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The Complete Guide to B2B Intent Data: From Signals to Pipeline [2026]

ยท 18 min read
sunder
Founder, marketbetter.ai

B2B intent data signal types flowing into a sales pipeline

Your best prospects are researching solutions like yours right now. They're reading comparison articles, checking G2 reviews, attending webinars, and visiting your pricing page.

But they haven't filled out a form. They haven't booked a demo. As far as your CRM is concerned, they don't exist.

This is the reality of B2B buying in 2026: up to 70% of the buyer journey happens in the dark funnel โ€” the invisible research phase where buyers evaluate vendors without ever raising their hand. By the time they contact sales, they've already shortlisted 2-3 vendors. If you're not on that shortlist, you're not in the deal.

Intent data changes the equation. Instead of waiting for buyers to come to you, it reveals who's actively researching solutions in your category โ€” so you can engage them while they're still making decisions.

The B2B buyer intent data market is worth an estimated $4.5 billion in 2026, growing at a 15.9% CAGR. But market size doesn't mean market maturity. Most sales teams still get intent data wrong โ€” buying expensive signals they can't activate, drowning SDRs in noise instead of giving them focus.

This guide covers everything: what intent data actually is, the different types and where they come from, how to evaluate providers, implementation frameworks that work, and the mistakes that burn budgets.

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

ยท 13 min read
MarketBetter Team
Content Team, marketbetter.ai

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.

Building a Lead Scoring Model Without a Data Team

ยท 11 min read
MarketBetter Team
Content Team, marketbetter.ai

๐ŸŸก Series Difficulty: MEDIUM (Part 6 of 10) โ€” Uses research skills from Part 2 and connects to MarketBetter's signal data. The most analytical post so far.

Every SDR knows the frustration: you've got 200 leads in your queue, and they all look the same. Same priority level. Same generic tags. No clear signal about who to call first.

So you do what every SDR does โ€” you start at the top of the list and work your way down. Or you sort alphabetically. Or you go with gut instinct. None of these are strategies. They're survival mechanisms.

Meanwhile, the enterprise sales teams down the hall have sophisticated lead scoring models built by data teams, powered by Marketo or HubSpot, with algorithms that predict which leads are most likely to convert. You don't have that. You don't have a data team. You don't have a marketing ops person who can build predictive models. You have a CRM, a list of leads, and a quota.

Here's the good news: you can build a lead scoring model in 30 minutes using Claude Code. It won't be as sophisticated as a machine-learning-powered enterprise system. But it'll be 10x better than alphabetical sorting. And when you pair it with MarketBetter's daily playbook, you'll have a complete system for knowing exactly who to call first, every morning.

This is Part 6 of our Claude Code + MarketBetter series โ€” the last of the Medium-level posts. In the Basic posts (Parts 1-3), you learned to research and write. In Parts 4 and 5, you built multi-step workflows for LinkedIn and competitive intel. Now you're going to do something more analytical: use Claude Code to build a system that makes decisions for you. You'll define scoring rules, apply them to data, and create a repeatable process that gets smarter over time.

If that sounds complex, don't worry. The Claude Code prompts are just as straightforward as the ones you've been using. You're just asking slightly more structured questions.

Let's build your scoring model.

What Is Lead Scoring (and Why Do You Need It)?โ€‹

Lead scoring assigns a numerical value to each lead based on how likely they are to buy. Higher score = more likely to convert = call them first.

Simple concept. But most scoring models fail because they're either:

  • Too complex โ€” Built by data teams with 47 variables that nobody understands
  • Too simple โ€” "Enterprise = high priority" doesn't tell you anything useful
  • Too static โ€” Set once and never updated, even as your market changes
  • Disconnected from action โ€” Great model, but nobody uses it in their daily workflow

The model we're going to build avoids all of these traps. It uses three categories of signals, is easy to understand, and plugs directly into your MarketBetter daily playbook.

For a deeper dive on scoring best practices, check out our lead scoring best practices guide.

The Three Pillars of SDR Lead Scoringโ€‹

Your scoring model is built on three pillars:

Pillar 1: Firmographic Fit (Does this company match our ICP?)โ€‹

This is the "who are they?" question. It includes:

  • Company size (employee count or revenue)
  • Industry
  • Geography
  • Technology used
  • Funding stage

Pillar 2: Behavioral Signals (Are they actively interested?)โ€‹

This is the "what are they doing?" question:

  • Website visits (especially high-intent pages like pricing)
  • Email engagement (opens, clicks, replies)
  • Content downloads
  • Social media interactions
  • Event attendance

Pillar 3: Timing Signals (Is now the right moment?)โ€‹

This is the "when is the right time?" question:

  • Recent funding rounds
  • Leadership changes
  • Job postings in relevant departments
  • Competitor contract renewals
  • Seasonal buying patterns

Each pillar contributes to a total score. The leads with the highest combined score get your attention first.

Step-by-Step: Building Your Model with Claude Codeโ€‹

Step 1: Define Your Ideal Customer Profileโ€‹

Before you can score leads, you need to know what a great lead looks like. Ask Claude Code:

"Help me define my Ideal Customer Profile (ICP). I sell [your product] to [your market]. My best customers tend to be:

  • Company size: [range]
  • Industry: [industries]
  • Typical buyer title: [titles]
  • Common pain points: [pains]

Based on this, create a firmographic scoring rubric with a 0-30 point scale. Give me the exact criteria for each score level."

Claude Code returns something like:

Firmographic Scoring (0-30 points)

CriteriaPointsDetails
Company Size0-101-49 employees: 2pts, 50-200: 7pts, 201-500: 10pts, 500-1000: 8pts, 1000+: 5pts
Industry0-10SaaS/Tech: 10pts, Financial Services: 8pts, Healthcare: 6pts, Manufacturing: 3pts, Other: 1pt
Geography0-5US: 5pts, UK/Canada: 4pts, Western EU: 3pts, Other: 1pt
Funding Stage0-5Series A-C: 5pts, Seed: 3pts, Bootstrapped: 2pts, Public: 2pts

Notice how the scoring reflects YOUR specific ICP. A 200-person SaaS company in the US scores higher than a 5,000-person manufacturer in Asia โ€” because that's who buys from you.

Step 2: Build the Behavioral Scoring Componentโ€‹

Now add the engagement signals. This is where MarketBetter's data becomes critical:

"Now create a behavioral scoring rubric (0-40 points) based on these engagement signals I can track:

  • Website visits (from MarketBetter visitor identification)
  • Pages visited (pricing page, case studies, product pages)
  • Visit frequency (one-time vs. return visitor)
  • Email engagement (opens, clicks, replies)
  • LinkedIn engagement (profile views, connection accepts, post interactions)

Weight the signals by purchase intent. A pricing page visit is more valuable than a blog page visit."

Claude Code returns:

Behavioral Scoring (0-40 points)

SignalPointsDetails
Pricing page visit10Single strongest buying signal
Case study/testimonial page7Evaluating social proof
Product/feature pages5Active research phase
Blog/content visit2Awareness stage
Return visitor (2+ sessions)8Sustained interest
Multi-page session (3+ pages)5Deep engagement
Email opened (2+ times)3Interest but not action
Email link clicked5Active engagement
Email replied8Direct interest
LinkedIn connection accepted3Openness to conversation

Step 3: Build the Timing Scoring Componentโ€‹

Finally, add signals that indicate the timing is right:

"Create a timing/trigger scoring rubric (0-30 points) based on these signals:

  • Recent funding announcement
  • Executive leadership changes
  • Job postings in relevant departments
  • Company expansion/new office
  • Technology changes or migrations
  • Contract renewal season (if known)

Weight by urgency of the buying window."

Claude Code returns:

Timing Scoring (0-30 points)

SignalPointsDetails
New funding (last 60 days)8Budget available, growth mandate
New CRO/VP Sales (last 90 days)7New leaders bring new tools
Hiring SDRs/AEs (active postings)6Scaling sales = needs tools
Hiring demand gen/marketing5Building pipeline infrastructure
Technology migration announced6Open to new vendors
Competitor contract likely up for renewal5Evaluation window
Expansion/new market entry4Growing pains = new needs

Step 4: Score Your Existing Leadsโ€‹

Now apply the model. Export your lead list from your CRM and feed it to Claude Code:

"I have a list of 100 leads. Apply this scoring model to each one:

[paste your scoring rubrics]

For each lead, I have:

  • Company name, size, industry, geography
  • Website visit data from MarketBetter (pages visited, frequency)
  • Email engagement data (opens, clicks, replies)
  • Any known trigger events

Score each lead across all three pillars, calculate the total, and rank them from highest to lowest. Group them into tiers:

  • Hot (70-100): Call immediately
  • Warm (40-69): Prioritize this week
  • Cool (20-39): Nurture sequence
  • Cold (0-19): Low priority

Here's the data: [paste your lead list with available data]"

In 2-3 minutes, you have a fully scored, prioritized lead list. No data team required.

Using MarketBetter's Daily Playbook as the Execution Layerโ€‹

A scoring model is useless if it doesn't change your daily behavior. Here's how to connect your Claude Code scoring model to your MarketBetter workflow:

The Morning Ritual (10 minutes)โ€‹

  1. Check MarketBetter's daily playbook โ€” New website visitors, return visitors, engaged prospects
  2. Apply your scoring model โ€” New behavioral signals from overnight activity change scores
  3. Identify your Hot tier โ€” These are your first calls of the day
  4. Identify new entrants to Warm tier โ€” Prospects who were Cool but just visited your pricing page. They jumped tiers overnight.
  5. Execute โ€” Start with the highest-scored leads and work down

Signal-Triggered Score Updatesโ€‹

MarketBetter sends you real-time signals throughout the day. Each signal should update your mental scoring:

  • Prospect visited pricing page โ†’ +10 points. If they were Warm, they're now Hot. Call them.
  • Prospect opened your email 3 times โ†’ +5 points. They're interested. Send a follow-up.
  • Prospect visited your site from a new device โ†’ +3 points. They might be sharing your site with colleagues. Multi-stakeholder interest.
  • Cold lead returned to your site โ†’ Re-score them entirely. They might have jumped from Cold to Warm in one visit. (More on re-engagement in Part 9.)

Automated Scoring with MarketBetterโ€‹

MarketBetter's built-in engagement tracking does much of the behavioral scoring automatically. Your Claude Code model handles the firmographic and timing scoring that MarketBetter doesn't cover. Together, they give you a complete picture.

For more on how intent data drives this process, read our guide to what intent data is and how it drives growth.

Refining Your Model Over Timeโ€‹

Your first scoring model won't be perfect. That's fine. Here's how to improve it:

Monthly Review (15 minutes)โ€‹

"Here are my last month's results:

  • 15 leads scored Hot โ†’ 8 converted to meetings (53%)
  • 30 leads scored Warm โ†’ 6 converted to meetings (20%)
  • 45 leads scored Cool โ†’ 2 converted to meetings (4%)
  • 10 leads scored Cold โ†’ 0 converted to meetings (0%)

Also, 3 meetings came from leads scored Cool or Cold. Here's what those leads had in common: [details]

Based on this data, what adjustments should I make to my scoring model? Are any signals over- or under-weighted?"

Claude Code will analyze the conversion data and suggest specific adjustments. Maybe pricing page visits should be worth 15 points instead of 10. Maybe industry scoring needs recalibration. Make the adjustments and run the updated model.

The Feedback Loopโ€‹

Over 3-6 months, your scoring model gets increasingly accurate because you're refining it based on actual conversion data. This is essentially what data teams do with machine learning โ€” just simpler and driven by your domain expertise instead of algorithms.

Advanced: Multi-Persona Scoringโ€‹

If you sell to multiple buyer personas, you might need different scoring models for each:

"I sell to two different personas:

Persona 1: VP of Sales (cares about pipeline and team productivity) Persona 2: RevOps Leader (cares about data quality and tech stack efficiency)

Create separate behavioral scoring rubrics for each persona. A VP of Sales visiting a case study page is different from a RevOps leader visiting an integration page โ€” weight them differently."

This gives you nuanced prioritization. A RevOps leader on your integrations page might score higher than a VP of Sales on your blog โ€” even though the VP is the more senior title โ€” because the RevOps behavior signals active evaluation.

Common Scoring Mistakes to Avoidโ€‹

  1. Over-weighting title/seniority โ€” A Director who's actively researching is more valuable than a VP who isn't
  2. Ignoring negative signals โ€” Unsubscribes, bounced emails, and "not interested" replies should decrease scores
  3. Scoring once and forgetting โ€” Scores should be dynamic, updated with every new signal
  4. Too many tiers โ€” Hot/Warm/Cool/Cold is enough. Don't create 10 tiers that nobody can remember
  5. Ignoring the denominator โ€” If your Hot leads aren't converting at a higher rate than Warm leads, your model isn't working
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Here's your concrete action item:

  1. Open Claude Code and use the prompts from Steps 1-3 above to build your scoring rubrics
  2. Pick 20 leads from your current queue
  3. Score them manually using your new model (estimate where you can)
  4. Sort them by score and compare the order to how you would have prioritized them with gut instinct
  5. Work the list in score order for one week and track your results

Most SDRs find that their intuition was right about 60-70% of the time. A scoring model gets you to 80-90%. That 20-30% improvement in prioritization translates directly to more meetings with less effort.


This is Part 6 (๐ŸŸก Medium) of our 10-part series. You've completed the Medium tier! Next up: Part 7: CRM Cleanup in Minutes โ†’ โ€” your first Advanced-level post.

MarketBetter's daily playbook surfaces the behavioral signals that power your lead scores. Book a demo to see how it works.

7 Best Sumble Alternatives for B2B Sales Teams in 2026

ยท 7 min read
MarketBetter Team
Content Team, marketbetter.ai

Sumble has carved out an impressive niche in sales intelligence. Founded by Kaggle co-founders Anthony Goldbloom and Ben Hamner and backed by $38.5M from Coatue and Canaan Partners, it uses a knowledge graph of 2.6 million companies to surface technographic data โ€” which tools companies use, what projects they're launching, and who to contact.

But Sumble isn't for everyone. If you're reading this, you've probably hit one of these walls:

  • You need more than data โ€” Sumble surfaces intelligence but doesn't help you act on it. No dialer, no email automation, no outreach workflows.
  • You want first-party signals โ€” Sumble scrapes public data. You want to know who's visiting your website right now.
  • You need an all-in-one platform โ€” using Sumble + Outreach + Orum + a chatbot tool + your CRM is too many tabs.
  • Pricing is unclear โ€” Sumble's Pro and Enterprise tiers aren't publicly transparent, making it hard to budget.

Here are 7 alternatives worth evaluating, ranked by how well they solve the execution gap.

1. MarketBetter โ€” Best All-in-One Alternativeโ€‹

Best for: Teams that want visitor identification, dialer, email, AI chatbot, and a daily SDR playbook in one platform.

MarketBetter isn't just a Sumble alternative โ€” it solves a fundamentally different problem. While Sumble tells you about accounts, MarketBetter tells your reps exactly what to do about them.

What sets it apart from Sumble:

  • Website visitor identification โ€” know who's on your site right now (first-party data Sumble doesn't offer)
  • Smart Dialer โ€” built-in calling, no Orum or Nooks needed
  • Daily SDR Playbook โ€” every rep gets a prioritized daily task list: who to call first, who to email, who to follow up with
  • AI Chatbot โ€” engages every visitor automatically, 24/7
  • Email automation โ€” hyper-personalized sequences powered by AI
  • All-in-one โ€” replaces 4-5 separate tools

What Sumble does better: Deeper technographic intelligence โ€” Sumble's knowledge graph is more granular on specific tech stack data across departments.

Pricing: Usage-based, transparent. Book a demo for a custom quote.

G2 Rating: 4.97 / 5 โ€” Top Performer across 15 lead generation categories.

2. ZoomInfo โ€” Best for Contact Database Scaleโ€‹

Best for: Teams that need a massive B2B database alongside intent signals.

ZoomInfo combines one of the largest contact databases in B2B with website visitor identification (WebSights), intent data, and basic outreach tools. It's the incumbent in sales intelligence โ€” big, broad, and expensive.

What sets it apart from Sumble:

  • Larger contact database (250M+ profiles)
  • Built-in basic email sequences
  • Stronger CRM integrations
  • Established category leader with years of data

Where it falls short:

  • Expensive โ€” SalesOS starts at $14,995/year
  • No smart dialer or daily playbook
  • Data quality varies by region
  • Long contracts with difficult cancellation

Pricing: $14,995+/year for SalesOS. See our full ZoomInfo pricing breakdown.

3. 6sense โ€” Best for Enterprise ABMโ€‹

Best for: Large enterprises running account-based marketing programs with big budgets.

6sense layers Bombora intent data with AI-driven account scoring to predict which accounts are in-market. It's enterprise-grade, comprehensive, and complex.

What sets it apart from Sumble:

  • Predictive account scoring and buying stage detection
  • Bombora intent data integration
  • Deep ABM campaign orchestration
  • Display advertising capabilities

Where it falls short:

  • $25,000+/year starting price
  • Complex implementation (months, not days)
  • No built-in dialer
  • Built for marketing teams, not individual SDRs

Pricing: Custom enterprise. Typically $25,000โ€“$100,000+/year. See our 6sense pricing breakdown.

4. Apollo.io โ€” Best Budget-Friendly Optionโ€‹

Best for: Startups and small teams that need prospecting + outreach on a budget.

Apollo combines a 270M+ contact database with email sequencing and a basic dialer at a fraction of what ZoomInfo or 6sense charge. It's the value play in this category.

What sets it apart from Sumble:

  • Built-in email sequences and basic dialer
  • Much cheaper ($59/month for Basic)
  • Large contact database accessible from day one
  • Chrome extension for prospecting

Where it falls short:

  • Data quality is inconsistent (community-contributed)
  • Visitor identification is limited (company-level, add-on)
  • Dialer is basic compared to purpose-built solutions
  • No daily playbook or prioritized SDR workflows
  • Email deliverability can be hit-or-miss

Pricing: Free tier | Basic: $59/month | Professional: $99/month | Organization: $149/month. See our Apollo pricing breakdown.

5. Common Room โ€” Best for Signal Aggregationโ€‹

Best for: Teams that want to consolidate buying signals from community, social, and product usage data.

Common Room takes a similar philosophy to Sumble โ€” aggregate signals from across the web โ€” but focuses on different sources: Slack communities, Discord, GitHub, Twitter, and product usage data. It's especially popular with product-led growth companies.

What sets it apart from Sumble:

  • Aggregates community and social signals (not just technographic)
  • Strong GitHub and open-source tracking
  • Product usage signal integration
  • Better for PLG-oriented GTM motions

Where it falls short:

  • Starts at $1,000/month โ€” not cheap
  • No built-in dialer, email automation, or chatbot
  • Better for signal aggregation than direct SDR execution
  • Not designed for traditional outbound sales

Pricing: Starter: $1,000/month | Team: $2,500/month | Enterprise: custom. See our Common Room alternatives guide.

6. Demandbase โ€” Best for ABM + Advertisingโ€‹

Best for: Enterprise B2B teams that combine account intelligence with targeted display advertising.

Demandbase merges account intelligence with B2B advertising capabilities, letting you both identify in-market accounts and serve them targeted ads. It's Sumble-like intelligence plus a media buying layer.

What sets it apart from Sumble:

  • B2B display advertising built in
  • Strong intent data from Demandbase's own network
  • Account-based experience (ABX) orchestration
  • Longer track record in enterprise B2B

Where it falls short:

  • Enterprise pricing ($30,000+/year typical)
  • Complex platform with steep learning curve
  • No built-in dialer or daily SDR workflow
  • Heavy implementation process

Pricing: Custom enterprise pricing. Typically $30,000+/year. See our Demandbase comparison.

7. Clearbit (now part of HubSpot) โ€” Best for HubSpot-Native Teamsโ€‹

Best for: HubSpot customers who want native data enrichment and visitor identification.

Since being acquired by HubSpot, Clearbit's enrichment and identification capabilities are increasingly bundled into HubSpot's platform. If you're a HubSpot shop, this is the path of least friction.

What sets it apart from Sumble:

  • Native HubSpot integration (no middleware)
  • Real-time enrichment on form fills and page views
  • Established reputation for firmographic data
  • Bundled pricing with HubSpot subscriptions

Where it falls short:

  • Locked into HubSpot's ecosystem
  • No standalone product anymore
  • No dialer, playbook, or outreach automation
  • Enrichment quality varies by segment

Pricing: Bundled with HubSpot. Standalone reportedly starts at $3,600/year. See our Clearbit comparison.

Quick Comparison: Sumble Alternatives at a Glanceโ€‹

PlatformStarting PriceVisitor IDSmart DialerDaily PlaybookAI ChatbotEmail Automation
MarketBetterUsage-basedโœ…โœ…โœ…โœ…โœ…
ZoomInfo$14,995/yearโœ…โŒโŒโŒโœ…
6sense$25K+/yearโœ…โŒโŒโŒโœ… (limited)
Apollo.ioFree / $59/moโœ… (limited)โœ… (basic)โŒโŒโœ…
Common Room$1,000/moโœ… (signals)โŒโŒโŒโŒ
Demandbase$30K+/yearโœ…โŒโŒโŒโœ… (via ads)
Clearbit/HubSpot$3,600/yearโœ…โŒโŒโŒโœ… (via HubSpot)
Free Tool

Try our AI Lead Generator โ€” find verified LinkedIn leads for any company instantly. No signup required.

The Core Question: Data vs. Executionโ€‹

Every platform on this list gives you some form of sales intelligence. The question is: what happens after you get the data?

Sumble's knowledge graph is genuinely impressive โ€” 2.6M companies, deep technographic insights, 550% YoY revenue growth. But it's a data platform. Your SDRs still need Outreach for sequences, Orum for calls, a chatbot vendor for website engagement, and a spreadsheet to prioritize their day.

If you want intelligence and execution in one platform โ€” visitor identification, smart dialer, email automation, AI chatbot, and a daily SDR playbook โ€” see how MarketBetter compares.


Related reads:

MarketBetter vs Sumble: Complete Comparison for B2B Sales Teams (2026)

ยท 6 min read
MarketBetter Team
Content Team, marketbetter.ai

Sumble and MarketBetter both help B2B sales teams find and close deals โ€” but they approach the problem from fundamentally different angles.

Sumble, founded by Kaggle co-founders Anthony Goldbloom and Ben Hamner, builds a knowledge graph of 2.6 million companies to surface technographic data: which tools companies use, who's making decisions, and what projects are being launched. It's backed by $38.5M in funding from Coatue and Canaan Partners, with angel investors including Marc Benioff and Nat Friedman.

MarketBetter identifies who's visiting your website right now โ€” then gives your SDRs a prioritized daily playbook with built-in email, dialer, and AI chatbot to act on those signals immediately.

The core difference: Sumble tells you about accounts. MarketBetter tells your reps what to do next โ€” and gives them the tools to do it.

Where Sumble Excelsโ€‹

Let's be fair about what Sumble does well:

Deep Technographic Intelligenceโ€‹

Sumble's knowledge graph trawls the web, social media, job boards, company websites, and regulatory filings to build detailed profiles of what tools companies use across departments. If you need to know whether a target account uses Snowflake in their data engineering team or just deployed Vercel for their frontend โ€” Sumble surfaces that.

This is genuinely useful intelligence. Knowing a company's tech stack tells you whether your product fits, what you're replacing, and who to target within the org.

Enterprise-Grade Data Productsโ€‹

Sumble offers an API, Sumble Enrich (bulk data enrichment), and Sumble Signals (real-time alerts when companies adopt new tools or launch projects). For enterprises building custom GTM workflows, these are powerful building blocks.

Viral Growth Inside Organizationsโ€‹

Sumble grows fast inside companies โ€” reportedly going from 1 to 500 monthly active users in 6 months at some accounts. Their free web app lets anyone search, and insights spread through Slack channels. Brendan Short of The Signal newsletter called it "the most interesting sales tool I found last year."

Where MarketBetter Excelsโ€‹

First-Party Website Visitor Identificationโ€‹

This is the fundamental difference. Sumble aggregates public data from across the web. MarketBetter identifies who's visiting your website โ€” giving you first-party intent signals that are dramatically more actionable than scraped technographic data.

When someone from a target account visits your pricing page, that's a buying signal Sumble can't provide. MarketBetter catches it in real time.

The Execution Layerโ€‹

Sumble is intelligence. MarketBetter is intelligence plus action.

With Sumble, once you know a company is using a competitor's tool, you still need to:

  1. Export that data to your CRM
  2. Build a sequence in Outreach or SalesLoft
  3. Find the right contact in another tool
  4. Make calls through a separate dialer
  5. Hope your SDR prioritizes the right accounts

With MarketBetter, all of this happens in one platform:

  • Smart Dialer โ€” built-in, no Orum or Nooks subscription needed
  • Email automation โ€” hyper-personalized sequences powered by AI
  • AI Chatbot โ€” engages website visitors automatically, 24/7
  • Daily SDR Playbook โ€” every morning, your reps get a prioritized list: call this person first, email this account second, follow up with this lead third

Daily SDR Playbookโ€‹

This is where the gap is widest. Sumble gives data. MarketBetter gives your reps a daily action plan.

The SDR Playbook combines website visitor data, intent signals, and engagement history into one prioritized task list. No more "20 tabs and a spreadsheet" workflow. Your rep opens MarketBetter, sees their playbook, and starts executing.

Feature-by-Feature Comparisonโ€‹

FeatureMarketBetterSumble
Website visitor identificationโœ… First-party, real-timeโŒ Not available
Technographic dataโœ… Via intent signalsโœ… Deep knowledge graph (2.6M companies)
Smart dialerโœ… Built-inโŒ Not available
Email automationโœ… AI-personalized sequencesโŒ Not available
AI chatbotโœ… Real-time visitor engagementโŒ Not available
Daily SDR playbookโœ… Prioritized daily actionsโŒ Not available
API accessโœ…โœ…
Bulk data enrichmentโœ…โœ… (Sumble Enrich)
Real-time alertsโœ…โœ… (Sumble Signals)
Org chart mappingโœ… Via contact identificationโœ… Deep org intelligence
Free tierDemo availableโœ… Free web app
G2 rating4.97 / 5Not yet rated

Who Should Choose Sumble?โ€‹

Sumble is a strong fit if you:

  • Need deep technographic intelligence โ€” knowing exactly what tools a company uses across departments is Sumble's core strength
  • Already have an outreach stack โ€” if you're invested in Outreach, SalesLoft, and a standalone dialer, Sumble layers on top as a data source
  • Want an API-first approach โ€” Sumble's API and Enrich products are built for teams with custom GTM workflows
  • Sell to developers or technical buyers โ€” Sumble's data is especially strong for tech companies (Snowflake, Figma, Wiz, and Vercel are among their 19 enterprise customers)

Who Should Choose MarketBetter?โ€‹

MarketBetter is the better fit if you:

  • Want to know who's on your website right now โ€” first-party visitor identification is a fundamentally different (and more actionable) signal than scraped public data
  • Need an all-in-one platform โ€” if your SDRs are juggling visitor ID, dialer, email, and CRM in separate tabs, MarketBetter consolidates everything
  • Want prioritized daily actions โ€” the SDR Playbook turns signals into a ranked task list, not just a data feed
  • Care about real-time engagement โ€” the AI chatbot captures intent while visitors are still on your site
  • Want to reduce tool sprawl โ€” instead of Sumble + Outreach + Orum + a chatbot tool, MarketBetter replaces all of them

The Intelligence vs. Execution Gapโ€‹

This is ultimately the decision you're making:

Sumble is best-in-class at answering "what do we know about this account?" It builds a detailed map of a company's tech stack, projects, and contacts. But it's a data platform โ€” your reps still need separate tools to act on those insights.

MarketBetter answers a different question: "what should my rep do right now?" It combines first-party website intent with built-in email, dialer, and an AI chatbot to create a complete execution loop.

For most B2B sales teams โ€” especially those with 5-50 SDRs who are drowning in tools โ€” the execution layer is what moves the needle.

Free Tool

Try our AI Lead Generator โ€” find verified LinkedIn leads for any company instantly. No signup required.

Try It Yourselfโ€‹

See how MarketBetter's all-in-one approach compares to a data-only platform. Book a demo and we'll show you how the Daily SDR Playbook turns website visitors into pipeline.


Related reads:

Sumble Pricing in 2026: Free Tier, Pro, Enterprise โ€” Is It Worth It?

ยท 7 min read
MarketBetter Team
Content Team, marketbetter.ai

Sumble has generated significant buzz in the sales intelligence space โ€” 550% year-over-year revenue growth, $38.5M in funding from Coatue and Canaan Partners, and angel investors like Marc Benioff and Nat Friedman. With 19 enterprise customers including Snowflake, Figma, Wiz, Vercel, and Elastic, it's clearly solving a real problem.

But what does Sumble actually cost? And more importantly: when you add up everything you need to go from "intelligence" to "closed deal," does the math work?

Here's the full breakdown.

Sumble's Pricing Tiersโ€‹

Sumble offers three pricing levels:

Free Tier ($0/month)โ€‹

Sumble's free web app lets anyone search their knowledge graph of 2.6 million companies. You can look up a company and see:

  • What tools and technologies they use
  • Department-level tech stack data
  • Key contacts and org chart information
  • Recent projects and initiatives

What's limited:

  • Search volume is capped
  • No API access
  • No bulk enrichment (Sumble Enrich)
  • No real-time alerts (Sumble Signals)
  • No data exports at scale

The free tier is genuinely useful for ad-hoc research. If you're a sales rep who needs to prep for a specific call, searching Sumble's free app can surface useful technographic context. But it's a research tool, not a sales workflow.

Pro Subscription (Pricing not publicly listed)โ€‹

Sumble's Pro tier unlocks higher search volumes and additional features. About 30% of Sumble's users convert to Pro โ€” a notably high conversion rate that suggests the free tier creates real "aha moments."

What Pro likely includes:

  • Higher or unlimited searches
  • Data export capabilities
  • Enhanced filtering and saved searches
  • Priority data freshness
  • Possibly limited API access

What we don't know:

  • Exact monthly/annual pricing
  • Whether it's per-seat or per-team
  • Usage caps or overage fees
  • Contract length requirements

The lack of transparent pricing is a yellow flag. When a company doesn't publish prices, it usually means one of two things: they're still experimenting with pricing, or the answer is "more than you'd expect."

Enterprise (Custom pricing)โ€‹

Sumble's enterprise tier includes their full product suite:

Sumble Enrich โ€” Bulk data enrichment via API. Upload a list of companies and get back technographic profiles, tech stack data, and contact information at scale.

Sumble Signals โ€” Real-time alerts when target accounts adopt new tools, launch projects, post relevant job listings, or show other buying signals.

Custom API access โ€” For teams building Sumble's intelligence into custom GTM workflows, CRM enrichment pipelines, or internal tools.

Enterprise pricing is fully custom โ€” based on data volume, number of companies monitored, API call volume, and seats.

The Hidden Cost: Everything Sumble Doesn't Doโ€‹

Here's where the pricing conversation gets real. Sumble is a data platform. It tells you what companies use, who works there, and what they're building. That's valuable intelligence.

But intelligence alone doesn't close deals. Here's what you'll need alongside Sumble:

Outreach or SalesLoft โ€” $100-150/month per seatโ€‹

Sumble doesn't send emails. It doesn't build sequences. It doesn't automate follow-ups. You'll need a dedicated sales engagement platform to turn Sumble's insights into actual outreach.

Dialer โ€” $150-300/month per seatโ€‹

Sumble doesn't make phone calls. If your SDRs pick up the phone (and they should โ€” phone is still the highest-converting outbound channel), you'll need Orum, Nooks, ConnectAndSell, or another dialer.

Website Visitor Identification โ€” $200-700/monthโ€‹

This is the big gap. Sumble trawls public data โ€” job boards, company websites, social media, regulatory filings. What it doesn't do is tell you who's visiting your website right now. For first-party intent signals, you'll need a separate visitor identification tool like Warmly, RB2B, or Clearbit.

Chatbot โ€” $100-500/monthโ€‹

Sumble doesn't engage website visitors. If you want real-time conversations with prospects who are actively browsing your site, that's another tool and another line item.

Total Stack Cost with Sumbleโ€‹

Let's estimate the full cost of building a sales execution stack around Sumble:

ToolMonthly Cost (per seat)
Sumble Pro~$100-200/month (estimated)
Outreach / SalesLoft$100-150/month
Dialer (Orum, Nooks)$150-300/month
Visitor ID (Warmly, RB2B)$200-700/month (shared)
Chatbot$100-500/month (shared)
Total per SDR$550-1,150+/month

For a team of 10 SDRs, you're looking at $5,500-$11,500/month in tool costs โ€” and that's before CRM, data enrichment, and other infrastructure.

The Alternative: All-in-One Pricingโ€‹

What if you didn't need five tools?

MarketBetter bundles visitor identification, smart dialer, email automation, AI chatbot, and the Daily SDR Playbook into one platform. Instead of managing five vendors, five contracts, and five integration points, your SDRs get everything in one tab.

CapabilitySumble + StackMarketBetter
Technographic intelligenceโœ… Sumbleโœ… Via intent signals
Website visitor identificationโŒ Need separate toolโœ… Built-in
Smart dialerโŒ Need Orum/Nooksโœ… Built-in
Email automationโŒ Need Outreach/SalesLoftโœ… Built-in
AI chatbotโŒ Need separate toolโœ… Built-in
Daily SDR playbookโŒ Not available anywhereโœ… Built-in
Number of vendors5+1
Number of logins5+1
Integration complexityHighNone
Pricing$550-1,150+/seat/monthUsage-based, transparent

When Sumble Is Worth the Investmentโ€‹

Sumble's pricing makes sense if:

  • You already have a mature outreach stack โ€” Outreach, Orum, and a CRM workflow that works. Sumble adds an intelligence layer on top.
  • You sell into technical markets โ€” Sumble's technographic data is especially deep for tech companies. If knowing your prospect uses Snowflake's data sharing vs. Databricks Lakehouse matters to your pitch, Sumble delivers.
  • You have a data engineering team โ€” Sumble's API and Enrich products are powerful for teams building custom GTM pipelines. If your RevOps team can ingest Sumble data into internal workflows, the API is valuable.
  • Volume is your game โ€” Sumble Enrich processes large datasets quickly. If you're enriching hundreds of thousands of accounts, the bulk pricing likely makes sense at enterprise scale.

When Sumble Isn't Worth Itโ€‹

Reconsider Sumble if:

  • Your SDRs are drowning in tools โ€” adding another data source without an execution layer makes the problem worse, not better
  • You need first-party website intent โ€” Sumble doesn't tell you who's on your website right now. That's arguably the strongest buying signal in B2B.
  • You want one platform โ€” if reducing tool count is a goal, Sumble moves you in the wrong direction
  • Transparent pricing matters โ€” unpublished pricing means unpredictable budgets
  • You're a team of 5-20 SDRs โ€” at this size, the stack cost of Sumble + everything else adds up fast
Free Tool

Try our AI Lead Generator โ€” find verified LinkedIn leads for any company instantly. No signup required.

The Bottom Line on Sumble Pricingโ€‹

Sumble's free tier is genuinely useful for research. Their knowledge graph is impressive, and 550% YoY revenue growth suggests real value.

But Sumble is a data platform, not a sales execution platform. The real cost isn't what you pay Sumble โ€” it's everything you need alongside it to go from "we know their tech stack" to "we booked a meeting."

If you want the intelligence and the execution in one platform โ€” with visitor identification, smart dialer, email automation, AI chatbot, and a daily SDR playbook โ€” book a demo with MarketBetter and compare the total cost of ownership.


Related reads:

Sumble vs MarketBetter: Which Sales Intelligence Platform Wins in 2026?

ยท 8 min read
MarketBetter Team
Content Team, marketbetter.ai

Two different philosophies. One goal: help B2B sales teams close more deals.

Sumble starts with the question: "What do we know about this account?" It builds a knowledge graph of 2.6 million companies, scraping the web, social media, job boards, regulatory filings, and company websites to surface technographic data โ€” which tools companies use, in which departments, and who to talk to.

MarketBetter starts with a different question: "What should my rep do right now?" It identifies who's visiting your website, combines that with intent signals, and turns everything into a prioritized daily task list โ€” with built-in email, dialer, and AI chatbot to execute immediately.

Both are valid approaches. The right choice depends on where your team's bottleneck is: intelligence or execution.

The Two Approaches to Sales Intelligenceโ€‹

Sumble: Knowledge Graph Intelligenceโ€‹

Sumble was built by Anthony Goldbloom and Ben Hamner โ€” the co-founders of Kaggle (the data science competition platform Google acquired). Their data-first DNA shows.

Sumble's knowledge graph ingests data from:

  • Company websites and tech documentation
  • Job postings (revealing tech stack adoption)
  • Social media and LinkedIn profiles
  • Regulatory filings and business registrations
  • App marketplaces and developer communities

The output: a detailed, company-level intelligence profile showing what tools a company uses across engineering, marketing, sales, finance, and other departments. Plus org charts, key contacts, and signals about new projects or technology changes.

The strength: Depth of intelligence. If you need to know that Acme Corp just switched from Segment to RudderStack in their data engineering team, Sumble surfaces that.

The limitation: Sumble stops at intelligence. It tells you about the account. It doesn't tell your rep what to do next, and it doesn't provide the tools to do it.

MarketBetter: Signal-to-Action Platformโ€‹

MarketBetter starts with a different data source: your own website. Website visitor identification reveals which companies and contacts are actively researching your solution โ€” right now.

This is first-party intent data, which is fundamentally more actionable than scraped public data. Someone visiting your pricing page at 2 PM is a stronger signal than a job posting from three weeks ago.

But identification is just the start. MarketBetter wraps that intelligence in an execution layer:

  • Daily SDR Playbook โ€” a prioritized list of exactly what each rep should do today
  • Smart Dialer โ€” call directly from the platform, no separate tool
  • Email Automation โ€” AI-personalized sequences that launch automatically
  • AI Chatbot โ€” engages visitors in real-time while they're still on your site

The strength: End-to-end workflow from signal to action.

The limitation: MarketBetter's intelligence is anchored to your website visitors and known contacts. For broad market mapping of accounts you've never interacted with, Sumble's knowledge graph casts a wider net.

Head-to-Head: What Each Does Betterโ€‹

Where Sumble Winsโ€‹

Technographic depth. Sumble's knowledge graph goes deeper than most platforms on tech stack data. Knowing that a prospect uses Snowflake vs. Databricks, or HubSpot vs. Salesforce, at the department level is genuinely valuable for personalized outreach.

Broad market discovery. Sumble covers 2.6 million companies. If you're building a target account list from scratch โ€” especially in technical markets โ€” Sumble's research capabilities are strong.

API and data products. Sumble Enrich (bulk enrichment) and Sumble Signals (real-time alerts) are built for teams that want to pipe intelligence into their own systems. If you have a RevOps team building custom workflows, these are serious tools.

Viral adoption. Sumble's free web app spreads organically through Slack channels โ€” reportedly going from 1 to 500 MAUs in some organizations within 6 months. Getting buy-in is easy because reps can start using it immediately.

Where MarketBetter Winsโ€‹

First-party intent signals. Sumble scrapes public data from across the web. MarketBetter tells you who's on your website right now. A prospect browsing your case studies page is a fundamentally stronger buying signal than a job posting that mentions your category.

All-in-one execution. This is the decisive difference for most teams. MarketBetter replaces 4-5 separate tools:

Without MarketBetterWith MarketBetter
Sumble for intelligenceโœ… Built-in intent signals
Outreach for email sequencesโœ… Built-in email automation
Orum/Nooks for callingโœ… Built-in smart dialer
Drift/Intercom for chatโœ… Built-in AI chatbot
Spreadsheet for prioritizationโœ… Built-in daily SDR playbook

Daily SDR Playbook. No other platform โ€” Sumble included โ€” gives reps a prioritized daily action list. Each morning, your SDR opens MarketBetter and sees: call this person first, email this account second, follow up with this lead third. No interpretation needed. No "20 tabs" workflow.

Real-time engagement. MarketBetter's AI chatbot captures intent while prospects are actively on your site. By the time Sumble surfaces a signal from a job posting or tech adoption, that moment may have passed.

Proven user satisfaction. MarketBetter holds a 4.97/5 rating on G2, ranked as a Top Performer across 15 lead generation categories. That kind of rating at scale indicates consistently strong user experience.

The Workflow Comparisonโ€‹

Here's how a typical outbound motion looks on each platform:

Sumble Workflowโ€‹

  1. Search Sumble's knowledge graph for target accounts
  2. Identify companies using competitor tools or launching relevant projects
  3. Export contacts and technographic data
  4. Import into your CRM
  5. Build sequences in Outreach or SalesLoft
  6. Make calls through a separate dialer
  7. Hope your chatbot catches any inbound visitors
  8. Manually prioritize tomorrow's tasks

Time to first outreach: Hours (best case). Days if your CRM sync is slow. Tools involved: 4-6

MarketBetter Workflowโ€‹

  1. Open the Daily SDR Playbook
  2. See prioritized actions based on yesterday's website visitors, engagement signals, and pipeline data
  3. Call the first prospect using the built-in dialer
  4. Send the AI-drafted follow-up email
  5. Move to the next task on the list
  6. AI chatbot handles visitors while you're on calls

Time to first outreach: Minutes. Tools involved: 1

Pricing: The Real Comparisonโ€‹

Sumble's pricing isn't fully transparent, but here's the realistic comparison:

Sumble + required tools:

  • Sumble Pro: ~$100-200/month (estimated)
  • Sales engagement (Outreach/SalesLoft): $100-150/seat/month
  • Dialer (Orum/Nooks): $150-300/seat/month
  • Visitor ID tool: $200-700/month (team)
  • Chatbot: $100-500/month (team)
  • Total: $650-1,850/seat/month

MarketBetter:

  • Usage-based pricing that includes all five capabilities
  • One vendor, one contract, one integration point
  • Book a demo for a custom quote

Even if Sumble's standalone price is modest, the total cost of the stack you need alongside it typically exceeds what an all-in-one platform costs. See our full Sumble pricing analysis.

Who Should Choose Sumble?โ€‹

โœ… You have a mature outreach stack (Outreach + dialer) and just need better intelligence โœ… You sell into technical markets where tech stack data directly impacts your pitch โœ… You have a data/RevOps team that can build custom workflows around Sumble's API โœ… You want a free research tool that reps can start using immediately โœ… Broad market mapping matters more than acting on today's intent signals

Who Should Choose MarketBetter?โ€‹

โœ… You want first-party website intent data โ€” the strongest buying signal in B2B โœ… Your SDRs are drowning in tools and need fewer tabs, not more โœ… You want a daily prioritized action list, not just a data feed โœ… You need built-in dialer, email automation, and AI chatbot โœ… Reducing tool sprawl and total cost of ownership is a priority โœ… You want one platform your reps actually use every morning

Free Tool

Try our AI Lead Generator โ€” find verified LinkedIn leads for any company instantly. No signup required.

The Verdictโ€‹

Sumble is a strong data platform. Its knowledge graph is impressive, its backing is serious (Coatue, Canaan Partners, Marc Benioff), and its 550% YoY growth is real.

But for most B2B sales teams, the bottleneck isn't intelligence โ€” it's execution. Your reps don't need another tab of data. They need to know what to do next and the tools to do it.

If your sales motion is "research โ†’ act," here's the question: do you want to build that workflow across 5 tools, or get it in one?

Book a MarketBetter demo and see the Daily SDR Playbook in action.


Related reads:

Signal-Based Selling: The Complete Guide to Signal-Based Market (SBM) for Sales Teams

ยท 18 min read
sunder
Founder, marketbetter.ai

Your SDRs have a list of 30,000 accounts. They're calling, emailing, and LinkedIn-ing their way through it โ€” one cold outreach at a time, praying that someone picks up.

Here's the math nobody talks about: at 80 activities per day, it takes a single rep 375 business days to touch every account once. That's 18 months. And by the time they circle back to account #1, whatever signal triggered the initial outreach is long dead.

This is the fundamental problem with traditional outbound. You're treating every account the same. The company that visited your pricing page three times this week gets the same generic sequence as the company that hasn't thought about your category in two years.

Signal-based selling fixes this. Instead of working a static list, you work a dynamic, living market โ€” the accounts showing real buying behavior right now. We call this your Signal-Based Market (SBM), and it changes everything about how modern sales teams operate.

What Is Signal-Based Selling?โ€‹

Signal-based selling is a GTM strategy where every sales action โ€” who to call, what to say, when to reach out โ€” is driven by real-time buying signals rather than static lists or gut instinct.

Instead of asking "Who's on my list today?", signal-based sellers ask: "Who's showing buying behavior today?"

Those signals include:

  • First-party engagement: Website visits, pricing page views, content downloads, demo page visits
  • Behavioral patterns: Repeat visits, increasing session depth, multi-stakeholder browsing
  • Champion movements: Key contacts changing jobs to new companies (they already know your product)
  • Firmographic changes: Funding rounds, hiring patterns, tech stack changes
  • Conversation intelligence: What prospects say on calls โ€” pain points, timeline, budget mentions

The shift is subtle but profound. Traditional selling is push-based โ€” you push your message to a list and hope for the best. Signal-based selling is pull-based โ€” you let buyer behavior pull you toward the accounts most likely to convert.

The best salespeople have always done this instinctively. Signal-based selling just makes it systematic, scalable, and available to every rep on the team โ€” not just the top 10%.

Understanding the Signal-Based Market (SBM)โ€‹

The Signal-Based Market is the core concept that makes this work. Think of it as a funnel โ€” but instead of a marketing funnel, it's a focus funnel that tells your sales team exactly where to spend their time.

The TAM โ†’ ICP โ†’ SBM Funnelโ€‹

Here's how a Signal-Based Market narrows the aperture from "everyone" to "right now":

StageWhat It RepresentsExample SizeHow You Define It
TAM (Total Addressable Market)Every company that could buy your product~150,000 accountsIndustry, company size, geography
ICP (Ideal Customer Profile)Companies that should buy your product~30,000 accountsFirmographic fit, technographic match, budget indicators
SBM (Signal-Based Market)Companies showing buying behavior today~100-150 accountsReal-time engagement + readiness signals overlaid on ICP

Read that last row again. From 150,000 accounts to ~100 that matter today. That's not a marginal improvement โ€” that's a 1,500x increase in focus.

Your TAM is everyone. Your ICP narrows it by fit. Your SBM narrows it by timing. And timing is everything in sales.

The Three-Signal Venn Diagramโ€‹

Your Signal-Based Market lives at the intersection of three signal categories:

๐ŸŽฏ Circle 1: ICP / Firmographic Fit Does this account match your ideal customer profile? Right industry, right size, right tech stack, right budget range? This is the foundational filter โ€” if they don't fit, no amount of intent signal matters.

๐Ÿ“Š Circle 2: Engagement Score Is this account actively engaging with your brand? Visiting your website, reading your content, clicking your emails, attending your webinars? Engagement signals tell you they know you exist and are actively researching.

โšก Circle 3: Readiness Score Are they showing signals that suggest they're ready to buy soon? Pricing page visits, competitor comparison research, multi-stakeholder engagement, expansion hiring, budget cycle timing? Readiness signals separate browsers from buyers.

The center of this Venn diagram โ€” where all three circles overlap โ€” is your Signal-Based Market. These are accounts that fit your ICP, are actively engaging with your brand, AND are showing readiness to buy. This is where your SDRs should spend 80%+ of their time.

An account that fits your ICP but isn't engaging? Nurture them. An account that's engaging but doesn't fit? Let marketing handle it. An account that's ready but doesn't fit? Pass.

But an account that fits, is engaging, AND is ready? That's a phone call. Today. Right now.

Why Traditional Prospecting Is Brokenโ€‹

Let's be honest about why most SDR teams struggle. It's not a people problem โ€” it's a system problem.

The Spray-and-Pray Realityโ€‹

The average SDR workflow looks like this:

  1. Get assigned a territory of 5,000-30,000 accounts
  2. Build sequences in a sales engagement platform
  3. Blast those sequences to as many contacts as possible
  4. Hope that sheer volume produces enough responses
  5. Cherry-pick the replies and book meetings
  6. Repeat until quota or burnout (usually burnout)

The conversion math is brutal: 1-2% reply rates on cold outbound means you need 5,000 emails to generate 50-100 replies, which yield maybe 10-15 meetings, which close 2-3 deals.

And here's the kicker โ€” those 2-3 deals would have likely come in anyway, because those prospects were already in a buying cycle. You didn't create demand. You just happened to catch them at the right time through brute force.

The Real Cost of Unfocused Outboundโ€‹

The hidden costs go beyond low conversion rates:

  • Rep burnout: SDRs churn at 35-40% annually. The #1 reason? Feeling like they're spinning their wheels
  • Brand damage: Every bad-fit email erodes your brand reputation. Recipients who aren't a fit don't just ignore you โ€” they remember you negatively
  • Opportunity cost: Every minute spent on a cold account is a minute NOT spent on a warm one
  • Data decay: By the time you circle back through 30K accounts, the data is stale

Signal-based selling doesn't just improve efficiency โ€” it fundamentally changes the experience of being an SDR. When reps know their outreach is going to people who are actually in-market, everything improves: response rates, conversation quality, confidence, and ultimately, retention.

The Signal Hierarchy: Not All Signals Are Created Equalโ€‹

This is where most intent data strategies go wrong. Teams buy a third-party intent data feed, light up a dashboard of "hot accounts," and expect magic. It doesn't work because they're using commoditized signals.

Commoditized vs. Proprietary Signalsโ€‹

Think of signals like stock market alpha. Public information is priced in. Everyone has access to the same job posting data, the same LinkedIn activity feeds, the same Bombora surge topics. When every competitor sees the same "intent signal," nobody has an advantage.

Signal TypeExamplesCompetitive Advantage
Commoditized (Public)Job postings, LinkedIn posts, press releases, G2 reviewsLow โ€” everyone sees these
Semi-ProprietaryThird-party intent data (Bombora, etc.), technographic changesMedium โ€” requires a subscription, but many competitors have it
Proprietary (Your Alpha)YOUR website visitors, YOUR content engagement, YOUR pricing page views, YOUR call recordingsVery High โ€” only YOU have this data
Compound SignalsProprietary signals layered with firmographic fit + timing triggersMaximum โ€” this is your Signal-Based Market

The real alpha in signal-based selling is in proprietary, compound signals. A company visiting YOUR pricing page three times in a week while also matching your ICP and having a champion who previously used your product at another company โ€” that's a signal stack that no competitor can replicate because it's built from YOUR data.

First-Party Signals Are Your Competitive Moatโ€‹

This is why website visitor identification is so critical to signal-based selling. Your website traffic is the highest-quality intent signal available because:

  1. It's exclusive to you: Only you know who's visiting YOUR site
  2. It's high-intent by definition: They found you, not the other way around
  3. It's timely: You see the visit when it happens, not weeks later in a third-party report
  4. It compounds: A single visit is interesting. Three visits with a pricing page view is a buying signal. Five visits with multiple stakeholders from the same company is a red alert

MarketBetter customers typically see 35,000+ website visits tracked monthly, with 5,000+ companies identified โ€” and these aren't random visitors. These are companies actively researching your solution.

Building Your Signal-Based Market: A Practical Frameworkโ€‹

Enough theory. Here's how to actually build and operationalize a Signal-Based Market for your sales team.

Step 1: Define Your ICP with Precisionโ€‹

Your ICP is the foundation of your SBM. Get this wrong and you'll be chasing signals from accounts that will never close.

Go beyond basic firmographics. A modern ICP includes:

  • Firmographic fit: Industry, employee count, revenue range, geography
  • Technographic fit: Current tech stack (do they use tools that complement or compete with yours?)
  • Behavioral fit: How do your best customers find you? What content do they consume? What's their buying journey look like?
  • Negative filters: Who should you explicitly EXCLUDE? (Too small, wrong industry, already using a competitor with a 3-year contract)

Pro tip: Analyze your last 20 closed-won deals. What do they have in common beyond the obvious? Look for patterns in tech stack, hiring velocity, funding stage, and growth trajectory. These are your hidden ICP dimensions.

With MarketBetter's Audience Builder, you can define these ICP criteria and use AI enrichment to automatically score every account in your database against your ideal profile โ€” no manual research required.

Step 2: Instrument Your Engagement Signalsโ€‹

Once your ICP is defined, you need to capture engagement signals from accounts that match:

Website Visitor Identification (Your #1 signal source)

  • Track anonymous website visitors and resolve them to companies
  • Identify which pages they visit (pricing = high intent, blog = research phase)
  • Track visit frequency and recency (3+ visits in a week = active buying cycle)
  • Identify multi-stakeholder visits (multiple people from the same company = committee forming)

Content Engagement

  • Which accounts are downloading your whitepapers?
  • Who's watching your webinars?
  • Which companies are engaging with your LinkedIn content?

Email and Outreach Engagement

  • Opens and clicks are noisy โ€” focus on reply sentiment and multi-touch engagement
  • An account that opens 5 emails without clicking is not engaged; an account that clicks once and visits your site is

Step 3: Layer Readiness Signalsโ€‹

Engagement tells you who's interested. Readiness tells you who's ready to buy. The difference matters.

Key readiness signals:

  • Pricing page visits: The clearest buying signal in B2B. If they're on your pricing page, they're evaluating budget
  • Repeat visits with increasing depth: Going from blog โ†’ features โ†’ pricing โ†’ about us โ†’ pricing again = active evaluation
  • Champion job changes: When a former customer or power user moves to a new company, that's a warm introduction waiting to happen
  • Competitive research signals: Visiting your comparison pages or G2 reviews
  • Internal momentum: Multiple stakeholders from the same account engaging simultaneously = buying committee activation
  • Conversation intelligence: On calls, listen for pain point articulation, timeline mentions, budget discussions, and stakeholder references

MarketBetter's GTM signal engine captures these readiness signals automatically and feeds them into a unified scoring model โ€” so your reps don't have to stitch together data from 8 different tools.

Step 4: Create the Daily SDR Playbookโ€‹

This is where SBM comes to life. Every morning, your SDRs should see a prioritized list of ~100-150 accounts that are:

โœ… ICP fit (firmographic + technographic match) โœ… Actively engaging (website visits, content consumption, email interaction) โœ… Showing readiness (pricing page views, repeat visits, champion moves, multi-stakeholder engagement)

This is the Daily SDR Playbook โ€” and it eliminates the single biggest productivity killer in sales: deciding who to call.

Instead of browsing through thousands of accounts wondering where to start, your reps open their playbook and see exactly who needs attention TODAY, ranked by signal strength. The #1 account might be a perfect-fit company whose VP of Sales just visited your pricing page for the third time this week. The #50 account might be a good-fit company with rising blog engagement.

Both are better than cold outreach to a random account on a static list.

MarketBetter's Daily SDR Playbook does exactly this โ€” it synthesizes ICP fit, engagement signals, and readiness indicators into a single prioritized view. Reps see who to call, why they should call, and what to say. Every morning. Automatically.

Step 5: Personalize Outreach Based on Signalsโ€‹

Signal-based selling doesn't stop at prioritization. The signals themselves tell you what to say.

Instead of: "Hi [Name], I noticed [company] is growing fast and thought you might be interested in..."

Try: "Hi [Name], I saw that a few folks from [Company] have been looking at our pricing and integration docs this week. Looks like you're evaluating solutions for [specific use case]. Would it help if I walked you through how companies like [similar customer] set this up?"

That's not creepy โ€” that's relevant. And relevance drives 3-5x higher response rates than generic personalization.

Signal-aware messaging templates:

Signal DetectedMessaging Approach
Pricing page visitLead with ROI and implementation ease
Competitor comparison pageDifferentiate on your unique value prop
Champion job changeReference their previous experience with your product
Multiple stakeholders browsingAcknowledge the evaluation and offer a team demo
Repeat blog visitor moving to product pagesBridge from their content interest to a product conversation
High engagement + no demo bookedAsk directly โ€” they're clearly interested, remove the friction

Signal-Based Selling Metrics: What to Trackโ€‹

If you're shifting to signal-based selling, you need new metrics. The old ones (activities per day, emails sent, calls made) measure effort. SBM metrics measure impact.

Activity Metrics โ†’ Signal Metricsโ€‹

Old Metric (Activity-Based)New Metric (Signal-Based)Why It Matters
Emails sent per daySignal-triggered outreach %What % of your outreach is based on a real signal? Target 70%+
Calls per dayConversations per signalHow many signals convert to actual conversations?
Accounts touchedSBM coverageAre you working ALL your hot accounts, or leaving signals on the table?
Response rate (overall)Response rate (signal vs. cold)Side-by-side comparison proves the model works
Meetings bookedSignal-to-meeting conversionHow efficiently do signals convert to pipeline?
Pipeline generatedPipeline per signal sourceWhich signals generate the most valuable pipeline?

Benchmarks for Signal-Based Sellingโ€‹

Based on data from teams running signal-based workflows:

  • Signal-triggered outreach response rate: 3-5x higher than cold outbound
  • Time to first meeting: 40-60% faster when working signal-prioritized accounts
  • SDR ramp time: Reduced significantly โ€” new reps don't need to "learn" the territory because the signals tell them where to focus
  • Rep retention: Higher โ€” reps who feel productive and have meaningful conversations stay longer
  • Pipeline quality: Deals from signal-sourced accounts close at higher rates because the timing is right

Common Mistakes in Signal-Based Sellingโ€‹

Mistake 1: Treating All Intent Data as Equalโ€‹

Buying a third-party intent data subscription and calling it "signal-based selling" is like buying a gym membership and calling yourself fit. The data is just the raw material โ€” you need to layer it with your own first-party signals and ICP scoring to create real intelligence. Read more about why generic intent data fails sales teams.

Mistake 2: Overcomplicating the Signal Stackโ€‹

You don't need 15 signal sources. Start with three:

  1. Website visitor identification โ€” your highest-quality, most actionable signal
  2. ICP scoring โ€” firmographic and technographic fit
  3. Engagement scoring โ€” email, content, and website engagement combined

That's enough to build a functioning SBM. You can add champion tracking, conversation intelligence, and third-party intent data later.

Mistake 3: Not Acting Fast Enoughโ€‹

Signals have a half-life. A pricing page visit from 30 minutes ago is a hot lead. A pricing page visit from 30 days ago is a historical footnote. Your SBM needs to feed into a daily (ideally real-time) workflow, not a weekly report that sits in someone's inbox.

Mistake 4: Ignoring Signal Decayโ€‹

Related to above: signals decay. A company that was hot last month may be ice cold today (they chose a competitor, the project got shelved, the champion left). Your SBM must be dynamic โ€” accounts should move in AND out of your active market based on current signals, not historical ones.

Mistake 5: Not Connecting Signals to CRMโ€‹

If your signals live in a dashboard that's separate from your CRM and sales engagement tools, reps won't use them. The signal has to appear where reps already work โ€” in Salesforce, HubSpot, or their daily workflow tool. MarketBetter pushes signals and daily playbook tasks directly into your CRM, eliminating the "another tab to check" problem.

Signal-Based Selling vs. Traditional Approachesโ€‹

DimensionTraditional OutboundABMSignal-Based Selling
Account selectionStatic list, territory-basedCurated list, committee-basedDynamic, signal-driven
PrioritizationAlphabetical, round-robin, or gut feelTier 1/2/3 based on fitReal-time signal scoring
TimingWhen the sequence firesWhen the campaign launchesWhen the buyer shows intent
PersonalizationName and company merge fieldsAccount-specific content and adsSignal-specific messaging
Daily rep workflow"Work through the list""Run the plays for target accounts""Here are 100 accounts showing buying signals TODAY"
AdaptabilitySlow โ€” requires list rebuildsMedium โ€” requires campaign updatesReal-time โ€” SBM updates continuously
SDR experienceGrindingStructured but slowFocused and productive

Signal-based selling isn't replacing ABM โ€” it's making it dynamic. You still need account selection and personalized engagement. But instead of running static plays against a fixed target account list, you're running signal-triggered plays against a live market.

How MarketBetter Powers Signal-Based Sellingโ€‹

We built MarketBetter specifically for signal-based selling because we lived the pain of the alternative. Every feature maps to a piece of the SBM framework:

Audience Builder + AI Enrichment โ†’ ICP Fit (Circle 1) Define your ICP criteria โ€” industry, size, tech stack, growth signals โ€” and let AI enrichment automatically score and segment your entire addressable market. No manual research. No spreadsheet gymnastics.

Website Visitor Identification โ†’ Engagement Score (Circle 2) Track every company visiting your website. See which pages they view, how often they return, and how many stakeholders are engaging. Our customers track 35,000+ visits and identify 5,000+ companies monthly โ€” all feeding directly into their SBM.

GTM Signal Engine โ†’ Readiness Score (Circle 3) Pricing page visits. Repeat visits with increasing depth. Champion job changes. Conversation intelligence from call recordings. All synthesized into a readiness score that tells you who's ready to buy.

Daily SDR Playbook โ†’ The Center of the Venn (Your SBM) Every morning, your reps see a prioritized list of the ~100 accounts sitting at the intersection of ICP fit, engagement, and readiness. No guessing. No list-surfing. Just focused, signal-driven outreach to the accounts most likely to convert today.

CRM Integration โ†’ Signal-to-Action Every signal, every playbook recommendation pushes directly into Salesforce and HubSpot. Reps never need to leave their workflow to access their SBM.

This isn't theoretical. MarketBetter holds a 4.97 rating on G2 โ€” the highest-rated platform in our category โ€” because teams using signal-based selling with our platform see real results: higher response rates, more meetings booked, faster ramp times, and reps who actually enjoy their jobs.

Getting Started with Signal-Based Sellingโ€‹

You don't need to overhaul your entire GTM motion overnight. Here's a practical 30-day ramp:

Week 1: Foundation

  • Define your ICP (or sharpen the one you have)
  • Implement website visitor identification
  • Identify your top 3 signal sources

Week 2: Instrumentation

  • Set up engagement scoring based on website visits + email engagement
  • Configure readiness signals (pricing page alerts, repeat visit tracking)
  • Build your first Daily SDR Playbook

Week 3: Activation

  • Train reps on signal-based workflow (who to call, what signals mean, how to personalize)
  • Run signal-based outreach alongside traditional outbound to benchmark results
  • Start tracking signal-based metrics (response rates, conversion rates by signal type)

Week 4: Optimization

  • Analyze which signals correlate with pipeline creation
  • Adjust signal weights and ICP scoring based on results
  • Scale what works, cut what doesn't

Beyond 30 days:

  • Add champion tracking and conversation intelligence
  • Build signal-based sequences (different messaging triggered by different signals)
  • Layer in AI SDR capabilities for automated follow-up on lower-priority signals

The Future of Signal-Based Sellingโ€‹

Signal-based selling isn't a trend โ€” it's the inevitable evolution of B2B sales. As buying cycles become more complex, more digital, and more committee-driven, the teams that win will be the ones that can:

  1. See buying signals in real-time across every channel
  2. Prioritize the right accounts at the right moment
  3. Act with speed and relevance that matches the buyer's urgency
  4. Learn which signals drive pipeline and continuously refine their SBM

The SDR role isn't going away. But the SDR who manually prospects from a spreadsheet is going the way of the door-to-door salesman. The future belongs to signal-driven reps โ€” armed with real-time intelligence, working a dynamic market, and spending every minute on accounts that actually want to hear from them.


Free Tool

Try our AI Lead Generator โ€” find verified LinkedIn leads for any company instantly. No signup required.

Ready to Build Your Signal-Based Market?โ€‹

MarketBetter gives you the complete signal-based selling stack: ICP scoring, website visitor identification, GTM signal engine, and a Daily SDR Playbook that tells your reps exactly who to work today.

Stop spraying and praying. Start signal-based selling.

๐Ÿ‘‰ Book a demo and see your Signal-Based Market in action

Lead Scoring in 2026: Why Traditional Models Are Failing (And What to Do Instead)

ยท 9 min read
MarketBetter Team
Content Team, marketbetter.ai

Your lead scoring model is lying to you.

That VP of Sales with a score of 85? Turns out they were researching for a competitor. The contact who scored 12? Just booked a demo after visiting your pricing page yesterday.

Traditional lead scoring was built for a buying journey that no longer exists. And yet, most sales teams are still using models from 2015 to prioritize 2026 leads.

Here's why it's broken โ€” and what actually works.

11 Best Buyer Intent Data Tools for B2B Sales [2026]

ยท 12 min read
MarketBetter Team
Content Team, marketbetter.ai

Buyer intent data promises to reveal who's ready to buy. But which tools actually deliver for SDR teams?

B2B buyers complete 70% of their research before engaging with sales. By the time they fill out a demo form, they've probably already shortlisted vendors. Intent data tools help you find these buyers earlier โ€” but not all intent data is created equal.

This guide compares the best buyer intent data tools in 2026, with real pricing, actual features, and honest assessments of what works for different team sizes.