • Launched new AI features for email personalization (Jan 2026)
  • Named in G2's "Best Marketing Automation" for mid-market (Feb 2026)
  • VP of Engineering departed (LinkedIn activity suggests Dec 2025)

Tech Stack

  • Salesforce CRM, HubSpot Marketing, Outreach for sequences
  • No visitor identification tool detected
  • Using Clearbit for enrichment

Job Openings (Relevant)

  • 3 SDR roles (posted last 2 weeks) โ€” scaling outbound
  • 1 Demand Gen Manager โ€” suggests inbound isn't enough
  • 1 RevOps Analyst โ€” building out operations

Key Decision Makers

  • James Wilson, CRO (LinkedIn: linkedin.com/in/jwilson)
  • Maria Garcia, VP of Sales (LinkedIn: linkedin.com/in/mgarcia)
  • David Park, Head of Growth (LinkedIn: linkedin.com/in/dpark)

Personalization Hooks

  1. They're hiring 3 SDRs โ€” they're clearly investing in outbound. Your solution helps SDR teams perform at scale.
  2. The VP of Engineering departure may signal internal shifts. Tread carefully but it's a potential change catalyst.
  3. Their recent AI email features suggest they value automation โ€” they're already bought into the AI thesis.

Review this in 60 seconds. Highlight the hooks you want to use. Move to outreach.

Step 4: Connect the Signalsโ€‹

Here's where the magic happens. You're not just looking at Claude Code's research in isolation โ€” you're layering it with MarketBetter's behavioral data.

MarketBetter tells you: Maria Garcia from Acme Corp visited your pricing page twice yesterday and your case studies page this morning.

Claude Code tells you: Acme Corp is hiring 3 SDRs, just raised Series C, and their CRO recently posted about scaling outbound.

Your outreach writes itself: "Maria, I see Acme is building out the SDR team โ€” congrats on the growth. When companies hit your stage, the biggest question is usually 'how do we maintain personalization at scale?' That's exactly what we help with..."

That's not a cold email. That's a warm, relevant, perfectly-timed message. And it took you 2 minutes total.

Batch Research: The Power Moveโ€‹

Once you're comfortable with individual dossiers, level up to batch research. This is where Claude Code really shines.

The Batch Research Workflowโ€‹

  1. Export your MarketBetter daily signal list (the companies showing intent today)
  2. Feed Claude Code the entire list:

"I have a list of 15 companies that visited our website today. Research each one and give me a brief for each with: company size, what they do, one key recent development, and the best personalization angle. Rank them by likely fit for [your ICP]. Here's the list:

  1. Acme Corp (acmecorp.com)
  2. Beta Industries (betaindustries.io)
  3. Gamma Solutions (gammasolutions.com) ..."
  1. Claude Code returns 15 mini-briefs, ranked by fit
  2. You focus your morning on the top 5

Instead of spending your entire morning researching, you spend 5 minutes reviewing Claude Code's output and then the rest of your morning selling.

Advanced Prompt Patterns for SDRsโ€‹

Here are some specialized prompts for common research scenarios:

The "Pre-Meeting" Deep Diveโ€‹

"I have a meeting with [Name], [Title] at [Company] in 2 hours. Research them like my career depends on it. I need: their career history, recent LinkedIn activity, anything they've published or said publicly, mutual connections, their company's recent news, and 3 talking points that will make me sound like I've known their business for years."

(For a complete meeting prep workflow, see Part 8: Meeting Prep That Doesn't Suck.)

The "Competitor Customer" Researchโ€‹

"I need to research [Company] as a potential customer. They currently use [Competitor]. Research what they might be frustrated with based on [Competitor] reviews on G2 and Reddit. Find their most likely pain points and suggest an angle for approaching them about switching."

(More on competitive intelligence in Part 5.)

The "Trigger Event" Researchโ€‹

"I just saw that [Company] announced [trigger event โ€” new funding, executive hire, product launch]. Research everything about this event and how it creates an opportunity for us to reach out with [our solution]. Give me the angle and draft an email opening."

The "Reactivation" Researchโ€‹

"[Company] was a prospect 6 months ago but went cold. Research what's changed since then โ€” new leadership, new funding, new challenges, shifts in their tech stack. Help me find an angle to re-engage them."

Common Mistakes to Avoidโ€‹

1. Researching Without Intentโ€‹

Don't just research random accounts because you can. Start with a signal โ€” a website visit, a LinkedIn engagement, a trigger event. Research is only valuable when it leads to action.

2. Over-Researchingโ€‹

Claude Code can give you pages of information. You don't need pages. You need 3 things: who to contact, what to say, and why now. Everything else is noise.

3. Not Verifying Key Claimsโ€‹

Claude Code is incredibly capable, but it can occasionally get details wrong. If your outreach hinges on a specific fact โ€” "I saw you just raised Series B" โ€” verify it before you reference it. Nothing kills credibility faster than getting a basic fact wrong.

4. Copy-Pasting Without Personalizationโ€‹

Claude Code gives you raw material, not finished outreach. Always add your own voice, adjust for tone, and make it feel like something a real human would write. (More on this in Part 3: Writing Hyper-Personalized Cold Emails.)

Making It a Daily Habitโ€‹

The SDRs who get the most value from Claude Code don't use it sporadically. They build it into their daily routine:

Morning Sprint (15 minutes):

  1. Check MarketBetter for overnight website visitors and intent signals
  2. Feed the top 10-15 accounts into Claude Code for batch research
  3. Review the dossiers, pick your top 5, and plan your outreach

Before Every Call (2 minutes):

  1. Quick Claude Code research on the specific person you're about to call
  2. Scan for recent LinkedIn posts, company news, or mutual connections
  3. Walk into the call with context

End of Day (5 minutes):

  1. Research tomorrow's follow-up targets
  2. Use Claude Code to draft follow-up messages for today's conversations
  3. Queue them in MarketBetter for morning delivery

For the full daily routine, check out Part 10: The Complete AI SDR Playbook.

The ROI of AI-Powered Researchโ€‹

Let's put real numbers on this:

  • Time saved per account: ~18 minutes (from 20 minutes to 2 minutes)
  • Accounts researched per day: 50 (up from 10-15)
  • Hours reclaimed per day: ~3 hours (redirected to selling)
  • Expected impact on pipeline: 2-3x more conversations with researched, personalized outreach

That's not incremental improvement. That's a fundamentally different job.

Free Tool

Try our Tech Stack Detector โ€” instantly detect any company's tech stack from their website. No signup required.

Try This Todayโ€‹

Here's your action item:

  1. Pick 3 accounts that you're planning to reach out to this week
  2. Open Claude Code and use the Basic Dossier Prompt from above for each one
  3. Compare the output to what you'd have found doing manual research
  4. Time yourself โ€” how long did Claude Code take vs. how long you'd normally spend?

Most SDRs who try this have a reaction somewhere between "wait, that's it?" and "I've been doing this manually like a fool." Either way, you'll never go back.


This is Part 2 (๐ŸŸข Basic) of our 10-part series on Claude Code + MarketBetter for SDRs. Next up: Part 3: Writing Hyper-Personalized Cold Emails at Scale โ†’

Ready to pair AI research with real-time buyer intent signals? Book a MarketBetter demo to see visitor identification in action.

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