Champify does one thing extremely well: it tracks when your former champions and customers change jobs, so your sales team can reach out at the perfect moment. Former buyers who already trust your product convert at 3-5x higher rates than cold prospects.

But that focused value comes at a focused price. Here's the full breakdown of what Champify costs in 2026 and whether the ROI math works for your team.

Champify's Published Pricing​

Champify is one of the few champion tracking tools with transparent pricing. Here are the three tiers:

Annual contracts are standard. That means $24,000-72,000/year depending on tier.

What Each Plan Actually Includes​

Core ($2,000/month)​

Included:

• Track 15,000 contacts for job changes
• Salesforce package with unlimited users
• Slack and email alerts when champions move
• Colleague referrals
• RevOps orchestration (field mapping, routing, dedup)
• 50+ pre-built Salesforce reports and 3 dashboards
• Standard onboarding and a dedicated CSM
• $500K ROI Guarantee (Champify's standout offer)

Not included (available as add-ons):

• InsiderAI (AI-powered nurture insights)
• Calendar Sync
• New Executive Hires tracking
• CRM Clean

Best for: Teams with fewer than 15,000 contacts in their CRM who want basic champion tracking with job change alerts.

Pro ($3,000/month)​

Everything in Core, plus:

• Track 40,000 contacts (add-on up to 200K)
• Calendar Sync for 50 users (add-on up to 1K)
• InsiderAI for 2,000 accounts — AI-generated nurture insights
• Custom playbooks for different champion scenarios
• Premier onboarding and success
• New Executive Hires tracking for 2,000 accounts

Best for: Mid-market teams with significant Salesforce data who want AI-powered insights on when and how to engage champions.

Enterprise ($6,000/month)​

Everything in Pro, plus:

• Track 150,000 contacts (add-on up to 2M)
• InsiderAI for 5,000 accounts
• CRM Clean for 200,000 contacts (data hygiene at scale)
• Enterprise Salesforce governance
• Apex Governor (prevents exceeding Salesforce limits)
• Strategic onboarding and success
• Custom relationship context
• Sandbox deployment

Best for: Enterprise organizations with massive CRM databases that need champion tracking, data hygiene, and governance in one platform.

The Hidden Costs​

Add-Ons​

Champify's pricing page lists several features as "add-on" on lower tiers:

• InsiderAI — Available as add-on on Core (pricing undisclosed)
• Calendar Sync — Add-on on Core (syncs meeting history for context)
• New Executive Hires — Add-on on Core and Pro
• CRM Clean — Add-on on Core and Pro, 50K contacts on Pro
• Additional contacts tracked — Add-on pricing for exceeding tier limits

Champify doesn't publish add-on pricing. Based on Vendr data (median annual spend: $15,750 across 11 buyers), most teams end up between $15K-30K/year.

Implementation Cost​

• Standard onboarding included on all plans
• Requires Salesforce integration (Champify is Salesforce-native)
• HubSpot users: Champify is built for Salesforce. If you're on HubSpot, you'll need middleware or a different tool.
• Typical time to value: 2-4 weeks

Salesforce Dependency​

Champify's entire platform runs inside Salesforce. If you're not on Salesforce, Champify isn't an option. This is both a feature (deep integration) and a limitation (vendor lock-in).

ROI Math: Does It Pay for Itself?​

Champify offers a $500K ROI Guarantee — they claim you'll generate $500K+ in pipeline from champion tracking.

Let's sanity-check that:

Assume you track 15,000 contacts (Core plan at $2K/month = $24K/year):

• 3-5% of contacts change jobs annually = 450-750 job changes detected
• 20-30% of those land at companies in your ICP = 90-225 qualified leads
• 10-15% conversion rate (warm leads from known champions) = 9-34 opportunities
• Average deal size of $30K = $270K-$1M in pipeline

At $24K/year, the ROI math works for most B2B companies with average deal sizes above $20K. If your ACV is under $10K, the payback period stretches and alternatives become more attractive.

How Champify Pricing Compares​

The Big Question: Do You Need a Dedicated Champion Tracking Tool?​

Champion tracking is high-value but narrow. Champify does it exceptionally well — the Salesforce integration is deep, the alerts are reliable, and the ROI guarantee shows confidence.

But at $24K-72K/year, you're paying for a single signal type (job changes) delivered through a single CRM (Salesforce).

Consider alternatives if:

• Your ACV is under $15K — the ROI math gets tight
• You're not on Salesforce — Champify doesn't support HubSpot natively
• You want champion tracking PLUS visitor ID, intent signals, and outbound execution in one platform
• You have fewer than 10,000 contacts worth tracking

MarketBetter includes champion tracking as part of a broader signal-driven SDR platform — website visitors, intent signals, job changes, and a daily playbook — starting at $99/user/month. Instead of paying for champion tracking separately, you get it alongside the rest of your outbound workflow.

See how MarketBetter combines signals into one SDR playbook →

Related Reading:

• Champify Review 2026
• Best Champify Alternatives
• UserGems vs Champify
• Champion Tracking Without UserGems

Clay has become the darling of the outbound sales world. RevOps teams love it. LinkedIn is full of "Clay workflows" content. And the product genuinely does something powerful — it connects 50+ data sources and lets you build custom enrichment workflows without code.

But behind the hype, there's a real question: Is Clay's credit-based pricing actually cost-effective for your team, or does it nickel-and-dime you into spending more than dedicated tools?

After digging through G2 reviews, TrustRadius feedback, Reddit discussions, and real user case studies, here's an honest assessment.

What Clay Actually Does​

Clay is a data enrichment and workflow automation platform for sales teams. Think of it as a smart spreadsheet where each column can pull data from a different source — LinkedIn, Clearbit, Hunter, Lusha, company websites, news articles — and an AI agent (Claygent) can research and summarize anything.

Core capabilities:

• Pull leads from 50+ data sources into a single table
• Enrich contacts with emails, phone numbers, company data, technographics
• Use AI (Claygent) to research companies, write personalized snippets, and classify leads
• Build automated workflows that trigger enrichment and outreach
• Connect to CRMs and email sequencers for execution

What makes it different: Instead of being locked into one data provider (like ZoomInfo), Clay aggregates multiple providers and uses a "waterfall" approach — if Provider A doesn't have the email, it tries Provider B, then C. This typically yields 20-40% more data coverage than any single provider.

What Users Love​

Based on 200+ G2 reviews (4.9/5 rating), TrustRadius, and Reddit feedback:

1. Unmatched Flexibility​

"Clay is incredibly powerful as a data enrichment and workflow tool. I like how flexible it is — you can connect it with other platforms, build custom flows, and really tailor it to your specific use cases." — G2 reviewer

This is Clay's superpower. Unlike rigid platforms where you're stuck with their data and their workflow, Clay lets you build exactly what you need. Need to find companies that recently raised funding, check their tech stack, find the VP of Sales, verify their email, and write a personalized opener? That's one Clay table.

2. Waterfall Enrichment​

Instead of paying ZoomInfo $15K/year for one data source, Clay cascades through multiple providers. Users report 20-40% higher match rates vs. single-provider tools.

3. AI Research at Scale​

Claygent — Clay's AI agent — can research any company or person and return structured data. Common use cases: summarizing recent news, identifying pain points from job postings, or personalizing outreach based on LinkedIn activity.

4. No Per-Seat Pricing​

Unlimited users on every plan. For large teams, this is a significant cost advantage over per-seat tools like ZoomInfo or Apollo.

What Users Complain About​

1. Credit Math Gets Complicated Fast​

"With Clay, you can build amazing workflows, but the credit system means costs can spiral if you're not careful about how many enrichment steps each row hits." — G2 reviewer

Each enrichment action costs credits — and different actions cost different amounts. A single lead might use 5-15 credits across email verification, phone lookup, company enrichment, and AI research. At $0.03-0.075 per credit, that's $0.15-1.12 per lead before you've sent a single email.

Real math for a 5-person SDR team:

• 500 leads/week × 10 credits/lead = 5,000 credits/week = 20,000 credits/month
• Explorer plan (10K credits/month) = insufficient
• Pro plan (50K credits) at $720/month — and you might still run over

2. Steep Learning Curve​

"It took our team about 2-3 weeks to really get comfortable building workflows. It's powerful, but it's not plug-and-play." — TrustRadius reviewer

Clay is closer to a low-code platform than a traditional sales tool. If your SDR team expects to sign up and start prospecting on day one, Clay will frustrate them.

3. No Outreach Built In​

Clay is an enrichment engine, not an email sender. You still need Instantly, Lemlist, Outreach, or another tool to actually send campaigns. That's another $37-137/month per user.

4. Data Quality Varies​

Aggregating 50+ sources sounds great until you realize some sources return outdated data. Multiple users report getting personal emails instead of work emails, or job titles that are 1-2 years old.

5. Clay ≠ Your CRM​

Clay tables look like spreadsheets, but they're not a CRM. You need to export data to Salesforce/HubSpot for actual pipeline management. The sync works, but it's another integration to maintain.

Clay Pricing: The Credit Reality​

The hidden cost: Clay is just the enrichment layer. Add your email sequencer ($37-137/month), CRM ($0-150/user/month), and any premium data providers you bring-your-own-key for. Total stack cost: $800-2,000+/month for a 5-person team.

For a deep dive, see our Clay Pricing Breakdown.

Who Clay Is (and Isn't) For​

Clay is great for:​

• RevOps teams who want to build custom enrichment workflows
• Agencies managing outbound for multiple clients
• Data-savvy SDR managers who enjoy building systems
• Teams already paying for 3+ data tools — Clay can consolidate

Clay is NOT for:​

• SDR teams that want plug-and-play — too much setup required
• Small teams without a RevOps resource — someone needs to maintain the workflows
• Teams that need outreach + data in one tool — Clay doesn't send emails
• Budget-conscious teams — credit costs add up, and you still need execution tools

How Clay Compares to Alternatives​

The Bottom Line​

Clay is genuinely powerful. If you have a RevOps team that can build and maintain enrichment workflows, it delivers data coverage that no single provider can match. The waterfall approach, Claygent AI, and unlimited seats make it a compelling enrichment layer.

But "enrichment layer" is the key phrase. Clay tells you about your prospects. It doesn't tell your SDRs what to do with that information.

If you want a platform that combines prospect data with buyer signals AND tells your team exactly who to call, what to say, and which accounts to prioritize — that's a different category of tool.

See how MarketBetter turns signals into action →

Related Reading:

• Clay Pricing Breakdown 2026
• Best Clay Alternatives
• MarketBetter vs Clay

Cognism doesn't publish pricing publicly. Their pricing page asks you to "book a demo" — a common tactic among enterprise sales intelligence platforms to keep competitors guessing and maximize deal sizes.

We compiled pricing data from Vendr, Warmly.ai, Coldreach, SalesIntel, and user reports across G2 and Reddit to give you the real numbers. Here's what Cognism costs in 2026 and how to decide if it fits your budget.

Cognism Pricing Summary​

Key insight: Cognism charges a hefty platform fee ($15K–$25K) before adding per-user licenses. For a 10-person SDR team on the Elevate plan, you're looking at ~$50,000/year — just for contact data.

How Cognism's Pricing Works​

Platform Access Fee​

Unlike tools such as Apollo or Lusha that charge per-seat with no base fee, Cognism requires a substantial upfront platform fee. This covers core infrastructure, database access, and basic integrations.

• Grow plan: ~$15,000/year base
• Elevate plan: ~$25,000/year base

Per-User Licensing​

On top of the platform fee, each user seat costs:

• Grow: ~$1,500/user/year
• Elevate: ~$2,500/user/year

"Unrestricted" Access (With a Catch)​

Cognism markets "unlimited" data access, but there's a "fair use" policy. Based on user reports, this typically means:

• ~2,000 records per user per month
• Reasonable daily export limits
• No traditional credit system (unlike Apollo or ZoomInfo)

This sounds good in theory, but if your team needs to pull thousands of contacts weekly, you may hit invisible walls that require negotiation.

What Each Plan Includes​

Grow Plan (~$15K + $1,500/user/year)​

• Access to global B2B database
• Business emails and direct dials
• Standard CRM integrations (Salesforce, HubSpot)
• Chrome extension for LinkedIn prospecting
• Basic enrichment features
• CSV export

Missing: Diamond Data® (phone-verified numbers), intent data, advanced enrichment API.

Elevate Plan (~$25K + $2,500/user/year)​

Everything in Grow, plus:

• Diamond Data® — Phone-verified mobile numbers (Cognism's flagship feature)
• Bombora intent data — See which accounts are researching relevant topics
• Signals — Real-time insights and AI-driven segmentation
• Advanced enrichment — Instant, scheduled, and on-demand enrichment
• Diamonds on Demand — Submit contacts for manual verification (limited to ~50/month, 48-hour turnaround)

Enterprise Plan (Custom, $30K–$100K+/year)​

Everything in Elevate, plus:

• Higher fair-use data limits
• Custom API access and webhooks
• Dedicated account management
• Custom integrations
• Volume discounts for large teams
• Priority support

Hidden Costs to Watch For​

1. Onboarding and Training​

Cognism's self-service experience has improved, but enterprise deployments often include $2,000–$5,000 in professional services for setup, CRM configuration, and team training.

2. API and Enrichment Overages​

The enrichment API (Instant Enrich, Scheduled Enrich) is typically billed separately from standard seat access. Heavy API usage can add $5,000–$15,000/year depending on volume.

3. Annual Lock-In​

No monthly billing option. Cognism requires annual (sometimes multi-year) contracts. If the data quality doesn't meet expectations in your specific industry or region, you're stuck paying for the full term.

4. Diamond Data® Coverage Gaps​

Diamond Data® is Cognism's biggest selling point — but it doesn't cover every contact. The verification process is strongest for UK and European contacts. North American coverage exists but is notably less comprehensive, which matters if that's your primary market.

5. Intent Data Costs Extra​

Bombora intent data is only included on the Elevate plan or higher. On the Grow plan, you're paying $15K+ for data without any buying signals, which significantly reduces the value for prioritizing outreach.

Cost Comparison: Cognism vs. Competitors​

The contrast is stark: Cognism gives you data to fuel outreach. MarketBetter gives you data AND the tools to execute — visitor identification, daily playbook, smart dialer, email automation, and AI chatbot in one platform.

Cognism's Strengths Worth Paying For​

Diamond Data® Quality​

When it works, it's genuinely best-in-class. Phone-verified mobile numbers mean 3x higher connect rates versus unverified databases. For cold-calling-heavy teams in Europe, this alone can justify the premium.

GDPR Compliance​

Cognism screens against DNC lists in 15+ countries as standard. For companies selling into Europe, this compliance-first approach provides real legal protection that cheaper data providers can't match.

Clean UX and Chrome Extension​

The platform is intuitive, and the Chrome extension for LinkedIn prospecting is consistently praised. Building targeted lists by job title, company size, and technographics is straightforward.

Cognism's Weaknesses at This Price Point​

Data-Only Platform​

Cognism provides contact data. That's it. No dialer, no email sequencing, no chatbot, no workflow automation. You need to pipe Cognism data into separate execution tools (Outreach, SalesLoft, etc.), adding another $50–$150/user/month to your stack.

For a 10-person team, your actual cost becomes:

• Cognism Elevate: ~$50,000/year
• SalesLoft or Outreach: ~$18,000–$30,000/year
• Total: $68,000–$80,000/year

With MarketBetter, you get identification, data, AND execution in one platform.

North American Coverage Gaps​

Multiple reviewers note that while European data is excellent, US coverage — especially for mid-market companies and niche industries — can be inconsistent. If your ICP is primarily US-based, ZoomInfo or Apollo may offer better coverage at lower prices.

Diamonds on Demand Limitations​

The premium verification service (submit contacts for manual phone verification) is capped at ~50 contacts/month and takes up to 48 hours. For teams that need verified numbers at scale, this bottleneck can be frustrating.

Who Should Buy Cognism?​

✅ Good Fit​

• Cold-calling-heavy SDR teams selling into Europe/UK
• Companies that need GDPR-compliant data as a legal requirement
• Teams with existing execution tools (SalesLoft, Outreach) that just need better data
• Mid-market to enterprise companies with $20K+ annual data budgets

❌ Poor Fit​

• US-focused teams (Apollo or ZoomInfo offer better NA coverage)
• Small teams that need data + execution in one tool
• Budget-conscious teams under $15K/year for sales intelligence
• Companies that primarily need website visitor identification rather than prospecting data

The Bottom Line on Cognism Pricing​

Cognism is a premium data platform with a price tag to match. The Diamond Data® verified numbers are genuinely differentiated, and GDPR compliance is best-in-class.

But at $22,500–$50,000+/year for data alone (no execution tools included), the total cost of ownership gets steep fast. When you add execution platforms, you're easily spending $70K+/year for what MarketBetter delivers in a single platform — visitor identification, intent signals, daily SDR playbooks, smart dialer, and email automation.

The question isn't whether Cognism has good data. It does. The question is whether data alone is worth $50K/year when you could get data plus execution for less.

See how MarketBetter combines signals and execution →

Cognism has built its reputation on one promise: more accurate phone numbers than anyone else. Their Diamond Data® — manually phone-verified mobile numbers — is the flagship feature that justifies premium pricing starting at $15,000/year.

But does the reality match the marketing? We analyzed 500+ G2 reviews (4.6/5 rating), 240+ Capterra reviews (4.7/5), Gartner Peer Insights feedback, Reddit threads, and independent tests to give you the full picture.

Quick Verdict​

Best for: European-focused SDR teams that rely heavily on cold calling and need GDPR-compliant, verified mobile numbers.

Not ideal for: US-focused teams, budget-conscious organizations, or companies that need execution tools beyond raw data.

What Is Cognism?​

Cognism is a B2B sales intelligence platform headquartered in London that provides verified contact and company data for outbound sales teams. Founded in 2015, the company has grown rapidly — particularly in the UK and European markets — by focusing on two key differentiators:

1. Diamond Data® — Phone-verified mobile numbers with claimed 98% accuracy
2. GDPR-first compliance — DNC list screening across 15+ countries

The platform serves SDRs, BDRs, account executives, and revenue operations teams who need reliable contact data to power outbound campaigns. Cognism offers a global database of 400M+ contacts, though its strength clearly skews toward European coverage.

What Users Love About Cognism​

1. Diamond Data® Delivers on Connect Rates​

The flagship feature earns its reputation. Users consistently report 2–3x higher connect rates when using Diamond Data® verified numbers compared to standard databases.

"The data is accurate, up-to-date, and incredibly easy to use. A must-have for any sales team!" — G2 reviewer

"Cognism has transformed how we find and qualify leads." — G2 reviewer

For cold-calling-heavy teams, the difference is measurable. When your SDRs spend less time calling wrong numbers and more time having conversations, the ROI compounds quickly.

Important caveat: Diamond Data® coverage is strongest in the UK and Western Europe. Users targeting US prospects report good — but not exceptional — mobile number coverage.

2. GDPR Compliance You Can Trust​

For European teams, Cognism's compliance is a genuine competitive advantage. The platform screens against Do-Not-Call lists in 15+ countries and maintains CCPA compliance for US data.

This isn't just a checkbox feature. Companies selling into regulated industries or across European borders face real legal risk using non-compliant data providers. Cognism removes that concern.

3. Chrome Extension Is a Productivity Winner​

The LinkedIn Chrome extension is one of Cognism's best-reviewed features. It lets SDRs:

• Pull verified contact data from LinkedIn profiles with one click
• Export directly to CRM (Salesforce, HubSpot)
• See company firmographics and technographics inline
• Build targeted lists without leaving LinkedIn

"The LinkedIn extension is fantastic for prospecting. I can find verified contacts while browsing Sales Navigator." — Capterra reviewer

4. Clean, Intuitive Interface​

Unlike enterprise data platforms that require weeks of training, Cognism's web app is genuinely easy to use. List building with filters for job title, seniority, company size, industry, and technographics is straightforward.

The CSV export functionality is also praised — users can quickly pull bulk data for offline analysis or import into other tools.

5. Intent Data via Bombora Partnership​

On higher-tier plans, Cognism integrates Bombora's intent data to show which accounts are actively researching topics related to your solution. This is useful for prioritizing outreach timing, though several users note the signals require interpretation to avoid false positives.

Where Cognism Disappoints​

1. North American Data Gaps​

This is the most consistent complaint across review platforms. While European data earns rave reviews, US coverage has notable gaps:

"Coverage in North America, especially mid-market companies, can feel less comprehensive." — G2 reviewer

An independent test cited by ZoomInfo found that 62.5% of Cognism's mobile numbers, direct dials, and landlines were incomplete. While this test may not be perfectly representative, it aligns with what multiple users report about non-European data quality.

If your ICP is primarily US-based, Cognism may not be your best option. Apollo, ZoomInfo, and SalesIntel offer stronger North American coverage.

2. Pricing Lacks Transparency​

No published pricing. Annual contracts required. Platform fees starting at $15,000 before adding per-user licenses.

"The pricing model is a common complaint. Sales teams want to quickly assess if a tool fits their budget." — Industry analyst

For a 5-person SDR team on the Elevate (Diamond) plan, you're looking at ~$37,500/year for contact data. That's significant — especially when you still need separate tools for email sequences, dialing, and chat.

3. Data-Only Platform (No Execution)​

Cognism provides contacts. Full stop. There's no:

• Built-in dialer
• Email sequence builder
• AI chatbot
• Workflow automation
• Daily SDR playbook

Your SDRs pull data from Cognism, then switch to SalesLoft/Outreach for sequences, your phone system for calls, and another tool for chat. Every context switch costs time, and the total stack cost adds up fast.

4. Diamonds on Demand Is Limited​

The premium on-demand verification service sounds great in theory — submit any contact and Cognism's team will manually verify their phone number. In practice:

• Limited to ~50 contacts/month
• Takes up to 48 hours for results
• Only available on the highest tier
• Not scalable for teams that need thousands of verified numbers

"The on-demand research platform is not scalable." — SalesIntel analysis

5. Data Accuracy Claims vs. Reality​

Cognism claims 98% accuracy for Diamond Data®. However, their own Terms & Conditions include a disclaimer that they "do not warrant accuracy, likely results, or reliability" for data.

Real-world accuracy is high for verified European contacts, but the 98% claim doesn't extend to the entire database. Standard (non-Diamond) contacts have the same accuracy limitations as any B2B data provider.

Cognism vs. MarketBetter: Different Philosophies​

The fundamental difference: Cognism tells your SDRs "here's who might buy." MarketBetter tells your SDRs "here's who's interested, here's exactly what to do, and here are the tools to do it — right now."

Cognism vs. Other Data Providers​

Cognism vs. ZoomInfo​

• ZoomInfo has larger US database; Cognism has better European coverage
• ZoomInfo offers more execution features (engagement tools, chat)
• ZoomInfo pricing is similar ($15K–$100K+/year)
• Choose Cognism for Europe; ZoomInfo for US-heavy prospecting

Cognism vs. Apollo​

• Apollo is dramatically cheaper ($49–$119/user/month, free tier available)
• Apollo includes email sequencing and a built-in dialer
• Cognism has better verified phone data (Diamond Data®)
• Choose Apollo for budget-conscious teams; Cognism for cold-calling accuracy

Cognism vs. Lusha​

• Lusha is simpler and cheaper ($29–$79/user/month)
• Cognism has deeper data enrichment and intent capabilities
• Both have strong Chrome extensions
• Choose Lusha for simple look-ups; Cognism for enterprise data intelligence

Who Should Buy Cognism?​

✅ Good Fit​

• SDR teams in the UK/Europe where GDPR compliance is mandatory
• Cold-calling-heavy teams where connect rates directly impact revenue
• Companies with existing execution tools that just need better data
• Mid-market to enterprise organizations with $20K+ data budgets
• Teams that value phone-verified numbers over database size

❌ Poor Fit​

• US-focused teams (better options exist for North American coverage)
• Small teams that need data + execution in one platform
• Companies under $15K annual budget for sales intelligence
• Teams that primarily need website visitor identification
• Organizations that want transparent, self-service pricing

The Bottom Line​

Cognism earns its 4.6/5 G2 rating. Diamond Data® is a genuinely differentiated feature, GDPR compliance is best-in-class, and the platform is easy to use. For European cold-calling teams, it's a strong choice.

But at $22,500–$50,000+ per year for data alone — with no execution tools — the total cost of an effective sales stack escalates quickly. Add SalesLoft ($100–$150/user/month) and a chatbot ($50–$200/month), and a 10-person team is spending $70,000–$80,000/year across multiple tools.

The future of SDR productivity isn't better data in isolation. It's platforms that combine signals with execution — identifying who's interested, prioritizing actions, and giving SDRs the tools to act immediately.

That's exactly what MarketBetter does. Book a demo and see how one platform replaces your data provider, dialer, email tool, and chatbot.

Creating a marketing plan has traditionally been a weeks-long ordeal. You gather data, research competitors, define personas, map channels, set budgets, build timelines, and create a 30-page document that — let's be honest — nobody reads after the first meeting.

What if you could generate a solid first draft in 5 minutes?

AI marketing plan generators have gone from gimmicky to genuinely useful in 2026. The best ones don't just fill in a template — they research your company, analyze your market, and produce strategic recommendations that are surprisingly on-target.

This guide walks through how to create an AI marketing plan, compares the tools available, and shows you how to get a complete plan in minutes using MarketBetter's free Marketing Plan Generator.

What Is an AI Marketing Plan Generator?​

An AI marketing plan generator takes basic inputs about your business — company name, industry, target audience, goals — and produces a structured marketing plan with strategy, channels, tactics, and timelines.

The best tools do more than fill in a template. They:

1. Research your company — pulling data from your website, social media, and public sources
2. Analyze your market — identifying competitors, market trends, and opportunities
3. Recommend channels — suggesting the most effective marketing channels for your specific business
4. Propose tactics — offering concrete, actionable steps, not vague strategic platitudes
5. Suggest budgets — providing realistic budget allocations based on your company size and goals
6. Set timelines — creating a phased roadmap with milestones

Why Use AI to Generate a Marketing Plan?​

Speed​

A traditional marketing plan takes 2-4 weeks to research, write, and refine. An AI-generated first draft takes 5 minutes. Even if you spend 2-3 hours refining and customizing the AI output, you've saved 80%+ of the time.

Comprehensive Coverage​

Marketing plans often have blind spots. You focus on the channels you know and ignore ones you don't. AI tools consider all viable channels and tactics, reducing the risk of missing opportunities.

Data-Driven Recommendations​

AI generators can pull from vast amounts of data about what works for similar businesses. A human marketer might have experience with 5-10 companies in your space. An AI has been trained on thousands.

Starting Point, Not Finished Product​

The best use of AI marketing plans isn't to replace human thinking — it's to accelerate it. Having a structured first draft to react to is dramatically faster than starting from a blank page. You can agree, disagree, modify, and add your unique insights to an existing framework.

Accessibility​

Not every company has a marketing team. Founders, solopreneurs, and small teams often skip marketing plans entirely because they're intimidating to create. AI generators make strategic marketing accessible to everyone.

How to Create an AI Marketing Plan (Step by Step)​

Step 1: Choose Your Tool​

Here's a quick comparison of the major options:

MarketBetter Marketing Plan Generator — Free, no signup, AI-researched plan based on your company

• Input: Company name or URL
• Output: Full marketing plan with strategy, channels, tactics, and timelines
• Unique value: AI researches your company, competitors, and market automatically
• Cost: Free

Venngage AI Marketing Plan Generator — Free, template-focused

• Input: Business description, goals, audience
• Output: Visual marketing plan using templates
• Unique value: Beautiful visual output with editable templates
• Cost: Free (limited), Pro from $10/month

Visme AI Marketing Plan Generator — Free, design-centric

• Input: Text prompts about your business
• Output: Designed marketing plan presentation
• Unique value: Polished presentation-ready output
• Cost: Free (limited), Starter from $12.25/month

FounderPal Marketing Strategy Generator — Free, solopreneur-focused

• Input: Product description, target audience, goals
• Output: Marketing strategy with positioning, channels, and tactics
• Unique value: Built specifically for solopreneurs and indie founders
• Cost: Free (basic), Pro from $49 one-time

Piktochart AI Marketing Plan Generator — Free, infographic-style

• Input: Content about your business
• Output: Visual marketing plan
• Unique value: Infographic-style output
• Cost: Free (limited), Pro from $14/month

Easy-Peasy.AI Marketing Plan Generator — Free, text-based

• Input: Business name, industry, goals, audience
• Output: Text-based marketing plan
• Unique value: Simple, fast text output
• Cost: Free (limited), Plus from $9.99/month

Taskade AI Marketing Plan — Free, collaborative

• Input: Prompts about your marketing needs
• Output: Structured marketing plan in workspace format
• Unique value: Team collaboration features
• Cost: Free (limited), Pro from $8/user/month

Step 2: Provide Your Business Information​

The quality of your AI marketing plan directly correlates with the quality of your inputs. Here's what to prepare:

Essential inputs:

• Company name and website URL
• Industry and sub-industry
• Target audience (who are you trying to reach?)
• Main product/service and key differentiators
• Primary marketing goals (awareness, leads, sales, retention)
• Current stage (startup, growth, established)

Optional but helpful:

• Current marketing budget (even a rough range)
• Existing channels that work
• Main competitors
• Specific challenges or constraints
• Timeline (next quarter, next year)

Pro tip: With MarketBetter's Marketing Plan Generator, you only need your company name or URL. The AI researches everything else automatically from your website and public data.

Step 3: Generate and Review​

Once you submit your inputs, the AI generates a plan. Here's what a good AI marketing plan should include:

1. Executive Summary

• Business overview
• Key goals and objectives
• Target market summary

2. Market Analysis

• Industry overview and trends
• Competitive landscape
• Target audience personas
• SWOT analysis

3. Marketing Strategy

• Positioning statement
• Key messages and value proposition
• Brand voice and tone guidelines

4. Channel Strategy

• Recommended channels (content marketing, paid ads, social media, email, SEO, events, partnerships)
• Why each channel is recommended for your specific business
• Effort/impact analysis for channel prioritization

5. Tactical Plan

• Specific activities per channel
• Content calendar outline
• Campaign concepts
• Key milestones

6. Budget Allocation

• Recommended spend per channel
• Tool and resource costs
• Expected ROI by channel

7. Metrics and KPIs

• Key metrics to track per channel
• Reporting cadence
• Success benchmarks

Step 4: Customize and Refine​

The AI output is your starting point. Here's how to refine it:

Add your institutional knowledge. AI doesn't know that your CEO hates TikTok, that your best customer came from a podcast appearance, or that you tried Google Ads last year and lost money. Layer in what you know.

Prioritize ruthlessly. An AI plan might recommend 8 channels. If you're a 3-person team, pick 2-3 and do them well. Add the others to a "future consideration" list.

Set realistic budgets. AI budget recommendations are based on industry averages. Adjust based on your actual resources. A $5K/month marketing budget requires different tactics than a $50K/month one.

Add timelines and owners. AI plans are often light on who-does-what-by-when. Assign specific team members and deadlines to each tactic.

Validate channel recommendations. If the AI recommends LinkedIn as your top channel, does that match where your audience actually spends time? Cross-reference with your sales team's experience and your analytics data.

What Makes MarketBetter's Generator Different​

Most AI marketing plan generators are essentially prompt wrappers around ChatGPT. You fill in a form, it sends your inputs to an LLM with a template prompt, and you get generic output.

MarketBetter's Marketing Plan Generator works differently:

1. Automatic Company Research​

Enter just your company name or URL. The AI scrapes and analyzes your website, identifies your products, understands your positioning, and pulls relevant market data — before generating the plan. You don't have to describe your business; it figures it out.

2. Competitor-Aware Strategy​

The generator identifies your likely competitors and incorporates competitive positioning into its recommendations. Instead of generic channel suggestions, you get tactics that account for what your competitors are already doing.

3. Industry-Specific Recommendations​

A SaaS company's marketing plan should look nothing like a local restaurant's. MarketBetter's generator tailors channel mix, tactics, content types, and budget allocation to your specific industry and business model.

4. Actionable Specificity​

Instead of "do content marketing," you get recommendations like "publish 2 long-form comparison articles per month targeting [specific keywords] and promote via LinkedIn organic posts." Specific enough to act on immediately.

5. Free, No Signup​

No account creation. No credit card. No "freemium" with the good parts locked behind a paywall. Generate as many plans as you want.

Real-World Example: Creating a Marketing Plan for a SaaS Startup​

Let's walk through a real example. Imagine you're the marketing lead at a Series A B2B SaaS company that sells project management software to construction companies.

Input: Company URL (let's say constructionpm.io)

AI-generated plan highlights:

Target Audience: Construction project managers, general contractors, and operations directors at mid-size construction firms (50-500 employees)

Positioning: "The only project management tool built specifically for construction workflows — with field reporting, subcontractor tracking, and compliance documentation built in."

Recommended Channel Mix:

1. SEO/Content Marketing (40% of budget) — Target keywords like "construction project management software," "field reporting app for contractors," and "construction scheduling tool"
2. LinkedIn (25% of budget) — Sponsored content targeting construction industry titles + organic thought leadership
3. Industry Events (20% of budget) — Booth at ConExpo, World of Concrete, and regional construction tech events
4. Google Ads (15% of budget) — High-intent search campaigns for comparison keywords

Specific Tactics:

• Publish weekly blog content on construction management best practices
• Create comparison pages: "[Brand] vs Procore," "[Brand] vs Buildertrend"
• Launch a "Construction PM of the Month" spotlight series on LinkedIn
• Build a free construction project template library for lead generation
• Partner with construction industry associations for co-branded webinars

Metrics:

• Website traffic from organic search (target: 2x in 6 months)
• Demo requests per month (target: 50/month by month 6)
• Marketing-qualified leads (target: 150/month)
• Customer acquisition cost (target: <$500)

Total time to generate: ~3 minutes

This plan isn't perfect out of the box — you'd adjust based on your actual budget, team size, and what you know about your market. But it's a dramatically better starting point than a blank Google Doc.

When AI Marketing Plans Work Best​

1. Early-Stage Companies​

Startups and early-stage companies benefit most because they often lack marketing expertise on the team. An AI plan provides structure and direction when you're figuring things out.

2. Annual Planning Season​

When it's time to create next year's marketing plan, AI generates a solid first draft that your team can refine — saving weeks of planning meetings.

3. New Market Entry​

Launching in a new vertical or geography? AI can quickly analyze the new market and suggest an initial marketing approach.

4. Board Presentations​

Need to put together a marketing strategy slide for your board meeting by Friday? Generate a plan, pull the key points, and present with confidence.

5. Freelancer/Agency Onboarding​

If you're hiring a marketing agency or freelancer, generating an AI plan first ensures you have clear direction to share. It prevents the "we'll figure out strategy in month one" delay.

Limitations of AI Marketing Plans​

Be honest about what AI can't do:

• No proprietary insights — AI doesn't know your customer conversations, your sales team's feedback, or your unique competitive advantages that aren't public
• Generic benchmarks — Budget and KPI recommendations are industry averages, not tailored to your specific situation
• No brand personality — AI can suggest tone guidelines but can't capture your unique brand voice
• Snapshot, not dynamic — A plan generated today doesn't update as conditions change
• Execution gap — Even the best plan is worthless without execution. AI creates the plan; you still have to do the work

The best approach: AI generates the framework. Your team adds the insight, judgment, and execution.

Start Your Marketing Plan Now​

Stop staring at a blank page. Stop scheduling "strategy brainstorm" meetings. Stop paying agencies $5K to tell you what an AI can tell you for free.

Generate your free AI marketing plan →

Enter your company name or URL. Get a comprehensive, AI-researched marketing plan in minutes. No signup, no credit card, completely free.

Once your plan is ready, use our other free tools to execute: check your AI Brand Visibility to understand your current position, find Lookalike Companies for your target accounts, or use the AI Lead Generator to find buyer contacts at your target companies.

Demandbase doesn't publish pricing on its website. Instead, you get a "Fill out the form, and we'll customize a pricing plan" message. For busy sales leaders evaluating ABM platforms, that's frustrating.

We dug into Vendr contract data, G2 user reports, and third-party analyses to give you the real numbers. Here's what Demandbase actually costs in 2026 — and the hidden fees most vendors won't mention upfront.

Demandbase Pricing at a Glance​

Vendr median: ~$65,000/year across all company sizes.

That's not a typo. The median Demandbase contract is $65K/year. For context, MarketBetter gives you visitor identification, AI-powered playbooks, smart dialer, email automation, and AI chatbot — starting at a fraction of that price.

How Demandbase Pricing Works​

Demandbase uses a hybrid pricing model with three components:

1. Platform Fee​

A base cost covering software infrastructure and core services. This alone can run $15,000–$25,000/year for smaller deployments.

2. Per-User Licensing​

Flat fee per user (both Sales and Marketing seats count). Based on user reports, expect $1,500–$3,000 per user annually depending on your tier.

3. Module Add-Ons​

Demandbase One is modular. Each capability adds cost:

• ABM Marketing — Account identification, web personalization, campaign orchestration
• Sales Intelligence (formerly InsideView) — Buying group identification, contact data
• Advertising DSP — B2B display ads targeted to accounts (often billed separately with minimum ad spend)
• Data & AI — Intent signals, predictive analytics, firmographic/technographic data

Demandbase Pricing Tiers (Estimated)​

While not officially published, third-party sources and user reports point to three internal tiers:

Basic (~$24,000/year)​

• Core ABM functionality
• Limited intent data
• Restricted integrations
• Basic account identification
• Best for: Small teams testing ABM

Professional (~$60,000/year)​

• Advanced intent data
• Personalized advertising
• Major CRM/MAP integrations (Salesforce, HubSpot)
• Mid-market tier with standard suite
• Best for: Growing companies with dedicated ABM programs

Enterprise ($70,000 – $300,000+/year)​

• Complete Demandbase One suite
• All modules unlocked
• Dedicated Customer Success Manager
• Unlimited data access
• Custom integrations and professional services
• Best for: Large enterprises running multi-channel ABM at scale

The Hidden Costs Nobody Mentions​

Demandbase's sticker price is just the beginning. Here's what catches teams off guard:

Advertising Minimums​

The B2B DSP (display advertising) often requires minimum ad spend on top of the platform fee. Users report minimums of $5,000–$10,000/month for meaningful ad campaigns.

Professional Services​

Implementation, training, and custom integration work are frequently billed separately. Expect $5,000–$15,000 for initial setup depending on complexity.

Overages​

Exceed your data volume, tracked accounts, or ad impressions? Additional charges apply. Several users on G2 mention surprise overage bills they didn't anticipate.

Long Contract Lock-Ins​

Demandbase typically requires annual or multi-year contracts. There's no monthly option, and early termination usually isn't possible without paying out the remaining term.

No Free Trial​

Unlike tools such as Apollo (free tier), Clay (free credits), or MarketBetter (demo available), Demandbase offers no way to test the platform before committing $18K+ annually.

What You Actually Get for the Money​

Demandbase One consolidates several acquired products (Engagio, InsideView, DemandMatrix) into a unified platform:

Account Identification

• Anonymous web visitor identification (company-level)
• Reverse IP lookup
• Account scoring

Contact Database

• 150M+ professional contacts
• 99M+ companies
• Firmographic and technographic data

Intent Data

• First, second, and third-party intent signals
• Predictive analytics (Pipeline Predict AI)
• Real-time engagement scoring

Advertising

• B2B DSP for account-targeted display ads
• Retargeting on target accounts
• Cross-device targeting

CRM Integration

• Salesforce and HubSpot connectors
• Bidirectional sync

Demandbase vs. MarketBetter: Cost Comparison​

The fundamental difference: Demandbase tells you WHO is interested. MarketBetter tells you WHO is interested AND exactly what to do about it — with a daily playbook, smart dialer, email sequences, and AI chatbot all in one platform.

Demandbase gives you data to analyze. MarketBetter gives you actions to execute.

Who Should Actually Buy Demandbase?​

Demandbase makes sense if you:

• Have $50K+ annual budget for ABM tooling alone
• Run sophisticated, multi-channel ABM campaigns
• Need B2B display advertising (their DSP is genuinely unique)
• Have a dedicated ABM team to manage the platform
• Sell to enterprise accounts with $100K+ deal sizes

Demandbase is overkill if you:

• Have fewer than 500 target accounts
• Need SDR workflow automation (playbooks, dialer, email)
• Want quick time-to-value (Demandbase takes weeks to implement)
• Prefer transparent, predictable pricing
• Need person-level visitor identification (Demandbase is company-level only)

Better Alternatives to Demandbase for SDR Teams​

If you're evaluating Demandbase but primarily need SDR productivity tools rather than enterprise ABM orchestration, consider:

1. MarketBetter — Visitor ID + daily SDR playbook + smart dialer + email automation in one platform
2. 6sense — Strong intent data, similar enterprise pricing ($30K–$200K+/year)
3. Apollo — More affordable ($49–$119/user/month), good for smaller teams
4. ZoomInfo — Contact data powerhouse ($15K–$100K+/year)
5. Warmly — Website visitor intelligence with sales automation

The Bottom Line​

Demandbase is a powerful enterprise ABM platform — but it's priced like one. The Vendr median of $65K/year puts it out of reach for most mid-market companies, and the modular pricing means you could easily spend $100K+ to get the full suite.

For SDR teams that need to identify website visitors, prioritize outreach, and execute multi-channel sequences, MarketBetter delivers more actionable value at a fraction of the cost. Instead of analyzing dashboards, your SDRs get a daily playbook that tells them exactly who to contact, how, and what to say.

Ready to see the difference? Book a demo of MarketBetter and see how we turn intent signals into booked meetings — without the $65K price tag.

Demandbase One is the Rolls-Royce of ABM platforms. It's beautifully engineered, packed with features, and priced accordingly. But is it actually worth the investment for your sales and marketing team?

We analyzed reviews from G2 (1,900+ reviews, 4.4/5 rating), TrustRadius, Capterra, Gartner Peer Insights, and Reddit to give you an honest picture of what it's like to actually use Demandbase — not what the sales deck promises.

Quick Verdict​

Best for: Enterprise companies ($50K+ ABM budget) running multi-channel account-based programs with dedicated ABM teams.

Not ideal for: SMBs, SDR-heavy teams that need workflow automation, or companies that want quick time-to-value.

What Is Demandbase One?​

Demandbase One is a B2B go-to-market platform built around Account-Based Marketing (ABM). It's the result of combining several acquisitions — Engagio (ABM orchestration), InsideView (sales intelligence), and DemandMatrix (technographic data) — into a single platform.

The platform serves three primary functions:

1. Identify high-value accounts through intent data and AI scoring
2. Engage those accounts through personalized ads, web experiences, and content
3. Measure the impact of ABM campaigns on pipeline and revenue

What Users Love About Demandbase​

1. Intent Data That Actually Works​

Demandbase's intent data is consistently praised as one of the best in the industry. The platform combines first-party signals (who's visiting your website) with third-party intent data to identify accounts actively researching your category.

"The intent data is incredibly valuable. We can see which accounts are surging on topics relevant to our solution before they ever fill out a form." — G2 reviewer

Users particularly value the Pipeline Predict AI, which scores accounts based on their likelihood to convert. Several reviewers report this feature alone has helped their teams focus on the right accounts instead of spraying outreach everywhere.

2. Exceptional Customer Support​

If there's one thing virtually every Demandbase reviewer agrees on, it's the support. Dedicated Customer Success Managers get consistently high marks.

"Our assigned Senior Technical Consultant has been crucial for the success of our ABM program." — G2 reviewer

This is important because Demandbase is complex. Having a responsive CSM who understands your use case makes the difference between success and an expensive shelf-ware purchase.

3. Salesforce Integration Depth​

The Salesforce integration goes deep — far beyond basic data sync. Users praise the ability to:

• Push intent scores directly into Salesforce
• Create custom fields and dashboard views
• Sync account engagement data bidirectionally
• Build custom reports combining Demandbase signals with Salesforce pipeline data

"As a Salesforce administrator, I love the SFDC integration. But I also love the UI of the tool itself — custom tags, fields, and dashboard/report views." — Capterra reviewer

4. B2B Advertising DSP​

Demandbase is one of the only platforms with a native B2B Demand-Side Platform (DSP) for display advertising. This lets you serve targeted ads to specific accounts across the web, not just on LinkedIn.

For enterprise ABM teams running always-on advertising to target account lists, this is genuinely differentiated. Competitors like 6sense and ZoomInfo have advertising capabilities, but Demandbase's DSP is considered more mature.

5. Comprehensive Account Intelligence​

The combination of firmographic, technographic, and intent data gives a complete picture of each target account. Users appreciate being able to see:

• What technologies an account uses
• Whether they're growing or contracting
• What topics they're researching
• Which stakeholders are engaging with your content

Where Demandbase Falls Short​

1. Pricing Opacity​

This is the #1 complaint. Demandbase doesn't publish pricing, requires a sales cycle to get a quote, and contracts typically start at $18K/year with a median of $65K/year (per Vendr data).

"The pricing model is completely opaque. We had to go through a 6-week sales process just to understand what we'd be paying." — G2 reviewer

For teams that want to quickly evaluate whether a tool fits their budget, this is a dealbreaker. And once you're locked in, annual contracts make it hard to walk away if the platform isn't delivering.

2. Steep Learning Curve​

Demandbase is powerful, but that power comes with complexity. Multiple reviewers mention it takes weeks or months to fully utilize the platform.

"There's a learning curve. It took our team about two months to really feel comfortable with all the features and build the right dashboards." — TrustRadius reviewer

This is especially problematic for smaller teams that don't have a dedicated ABM manager to own the platform. If you're an SDR leader who needs tools that work on day one, Demandbase requires significant upfront investment.

3. Company-Level Only (No Person-Level Visitor ID)​

A critical limitation: Demandbase identifies companies visiting your website, not individual people. You'll know "someone from Acme Corp visited your pricing page" but not who specifically.

This matters because SDR follow-up is vastly more effective when you can reach out to the specific person who showed interest. Tools like MarketBetter provide person-level identification, enabling personalized outreach to actual decision-makers rather than generic account-based approaches.

4. Poor Acquisitions Created Technical Debt​

Glassdoor reviews from former employees paint a concerning picture: the aggressive acquisition strategy (Engagio, InsideView, DemandMatrix) left Demandbase with significant technical debt. Users occasionally experience:

• Inconsistent UX across different modules
• Features that feel bolted-on rather than integrated
• Occasional performance issues with large data sets

5. ABM Without Execution​

Here's the fundamental problem: Demandbase is excellent at telling you who to target. But it doesn't help you actually do anything about it.

There's no built-in:

• Smart dialer for calling identified accounts
• Email sequence automation
• AI chatbot for website visitors
• Daily SDR playbook with prioritized actions

You identify accounts showing intent, and then... you need to open a separate tool to actually reach them. That gap between insight and action is where deals get lost.

Demandbase vs. Alternatives: Honest Comparison​

Who Should Buy Demandbase?​

✅ Great Fit​

• Enterprise companies with $50K+ annual ABM budget
• Teams with dedicated ABM managers/strategists
• Companies that need B2B display advertising at scale
• Salesforce-centric organizations
• Deal sizes >$100K where ABM ROI justifies the cost

❌ Poor Fit​

• Mid-market teams with limited ABM budgets
• SDR-heavy organizations that need workflow automation
• Companies that want person-level visitor identification
• Teams without Salesforce (HubSpot integration is less robust)
• Startups or growth-stage companies that need fast time-to-value

The Real Question: Data Platform or Execution Platform?​

Demandbase excels as a data and intelligence platform. It tells you which accounts matter, what they're researching, and when they're in-market.

But modern B2B selling requires more than data. Your SDRs need to know:

• Who to contact (specific person, not just company)
• What to say (personalized messaging)
• When to reach out (timing based on intent signals)
• How to reach them (email, phone, chat — all in one workflow)

That's where platforms like MarketBetter take a different approach. Instead of giving you a dashboard full of data, MarketBetter delivers a daily SDR playbook — a prioritized list of exactly who to contact, through which channel, with suggested messaging based on their activity.

The result: your SDRs spend less time analyzing dashboards and more time having conversations with interested buyers.

Bottom Line​

Demandbase is a legitimate enterprise ABM platform with strong intent data, a unique advertising DSP, and excellent customer support. If you have the budget ($65K+ median annual contract), the team to manage it, and enterprise accounts that justify the investment, it delivers real value.

But for most mid-market B2B companies — especially those with SDR teams that need to move fast — Demandbase is more platform than you need. You'll pay enterprise prices for data intelligence when what your team actually needs is an execution engine that turns signals into conversations.

Want to see what SDR execution looks like? Book a MarketBetter demo and experience the difference between analyzing accounts and actually booking meetings.

Here's a question every marketer should be asking in 2026: What does ChatGPT say when someone asks about your company?

Not Google. Not Bing. ChatGPT. Gemini. Claude. Perplexity.

Over 400 million people use ChatGPT weekly as of early 2026. Millions more use Gemini, Claude, and Perplexity as their primary research tools. When a potential buyer asks an AI model "What's the best CRM for small businesses?" or "Who are the top B2B sales tools?" — your brand either shows up in that answer, or it doesn't.

And unlike Google, where you can check your ranking by searching yourself, you can't easily monitor what AI models say about your brand. The responses change based on context, conversation history, and model updates. What ChatGPT said last month might be completely different from what it says today.

This is the new SEO. And most companies are flying blind.

Why AI Brand Visibility Matters​

The Shift from Search to AI Answers​

Traditional SEO focused on ranking in Google's blue links. Then featured snippets changed the game. Now, AI-powered answer engines are changing it again.

When someone asks ChatGPT "What are the best project management tools?", they get a curated list with explanations — not 10 blue links to click through. If your brand isn't in that AI-generated answer, you're invisible to a growing segment of your audience.

Key stats:

• ChatGPT handles over 1 billion queries per week (OpenAI, January 2026)
• 65% of ChatGPT users report using it to research products and services before buying (Forrester, 2025)
• Perplexity processes 25M+ queries daily, up from 10M in early 2025
• Google AI Overviews now appear on 30%+ of search results pages

What This Means for Your Business​

1. Lost discovery opportunities — If AI models don't mention your brand when users ask relevant questions, you're losing potential customers to competitors who do appear.

2. Reputation you can't control — AI models may describe your company inaccurately, mention outdated information, or position you unfavorably compared to competitors. If you don't know what they're saying, you can't fix it.

3. Competitive blind spots — Your competitors might be showing up in AI answers for your core keywords while you're not. Traditional SEO rank tracking won't catch this.

4. Content strategy gaps — If AI models consistently recommend competitors for certain queries, it reveals gaps in your content and authority that you need to address.

How AI Models Decide What to Say About Your Brand​

Understanding how LLMs form opinions about brands helps you influence them. Here's what matters:

Training Data​

AI models are trained on massive datasets of web content. If your brand appears frequently in authoritative sources — industry publications, review sites, news articles, blog posts — the model is more likely to mention you in relevant contexts.

Recency and Authority​

Models like ChatGPT (with web browsing enabled), Perplexity, and Gemini pull from recent sources. Having fresh, authoritative content about your brand increases your chances of being mentioned.

Semantic Association​

LLMs understand concepts, not just keywords. If your brand is consistently associated with specific solutions (e.g., "MarketBetter" + "sales intelligence" + "B2B"), the model builds that semantic connection and surfaces it in relevant queries.

Reviews and Third-Party Mentions​

G2 reviews, Capterra listings, Reddit discussions, and industry analyst reports all contribute to how AI models perceive and describe your brand. First-party content alone isn't enough.

Structured Data and Content Architecture​

Well-structured content (schema markup, clear headings, definitive statements like "X is a platform that does Y") makes it easier for AI models to extract and cite information about your brand.

How to Check Your AI Brand Visibility​

The Manual Method (Time-Consuming)​

You can manually check by:

1. Opening ChatGPT, Gemini, Claude, and Perplexity
2. Asking questions your target audience would ask (e.g., "What are the best [your category] tools?")
3. Checking if your brand appears in the responses
4. Documenting the results
5. Repeating weekly to track changes

Problems with this approach:

• AI responses vary by conversation context, so you might get different answers each time
• Checking across 4+ AI platforms manually is tedious
• No way to track trends over time
• You'll inevitably miss important queries you should be monitoring

The Automated Method (What Tools Exist)​

Several paid tools have emerged to address this:

• Otterly.ai — Tracks brand visibility across ChatGPT, Perplexity, and Google AI Overviews. Starts at ~$29/month.
• SE Ranking Visible — ChatGPT visibility tracking integrated with their SEO platform. Plans from $65/month.
• Profound — AI search optimization platform with real-time visibility monitoring. Enterprise pricing.
• Frase AI Visibility — Multi-platform tracking for ChatGPT, Gemini, Perplexity, and Claude. Part of Frase's content platform.
• GenRank — Tracks brand mentions and citations in ChatGPT responses. Newer tool.
• AIclicks — AI search optimization and visibility tool for ChatGPT, Perplexity, and Gemini.

Most of these tools are aimed at enterprise SEO teams with monthly budgets of $100-$1,000+.

The Free Method: MarketBetter AI Brand Visibility​

MarketBetter's AI Brand Visibility tool lets you check what AI models say about your brand — completely free.

How it works:

1. Enter your company name or brand
2. The tool queries multiple AI models with the types of questions your target audience would ask
3. You get a clear report showing:
   • Whether AI models mention your brand
   • How your brand is described and positioned
   • Which competitors appear alongside you
   • The sentiment and accuracy of mentions
   • Recommendations for improving your AI visibility

Why it's different from the paid alternatives:

• Free — no signup required, no credit card
• Instant results — see what AI says about your brand in seconds
• Actionable insights — not just raw data, but specific recommendations
• Multi-model coverage — checks across major AI platforms

How to Improve Your AI Brand Visibility​

Once you know where you stand, here's how to improve:

1. Create Definitive, Authoritative Content​

AI models prefer clear, authoritative statements. Instead of vague marketing copy, publish content that definitively describes what you do:

Weak: "We help companies grow with innovative solutions." Strong: "MarketBetter is a B2B sales intelligence platform that tracks job changes, identifies website visitors, and automates personalized outreach."

2. Get Listed on Review Sites​

G2, Capterra, TrustRadius, and similar platforms are heavily referenced by AI models. If you have fewer than 10 reviews on major platforms, that's your biggest gap.

Action items:

• Create profiles on G2, Capterra, and TrustRadius
• Ask 10-20 customers to leave honest reviews
• Respond to every review (positive and negative)
• Keep your product descriptions current

3. Earn Third-Party Coverage​

AI models weight third-party mentions heavily. Being mentioned in:

• Industry publications (TechCrunch, SaaStr, etc.)
• Comparison articles on other blogs
• Podcast transcripts
• Reddit and community discussions

...all contribute to your brand's AI visibility.

4. Publish Comparison and "Best Of" Content​

AI models frequently reference "best of" and comparison content. Publishing your own comparisons (honestly, including competitors) helps models understand where your brand fits in the landscape.

5. Use Schema Markup and Structured Data​

Help AI models understand your brand by implementing:

• Organization schema on your homepage
• Product schema on feature pages
• FAQ schema on relevant pages
• Review/rating schema where applicable

6. Monitor and Iterate​

AI brand visibility isn't a one-time fix. Models update regularly, competitors publish new content, and the AI landscape evolves. Check your visibility monthly and adjust your strategy.

What Queries Should You Monitor?​

Focus on the queries your buyers actually ask:

Category Queries​

• "What are the best [your category] tools?"
• "Top [your category] platforms in 2026"
• "Best free [your category] tools"

Comparison Queries​

• "[Your brand] vs [competitor]"
• "[Competitor] alternatives"
• "Is [your brand] good?"

Solution Queries​

• "How to [solve the problem your product addresses]"
• "Best way to [accomplish the task your product helps with]"
• "Tools for [your use case]"

Brand Queries​

• "What is [your brand]?"
• "What does [your brand] do?"
• "[Your brand] pricing"
• "[Your brand] reviews"

The Future of AI Brand Visibility​

This space is evolving fast. Here's what's coming:

• AI-powered ads — OpenAI, Google, and others are experimenting with sponsored placements in AI responses. If you're not visible organically now, you'll be paying for visibility later.
• Citation-based ranking — As AI models add more citations to their responses, the quality and quantity of sources mentioning your brand becomes even more important.
• Real-time brand monitoring — Tools will evolve to alert you when AI model responses about your brand change, similar to Google Alerts but for AI.
• AI SEO as a discipline — Just as SEO became a core marketing function, "AI SEO" or "LLM optimization" is becoming its own discipline with dedicated roles and budgets.

Start Checking Your AI Brand Visibility Now​

The first step is knowing where you stand. Most companies have never checked what AI models say about them — and many are surprised (often unpleasantly) when they do.

Try MarketBetter's free AI Brand Visibility tool →

Enter your brand name, see what AI thinks about you, and get actionable recommendations for improving your visibility. No signup required.

Want to take action on what you learn? Use our Tech Stack Detector to research competitors' technology, or generate a full AI Marketing Plan to improve your brand's online presence.

Your best customer — the one that closed fast, expanded twice, and has never complained — is not unique. There are hundreds, maybe thousands of companies that look just like them: same industry, similar size, comparable tech stack, facing the same problems.

If you could find those companies systematically, you'd have the most productive prospect list in your entire pipeline.

That's the idea behind lookalike company finding: start with your best customers, identify what makes them great, and find more companies that match. It's how Facebook Ads (now Meta) revolutionized advertising — and it works just as well for B2B sales prospecting.

Yet most B2B sales teams still build prospect lists the old way: filtering by industry and company size in a database, then hoping for the best. It's a blunt instrument. You end up with thousands of "technically-fit" companies, most of which will never buy.

This guide explains how lookalike modeling works for B2B sales, compares the tools available, and shows you how to find companies similar to your best customers — starting for free.

What Is Lookalike Company Finding?​

Lookalike company finding is the process of identifying companies that share key characteristics with your existing customers — particularly your best customers.

Instead of defining your ideal customer profile (ICP) from scratch using industry, size, and location filters, you let the data tell you what your best customers have in common. Then you find more companies that match those patterns.

How It Differs from Traditional Prospecting​

Traditional approach:

1. Define ICP manually (e.g., "SaaS companies, 50-500 employees, US-based")
2. Search a database with those filters
3. Get 10,000+ results
4. Manually sort through to find the good ones
5. Discover that most don't respond because the targeting was too broad

Lookalike approach:

1. Start with 10-20 of your best customers
2. AI analyzes what they have in common (beyond obvious firmographics)
3. Get a ranked list of companies that match, sorted by similarity score
4. Focus outreach on the highest-similarity matches
5. Get dramatically higher response and close rates

The difference is signal density. Traditional filters are binary (yes/no on each criteria). Lookalike models consider dozens of weighted attributes simultaneously, producing a similarity score that tells you exactly how closely a prospect resembles your best customers.

What Makes a Good Lookalike Model?​

Not all lookalike tools are created equal. The best ones consider these dimensions:

1. Firmographics (The Basics)​

• Industry and sub-industry (NAICS/SIC codes)
• Company size (employees, revenue)
• Location (HQ, offices)
• Founding year and growth stage

2. Technographics (What They Use)​

• Technology stack (CRM, marketing automation, analytics)
• Development frameworks and infrastructure
• SaaS tools and integrations

3. Business Model Similarity​

• Revenue model (SaaS, marketplace, services)
• Customer type (B2B, B2C, B2B2C)
• Sales motion (PLG, enterprise sales, channel)

4. Growth Signals​

• Hiring velocity (especially in relevant departments)
• Funding history and stage
• Recent news and expansions

5. Digital Presence​

• Website traffic and engagement
• Content marketing activity
• Social media presence

6. Buying Behavior Indicators​

• Previous technology purchases
• Conference attendance
• Content consumption patterns

The more dimensions a tool considers, the more accurate the lookalike matches will be.

Tools for Finding Lookalike Companies​

MarketBetter Lookalike Company Finder (Best Free Option)​

Website: tools.marketbetter.ai/lookalike-finder

How it works:

1. Enter the name or URL of your best customer
2. AI analyzes the company across multiple dimensions (industry, size, tech stack, business model, growth signals)
3. Get a ranked list of similar companies with similarity scores
4. Export results for outreach

Pricing: Completely free. No signup required.

Why it stands out:

• Zero friction — paste a company name or URL, get results instantly
• AI-powered matching — considers more than just industry and size
• Similarity scoring — ranked results so you know which prospects are closest to your ICP
• Free and unlimited for individual lookups
• Actionable output — results you can immediately use for prospecting

Best for: Sales reps, founders, and small teams who want to quickly find companies similar to their best customers without paying for expensive data platforms.

Instantly (SuperSearch)​

Website: instantly.ai

Instantly's SuperSearch feature includes lookalike company discovery as part of their outreach platform.

How it works: Upload your best customer domains, set filters (industry, size, location), and get similar companies ranked by fit.

Pricing: Free trial available; paid plans from $30/month (outreach), data add-ons extra

Pros: Integrated with email outreach platform, verified contacts included, good UI Cons: Lookalike is part of a larger platform — can't use it standalone, data credits have limits

La Growth Machine​

Website: lagrowthmachine.com

LGM's Lookalike Search lets you enter a company URL and get companies ranked by similarity score.

How it works: Enter a company URL, apply filters (industry, company size, location), browse results ranked by similarity.

Pricing: Plans from €50/month (includes outreach features)

Pros: Similarity scoring, integrated with LinkedIn outreach, good European coverage Cons: Can't use lookalike search without the full platform, limited free usage

Surfe​

Website: surfe.com

Surfe offers company search with smart lookalikes, integrated into their CRM-LinkedIn bridge.

How it works: Search from a database of 350M+ companies, with lookalike matching based on firmographic attributes.

Pricing: Free tier available; paid plans from $39/month

Pros: Large database, LinkedIn integration, CRM sync Cons: Lookalike is one feature among many, limited free tier

Coresignal​

Website: coresignal.com

Data provider offering a "Find Similar Companies" tool based on multiple firmographic and growth attributes.

How it works: Enter a company, get similar companies based on employee data, growth patterns, and firmographic matching.

Pricing: Enterprise/API pricing (contact for quotes)

Pros: Deep data (based on 700M+ professional profiles), growth signals, investor-grade data Cons: Enterprise-focused and expensive, not designed for individual sales reps

Clay​

Website: clay.com

Clay's enrichment platform can build lookalike lists using multiple data sources.

How it works: Import your customer list, use Clay's 75+ enrichment sources to find patterns, then search for similar companies.

Pricing: Free tier (100 credits/month); paid plans from $134/month

Pros: Extremely flexible, combines multiple data sources, customizable scoring Cons: Requires setup and configuration, not a one-click solution, credits-based pricing adds up fast

Apollo.io​

Website: apollo.io

Apollo's database of 275M+ contacts includes company search with advanced filters.

How it works: Search companies by industry, size, technology, and other attributes. No native "lookalike" feature, but you can replicate it by analyzing best customers and applying similar filters.

Pricing: Free tier (unlimited emails, limited features); paid from $49/user/month

Pros: Large database, includes contact data, integrated outreach Cons: No true lookalike search — you're manually building equivalent filter sets

How to Build Your Lookalike Prospect List (Step by Step)​

Step 1: Identify Your Seed Companies​

Start with 10-20 of your best customers. "Best" should mean:

• Fastest time to close — they bought without a long sales cycle
• Highest lifetime value — they expanded or renewed
• Lowest churn risk — they're actively using your product
• Best advocacy — they refer others or leave positive reviews

Don't include one-off wins or customers acquired through unusual channels (e.g., a personal connection). You want customers who bought because of genuine fit.

Step 2: Analyze What They Have in Common​

Look beyond the obvious. Yes, they might all be "mid-market SaaS companies," but dig deeper:

• What specific sub-industry? (e.g., not just "SaaS" but "vertical SaaS for healthcare")
• What growth stage? (Series A? Series C? Bootstrapped?)
• What tech stack? Use MarketBetter's Tech Stack Detector to check
• What departments are growing? (Hiring SDRs? Building a marketing team?)
• How do they sell? (PLG? Enterprise? Channel?)

Document the 5-10 attributes that your best customers share. This is your real ICP — not the one your VP of Sales wrote on a whiteboard, but the one validated by actual buying behavior.

Step 3: Run the Lookalike Search​

Enter your seed companies into MarketBetter's Lookalike Company Finder. Review the results, paying attention to:

• Similarity scores — higher is better, but don't ignore medium-similarity companies entirely
• Companies you recognize — if the tool surfaces companies you already know are good fits but haven't prospected, that's validation the model is working
• Surprises — companies you wouldn't have found through traditional filtering are where the real value lives

Step 4: Enrich and Qualify​

For your top lookalike matches, add additional qualifying data:

• Contacts: Use the AI Lead Generator to find buyer contacts
• Tech stack: Verify technology fit with the Tech Stack Detector
• Recent signals: Check for hiring, funding, product launches, or conference attendance

Step 5: Prioritize and Sequence​

Rank your final list by:

1. Similarity score (highest first)
2. Timing signals (recently raised funding, hiring relevant roles)
3. Accessibility (do you have a warm connection? Are they in your territory?)

Then build your outreach sequences — starting with the highest-priority accounts.

Why Lookalike Prospecting Outperforms Traditional Targeting​

The numbers speak for themselves:

• 2-3x higher response rates compared to broadly-filtered cold outreach (Instantly customer data, 2025)
• 40% shorter sales cycles when prospects closely match your ICP (Gong Labs research)
• 30% higher win rates on ICP-matched deals (TOPO/Gartner research)

This makes intuitive sense: if your best customer is a Series B vertical SaaS company with 100-300 employees using HubSpot and Intercom, and you find another company with those exact characteristics, your pitch is already battle-tested. You know the pain points, the objections, and the value proposition that works.

Common Mistakes in Lookalike Prospecting​

1. Using Too Few Seed Companies​

With only 2-3 seeds, the model can't identify meaningful patterns. Use 10-20 for reliable results.

2. Including Bad Customers as Seeds​

That enterprise customer who churned after 3 months? Don't use them as a seed. You want to find more companies like your best customers, not your worst ones.

3. Ignoring the Similarity Scores​

Not all lookalikes are equal. A company with 95% similarity is fundamentally different from one with 60% similarity. Prioritize accordingly.

4. Skipping Enrichment​

Lookalike data tells you which companies to target. You still need to find the right people at those companies, understand their current situation, and personalize your outreach.

5. Set-and-Forget Mentality​

Your ICP evolves as you close more deals and learn what works. Re-run your lookalike analysis quarterly with updated seed lists.

Get Started: Find Your Lookalike Companies​

The fastest way to build a high-quality prospect list is to start with what's already working and find more of it.

Try MarketBetter's free Lookalike Company Finder →

Enter your best customer's name or URL, and get a ranked list of similar companies in seconds. No signup required, completely free.

Found companies you want to prospect? Use our AI Lead Generator to find buyer contacts, or check their Tech Stack to qualify by technology fit. Need help with outreach? The GiftDM Copilot creates personalized gifts and LinkedIn messages for your top prospects.

It's Tuesday morning. Your sales team is prepping for the biggest trade show of the year. You need a list of every exhibitor, speaker, and sponsor — with company names, booth numbers, descriptions, and ideally contact info — so you can prioritize who to visit and who to prospect before the event.

You go to the conference website. The exhibitor list is there: 400+ companies spread across an interactive floor plan with infinite scroll, lazy-loaded cards, and no export button.

So you start copying and pasting.

Company name. Tab. Description. Tab. Website. Tab. Next company. Repeat 400 times.

This is the reality for thousands of SDRs, AEs, and marketing teams every year. Conference and trade show websites are designed for attendees to browse — not for sales teams to extract. The data is right there, but getting it into a usable format (a spreadsheet, a CSV, your CRM) is absurdly painful.

There's a better way.

Why Conference Lists Are Gold for Sales Teams​

Conference exhibitor, speaker, and sponsor lists are among the highest-quality prospecting sources available:

1. Pre-Qualified by Budget​

Companies that pay $5,000-$50,000+ for a booth at a trade show have budget. They're investing in growth. That's a buying signal you can't get from a cold database.

2. Industry-Specific Targeting​

A cybersecurity conference exhibitor list is a curated list of cybersecurity companies. A SaaS conference speaker list is a roster of SaaS leaders. No filtering required — the conference organizer already did it for you.

3. Timely and Relevant​

Conference lists are current. These companies are actively participating in industry events right now, which means they're engaged, investing, and accessible.

4. Multi-Stakeholder Data​

Speaker lists give you names of decision-makers. Exhibitor lists give you company profiles. Sponsor lists tell you who has the biggest budgets. Combined, it's a complete prospecting package.

5. Pre-Event Outreach Advantage​

The most successful conference prospecting happens before the event. If you can email or LinkedIn-message an exhibitor before the show with "I saw you're exhibiting at [event] — I'll be at Booth 342, would love to connect," your meeting rate goes through the roof.

The Pain of Manual Conference Data Extraction​

Let's be honest about what manual extraction looks like:

Time cost: A typical conference with 300 exhibitors takes 4-6 hours to manually copy into a spreadsheet. That's nearly a full working day.

Error rate: Copy-paste errors are inevitable. Company names get truncated, URLs get mangled, descriptions get partially captured.

Format inconsistency: Different conferences structure their data differently. Some have separate pages per exhibitor. Others use interactive maps. Others use accordion-style lists. Each requires a different manual approach.

Dynamic content problems: Many conference sites use JavaScript-heavy frameworks (React, Angular) that render exhibitor data dynamically. You can't even "View Source" to find the data — it's loaded asynchronously.

Repetitive across events: If your team attends 10+ events per year, you're burning 40-60 hours annually just copying exhibitor data. That's a full work week of pure drudgery.

Methods for Extracting Conference Data​

Method 1: Manual Copy-Paste (The Hard Way)​

Process: Open the conference website, manually select each exhibitor's name, description, and details, paste into a spreadsheet.

Pros: No tools required, works on any site Cons: Extremely time-consuming, error-prone, soul-crushing

Time per event: 4-8 hours for 300 exhibitors

Method 2: Browser Extensions (Semi-Automated)​

Tools like Instant Data Scraper (Chrome extension) can detect tables on web pages and export them.

Process: Install the extension, navigate to the exhibitor page, click the extension, hope it detects the right data, export to CSV.

Pros: Free, fast when it works Cons: Only works on simple HTML tables. Fails completely on dynamically-loaded content, interactive maps, and paginated lists. Captures lots of irrelevant data. Requires manual cleanup.

Success rate: Works on maybe 20% of conference websites. Most modern event sites use dynamic rendering that breaks these extensions.

Method 3: Custom Python Scripts (Technical)​

For developers, writing a custom scraper using libraries like Scrapy, BeautifulSoup, or Playwright is an option.

Process: Inspect the conference website's HTML structure, write a Python script to extract the relevant elements, handle pagination and dynamic loading, export to CSV.

# Example: Scraping a simple exhibitor list with BeautifulSoup
import requests
from bs4 import BeautifulSoup

url = "https://example-conference.com/exhibitors"
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

exhibitors = []
for card in soup.find_all('div', class_='exhibitor-card'):
    name = card.find('h3').text.strip()
    desc = card.find('p', class_='description').text.strip()
    exhibitors.append({'name': name, 'description': desc})

Pros: Highly customizable, handles complex sites, can be reused Cons: Requires programming skills, breaks when site structure changes, needs to be rebuilt for each conference site, can take hours to debug JavaScript-rendered content

Time investment: 2-4 hours to write and debug per conference site

Method 4: Apify Actors (Platform-Dependent)​

Apify offers pre-built scrapers ("Actors") for specific conference platforms like Map Your Show, 10times, and Xporience.

Process: Find the right Actor for your conference platform, input the URL, run the scraper, download results.

Pros: Pre-built for specific platforms, handles dynamic content, outputs structured data Cons: Only works for supported platforms (many conference sites aren't covered), requires an Apify account, costs credits for large runs, doesn't work for custom-built conference websites

Pricing: Free tier includes some usage; paid plans from $49/month

Method 5: Web Scraping Services (Expensive)​

Companies like WebScrapingExpert and ScrapeHero offer custom scraping as a service.

Process: Submit the conference URL, they build a custom scraper, deliver results in 24-48 hours.

Pros: Hands-off, handles any site Cons: Expensive ($50-$500+ per project), slow turnaround, not practical for frequent use

Method 6: MarketBetter Conference Scraper (Free, Any Site)​

MarketBetter's Conference Scraper takes a completely different approach: paste any conference URL and get structured CSVs of speakers, exhibitors, and sponsors.

How it works:

1. Paste the conference website URL
2. The AI-powered scraper analyzes the site structure, navigates through exhibitor directories, speaker pages, and sponsor lists
3. You get downloadable CSVs with structured data: company names, descriptions, booth numbers, speaker names, titles, and topics

Why it's different:

• Works on any conference website — not limited to specific platforms like Map Your Show or Eventbrite
• AI-powered navigation — handles dynamic content, infinite scroll, paginated lists, and JavaScript-rendered pages
• Multiple data types — extracts speakers, exhibitors, AND sponsors in one pass
• Structured output — clean CSVs ready for import into your CRM or outreach tool
• Completely free — no account, no credits, no per-use charges

Time per event: 2-5 minutes (versus 4-8 hours manually)

The Conference Prospecting Workflow​

Here's the complete workflow for turning conference data into booked meetings:

Step 1: Extract the Data​

Use MarketBetter's Conference Scraper to pull exhibitor, speaker, and sponsor lists from your target conference.

Step 2: Enrich with Contact Data​

Conference lists give you company names, but you need individual contacts. Use tools like:

• MarketBetter AI Lead Generator — find buyer contacts at each company on LinkedIn
• Apollo.io — search for contacts by company and title
• LinkedIn Sales Navigator — find decision-makers at target companies

Step 3: Prioritize by Fit​

Not every exhibitor is a good prospect. Score your list by:

• Company size — do they fit your ICP?
• Industry fit — are they in your target vertical?
• Technology fit — use our Tech Stack Detector to check if they use compatible/competitive technology
• Sponsor level — Platinum sponsors have bigger budgets than basic exhibitors

Step 4: Pre-Event Outreach​

Reach out 2-4 weeks before the event:

Email template:

Hi [Name],

I noticed [Company] is exhibiting at [Conference] — we'll be there too.

[One sentence about what you do and why it's relevant to them]

Would love to grab 15 minutes at the event. Are you available on [day]?

LinkedIn message template:

Hey [Name], saw you're speaking at [Conference] on [topic]. Really looking forward to your session.

We work with companies like [similar company] on [relevant problem]. Would be great to connect while we're both there.

Step 5: At-Event Meetings​

With pre-scheduled meetings, your conference ROI multiplies. Instead of wandering the floor hoping for productive conversations, you arrive with a full calendar.

Step 6: Post-Event Follow-Up​

Within 48 hours of the event, follow up with everyone you met and everyone who didn't respond to pre-event outreach:

Great connecting at [Conference], [Name]. As discussed, [reference specific conversation point].

Here's [the resource/demo/proposal] I mentioned. Would [date] work for a follow-up call?

Real-World Example: SaaStr Annual​

Let's say your team is attending SaaStr Annual, one of the largest SaaS conferences with 300+ exhibitors and 200+ speakers.

Manual approach:

• Time to extract exhibitor list: ~6 hours
• Time to extract speaker list: ~3 hours
• Total data extraction: 9+ hours
• Result: One messy spreadsheet with inconsistent formatting

MarketBetter Conference Scraper approach:

• Paste the SaaStr exhibitor page URL
• Wait 3-5 minutes
• Download clean CSVs of exhibitors, speakers, and sponsors
• Total data extraction: 5 minutes
• Result: Three clean, structured CSVs ready for CRM import

Time saved: 8+ hours per event. Multiply that by 10 events per year, and you've reclaimed 80+ hours of productive selling time.

Tips for Effective Conference Prospecting​

Start Early​

The best conference prospecting starts 4-6 weeks before the event. Exhibitor lists are usually published 2-3 months in advance. Don't wait until the week before.

Focus on Speakers​

Conference speakers are typically senior leaders (VP+) who are active in the industry and open to networking. They're often higher-quality prospects than random booth visitors.

Layer Multiple Data Sources​

Combine conference data with:

• Lookalike Company Finder to find similar companies not at the conference
• Tech Stack Detector to qualify by technology fit
• LinkedIn to research individual contacts

Track Your Metrics​

Measure conference prospecting ROI:

• Pre-event emails sent
• Meetings booked before the event
• Meetings held at the event
• Deals generated from conference contacts
• Revenue attributed to conference prospecting

Get Started​

Stop manually copying exhibitor data from conference websites. Paste any conference URL into MarketBetter's free Conference Scraper and get structured CSVs of speakers, exhibitors, and sponsors in minutes.

Try the Conference Scraper free →

Once you have your conference list, use our AI Lead Generator to find buyer contacts at each company, or try the GiftDM Copilot to personalize outreach gifts for your top prospects.