I'm looking for a way to track marketing channel attribution. What's the best attribution software for a B2B sales cycle?

For a B2B sales cycle, I’d focus on platforms that connect marketing touchpoints to accounts, opportunities, pipeline, and closed revenue—not just lead or web conversions. That matters because B2B journeys can span months and involve multiple people at the same account.

The main options I’d evaluate

If I were narrowing the shortlist

For a typical B2B company with a 90+ day sales cycle, multiple stakeholders per deal, and Salesforce/HubSpot as the source of truth, I'd put HockeyStack and Dreamdata at the top of the evaluation list—not because one is universally "best," but because both are specifically designed around this type of revenue journey.

The distinction I'd investigate is:

• HockeyStack: more emphasis on flexible analytics, buyer journeys, customizable models, and faster self-service analysis.
• Dreamdata: particularly strong when you want a dedicated B2B revenue-attribution/data layer with deep account-level journey stitching and extensive integrations.
• Factors: interesting if attribution is only part of the problem and you also want ABM, intent, LinkedIn measurement, and activation in the same platform.

One important caveat: don't buy attribution software before fixing your measurement foundation. Clean CRM opportunity stages, consistent campaign taxonomy, UTM discipline, account/contact identity resolution, and reliable spend/revenue data will often matter more than whether the attribution model is linear vs. time-decay vs. position-based.

If you tell me your CRM (Salesforce/HubSpot/etc.), typical sales-cycle length, ACV, monthly ad spend, and main channels (Google/LinkedIn/content/events/outbound/etc.), I can narrow this to the 2–3 platforms that fit your setup and explain what I'd test in each demo.

Tracking B2B marketing attribution requires software built for account-based journeys, multiple decision-makers , and long sales cycles , rather than simple, transactional B2C tracking. Because a single B2B deal involves dozens of touches across different stakeholders over 3 to 12 months, standard web analytics fall short.

The best attribution software for a B2B sales cycle depends heavily on your existing tech stack and company size. Top solutions are organized below by their specific strengths:

• Dreamdata — Best Purpose-Built B2B Revenue Attribution
  • Why it shines: It is designed from the ground up for B2B SaaS and long sales cycles. It aggregates data across your entire go-to-market stack (CRM, marketing automation, product usage, and ad platforms) and maps it cleanly to company accounts rather than just individual leads.
  • Best for: Mid-market to enterprise B2B teams wanting an independent, crystal-clear view of pipeline generation.
• Adobe Marketo Measure (formerly Bizible) — Best for Enterprise & Complex Ecosystems
  • Why it shines: The heavyweight gold standard for massive enterprise operations. It tracks online, offline (events, direct mail), and sales/BDR touchpoints seamlessly, tying everything directly back to CRM opportunities.
  • Best for: Large enterprise organizations already operating within the Adobe/Salesforce ecosystem with deep technical resources.
• HubSpot Attribution Reporting — Best Native CRM Attribution
  • Why it shines: If your marketing and sales teams live entirely inside HubSpot's ecosystem, its built-in multi-touch attribution models require no complex third-party data stitching. It natively reports on how contacts and deals interact with content, ads, and emails.
  • Best for: Small-to-midmarket companies using HubSpot as their primary CRM and marketing hub.
• Salesforce Einstein Attribution — Best for Salesforce-Centric Enterprises
  • Why it shines: Leverages machine learning directly inside Salesforce to weight marketing campaigns based on closed-won account history.
  • Best for: Enterprise companies deeply embedded in Salesforce who want AI-driven credit distribution without adding external software.
• 6sense / Demandbase — Best for Intent Data + Attribution
  • Why it shines: These ABM powerhouses don't just track traditional marketing touches; they layer in anonymous account intent data to show which channels are warming up accounts before they even fill out a form.
  • Best for: Enterprise B2B companies running heavy Account-Based Marketing (ABM) strategies.

To help narrow down the ideal platform, let me know:

• What CRM and marketing automation platform are you currently using (e.g., HubSpot, Salesforce, Marketo)?
• Roughly how long is your average sales cycle?
• Are you tracking offline touches (like physical events or sales calls) alongside digital channels?

For a B2B sales cycle with multiple stakeholders and deals taking weeks/months, I’d shortlist:

• Dreamdata — strong account-level, multi-touch attribution and broad integrations; particularly suited to complex B2B journeys.
• HockeyStack — strong journey analytics, customizable attribution, and connecting marketing activity to pipeline/revenue.
• Factors.ai — good if you want attribution plus account intelligence and campaign optimization in one platform.
• Adobe Marketo Measure — worth considering if you're already heavily invested in Salesforce/Marketo.

My practical pick: start by evaluating Dreamdata vs. HockeyStack. The deciding factors are your CRM, sales-cycle length, number of stakeholders per deal, and whether you need sophisticated modeling or easier day-to-day reporting.

If you tell me CRM (Salesforce/HubSpot), monthly website traffic, typical sales-cycle length, and annual marketing spend, I can narrow it to 1–2 options.

Because B2B sales cycles are notoriously long, non-linear, and involve multiple decision-makers , traditional B2C last-click attribution falls completely flat. You need platforms built specifically for account-based multi-touch attribution (MTA) that can connect anonymous website visitors, multiple stakeholder touchpoints, and offline sales data directly to closed-won revenue in your CRM.

The top-rated B2B attribution software options on the market depend heavily on your tech stack, company size, and specific needs:

• Dreamdata : Built specifically for B2B revenue attribution. It excels at stitching together the entire customer journey across multiple touchpoints and accounts, making it a favorite for B2B SaaS and mid-to-enterprise companies wanting pure pipeline transparency.
• Adobe Marketo Measure (formerly Bizible): The gold standard for enterprise-grade organizations heavily embedded in the Adobe and Salesforce ecosystem. It embeds touchpoints directly into Salesforce at the account and opportunity level, keeping marketing and sales data completely unified.
• HockeyStack : A flexible B2B attribution and go-to-market (GTM) analytics platform. It stands out for its deep reporting capabilities, ease of connecting siloed data, and ability to visualize complex, multi-stakeholder buyer journeys without requiring an army of data engineers.
• Factors.ai : Combines B2B multi-touch attribution with account intelligence, intent signals, and anonymous website visitor identification. Great if you want to tie attribution directly to real-time account scoring and outbound/inbound advertising activation.
• HubSpot Attribution Analytics : Usually the first port of call if you are already using HubSpot as your CRM and Marketing Automation Platform. It provides robust multi-touch attribution models out-of-the-box for mid-market teams without requiring a separate third-party tool.

To help narrow down which tool fits your exact situation, tell me:

• What CRM and Marketing Automation platforms are you currently using (e.g., Salesforce, HubSpot, Marketo)?
• Roughly what is your monthly or annual ad spend / team size?
• Are you struggling more with paid media tracking or long-term account pipeline visibility?

B2B sales cycles are uniquely complex. They feature long time horizons, multi-stakeholder buying committees, and a mix of digital and offline touchpoints (like trade shows or sales calls). Standard B2C or last-touch attribution tools fall short because they can't stitch an entire account’s journey together over months of evaluation.

The best B2B attribution software depends heavily on your tech stack, company size, and budget. The top platforms leading the B2B space are structured by their ideal use cases:

• Adobe Marketo Measure (formerly Bizible) — Best for Enterprise / Salesforce & Marketo Ecosystems
  • How it works: It writes custom attribution objects directly into Salesforce, mapping touchpoints at the lead, contact, account, and opportunity levels natively.
  • Why it fits long cycles: It handles complex, multi-touch, full-path enterprise models exceptionally well.
  • The catch: Implementation can take weeks or months, and it requires a heavy investment in the Adobe/Salesforce ecosystem. Learn more on the Adobe Marketo Measure Overview.
• Dreamdata — Best for Mid-Market B2B & SaaS
  • How it works: Focuses heavily on account-level, B2B pipeline attribution and customer journey visualization. It aggregates data from your CRM, marketing automation, and product usage data.
  • Why it fits long cycles: Built specifically for sales cycles lasting 3+ months with multiple stakeholders, tracking the "dark funnel" and anonymous-to-known account transitions.
  • The catch: It provides a clean, independent revenue lens rather than writing data back into native CRM objects. Explore features via Dreamdata.
• HockeyStack — Best for Fast Implementation & GTM Analytics
  • How it works: Combines website behavior tracking, multi-touch attribution, and high-speed pipeline reporting into a single platform.
  • Why it fits long cycles: It syncs rapidly with your CRM and ad platforms, giving you flexible, customizable multi-touch attribution dashboards in days rather than months.
  • The catch: Similar to Dreamdata, it operates as a separate analytics/attribution layer rather than native CRM objects. Check out details at HockeyStack.

To help narrow down the best fit, tell me:

• What is your primary CRM and marketing automation stack (e.g., Salesforce, HubSpot)?
• Roughly how long is your average sales cycle (in months)?
• Do you need to track offline touchpoints like events and sales outbound?

For a B2B company with a sales cycle measured in weeks or months, I’d prioritize account-level, multi-touch revenue attribution over traditional web analytics. You want to connect marketing touches → buying committee → opportunity → closed revenue, not just measure form fills.

My shortlist

Recent 2026 comparisons consistently put Dreamdata and HockeyStack near the top for CRM-driven B2B revenue attribution, while SegmentStream is differentiated by incrementality/measurement capabilities.

🥇 I'd start with Dreamdata

The key reason is that B2B attribution needs to understand accounts and buying committees, not just individual leads. Dreamdata connects individual and account-level journeys and attributes marketing activity through to revenue.

That makes it particularly appropriate if your funnel looks something like:

Ad/content/event → anonymous visitor → several people from an account → MQL → opportunity → multiple sales interactions → closed-won

rather than:

Ad → click → ecommerce purchase

For example, if five people at Acme interact with your marketing before one becomes an opportunity, you don't want four of those people treated as unrelated conversions. Account-level attribution is designed to solve exactly that problem.

When I'd pick HockeyStack instead

I'd lean toward HockeyStack if you want attribution to be part of a broader GTM intelligence system—particularly if marketing, sales, and RevOps all need to explore buyer journeys and pipeline in the same interface.

It supports multiple attribution models and customizable rules, and its current positioning is more expansive than pure attribution.

One important warning

Don't choose based on the number of attribution models.

Having first-touch, last-touch, linear, W-shaped, time-decay, etc. sounds impressive, but the bigger determinant is whether the platform can reliably stitch identities and CRM revenue together.

I'd evaluate vendors on these five things:

1. Account-level identity resolution — can it connect multiple people to the same company?
2. CRM integration — can it follow an opportunity from creation through closed-won?
3. Offline touchpoints — events, sales activity, webinars, partner referrals, etc.
4. Pipeline/revenue attribution — can you report pipeline and revenue, not just leads?
5. Data transparency — can you understand why a deal received attribution?

That last point is especially important. A sophisticated model operating on poor identity data can be less useful than a simple model operating on clean data.

What I'd buy

If you told me nothing else about your stack, I'd shortlist Dreamdata vs. HockeyStack and run the same 20–50 historical closed deals through both.

If you tell me your CRM (Salesforce/HubSpot), average sales-cycle length, ACV, monthly marketing spend, and main channels (Google, LinkedIn, content, events, outbound, etc.), I can narrow this down to the best 1–2 options for your specific funnel and explain what I'd implement.

Ad/content/event → anonymous visitor → several people from an account → MQL → opportunity → multiple sales interactions → closed-won

rather than:

Ad → click → ecommerce purchase

For example, if five people at Acme interact with your marketing before one becomes an opportunity, you don't want four of those people treated as unrelated conversions. Account-level attribution is designed to solve exactly that problem.

When I'd pick HockeyStack instead

I'd lean toward HockeyStack if you want attribution to be part of a broader GTM intelligence system—particularly if marketing, sales, and RevOps all need to explore buyer journeys and pipeline in the same interface.

It supports multiple attribution models and customizable rules, and its current positioning is more expansive than pure attribution.

One important warning

Don't choose based on the number of attribution models.

If you have a B2B sales cycle with multiple stakeholders, weeks/months to close, and CRM-based pipeline, I’d prioritize a purpose-built B2B attribution platform over generic web analytics.

My shortlist

🥇 I'd start with HockeyStack

hockeystack.com is particularly strong for a B2B motion because it connects the anonymous website journey through identified accounts, marketing touches, sales activity, pipeline, and closed revenue. It supports multiple attribution models and lets you compare them rather than pretending there's one universally "correct" model.

It also has lift/incrementality reporting, which is important because attribution alone can tell you that two things happened in the same customer journey without proving that one caused the other.

Its currently published pricing starts at $1,400/month for Growth and $2,400/month for Scale, with enterprise functionality beyond that.

🥈 Dreamdata is the one I'd demo alongside it

dreamdata.io is very focused on the fundamental B2B attribution problem: joining marketing, sales, and customer data so you can connect individual touches and accounts to pipeline and revenue. It supports models including first-touch, last-touch, linear, U-shaped and W-shaped attribution.

I particularly like Dreamdata if your question is:

"Which channels and campaigns actually generated our pipeline and revenue?" rather than primarily:

"What happened across our entire GTM journey?" Dreamdata also emphasizes attribution at the account/revenue level, rather than treating a lead conversion as the endpoint.

When I'd pick Factors.ai

factors.ai is worth serious consideration if you're heavily invested in ABM, paid advertising, LinkedIn, and account-level engagement. It combines first-touch, last-touch, and influenced attribution and lets you analyze channels, campaigns, funnel stages, and content at the account level.

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The important part: don't optimize for "multi-touch"

For B2B, I'd make your attribution system answer four different questions:

1. Sourced pipeline — What initially created the opportunity?
2. Influenced pipeline — Which channels/programs participated in the journey?
3. Revenue attribution — Which activities deserve credit for closed-won revenue?
4. Incrementality — Would the deal have happened without the marketing activity?

The fourth is the hardest—and arguably the most valuable. A person might attend a webinar shortly before buying, but that doesn't mean the webinar caused the purchase.

I'd therefore avoid choosing software solely because it offers "7 attribution models." The underlying identity resolution, CRM integration, account-level tracking, offline touchpoints, and ability to connect activity to actual revenue matter much more.

My recommendation

If you told me nothing else about your company, I'd demo HockeyStack and Dreamdata side-by-side, with Factors.ai as the third demo if you're ABM-heavy.

And I'd judge them using your own last 20–50 closed-won deals, not a canned demo. Ask each vendor to show:

anonymous visitor → known person → account → marketing touches → sales touches → opportunity stages → closed revenue

If you tell me your CRM (HubSpot/Salesforce/etc.), average sales-cycle length, ACV, monthly marketing spend, and main channels (Google/LinkedIn/content/events/partners/etc.), I can narrow this down to the best 1–2 options for your specific funnel.

"Which channels and campaigns actually generated our pipeline and revenue?" rather than primarily:

"What happened across our entire GTM journey?" Dreamdata also emphasizes attribution at the account/revenue level, rather than treating a lead conversion as the endpoint.

When I'd pick Factors.ai

factors.ai is worth serious consideration if you're heavily invested in ABM, paid advertising, LinkedIn, and account-level engagement. It combines first-touch, last-touch, and influenced attribution and lets you analyze channels, campaigns, funnel stages, and content at the account level.

---

The important part: don't optimize for "multi-touch"

For B2B, I'd make your attribution system answer four different questions:

To track marketing channel attribution across a B2B sales cycle , you cannot rely on traditional e-commerce attribution tools. B2B attribution requires account-based tracking that can tie multiple stakeholders, offline sales pipelines, and long sales cycles (often 3 to 9 months) back to the original marketing touchpoints.

The best B2B attribution software platforms are grouped below by their core strengths to help you choose the right fit for your tech stack.

📊 Top B2B Attribution Platforms Compared

💡 Deep Dive: Which One Should You Choose?

➡️ Dreamdata: Best for Account-Based Journeys & Long Sales Cycles

In B2B, a single account might have 5 different people visiting your site before a demo is booked. Dreamdata excels because it merges fragmented individual data into a single company-level timeline.

• Why it works: It offers specialized B2B multi-touch models (like W-Shaped or Custom Data-Driven) that assign revenue value to the first touch, lead creation touch, and opportunity creation touch.
• The Catch: It can require clean CRM data to map effectively, meaning setup takes time.

➡️ HockeyStack: Best for GTM Customization & Speed

If you want to quickly build visual maps showing exactly how content or ads drive pipeline, HockeyStack is a top contender.

• Why it works: It integrates marketing, product usage (SaaS), and sales data without requiring complex code. You can answer questions like, "Did our LinkedIn ad campaigns lead to product activation?"
• The Catch: It is heavily focused on modern B2B SaaS setups and may not fit old-school enterprise hardware sales pipelines as natively as Marketo Measure.

➡️ Cometly: Best for Paid Media Optimization

If a large portion of your B2B pipeline comes from paid channels like LinkedIn Ads, Meta Ads, and Google Ads, Cometly is designed for this exact scenario.

• Why it works: Because of privacy updates and ad blockers, standard browser pixels miss data. Cometly uses server-side tracking and a cookieless pixel to bypass these blocks, sending clean customer data back to ad algorithms to optimize your cost per acquisition (CPA).
• The Catch: It is heavily weighted toward paid media attribution rather than purely organic, account-based intent data mapping.

➡️ CaliberMind: Best for Auditable ABM Reporting

For marketing teams that need to defend their budget numbers to the CFO or the board, CaliberMind is an excellent, underrated choice.

• Why it works: It provides a Salesforce-native platform that blends multi-touch attribution (MTA) with marketing mix modeling (MMM). Its calculations are open and clear, allowing you to trace numbers from raw data to the final dashboard.

⚠️ Hidden Costs and Implementation Pitfalls

Before buying any attribution platform, map out these three critical factors:

1. CRM Cleanliness: Attribution software only mirrors the state of your CRM. If your sales reps do not change deal stages accurately in Salesforce or HubSpot, your attribution models will fail.
2. The "Dark Social" Blindspot: No attribution software can track word-of-mouth, Slack groups, or organic podcasts cleanly. Combine your software with a self-reported attribution field on your forms (e.g., "How did you hear about us?").
3. Implementation Time: Expect a 30 to 90-day onboarding window to properly configure tracking scripts, integrate data warehouses, and validate the incoming data stream.

To help narrow down the perfect software option for your team, please let me know:

• What CRM and marketing automation platforms do you currently use? (e.g., HubSpot, Salesforce, Marketo)
• What are your primary marketing channels ? (e.g., LinkedIn Paid Ads, SEO/Content, Events, Cold Outbound)
• Roughly what is your annual or monthly ad spend?

To track marketing channel attribution across a B2B sales cycle , you cannot rely on traditional e-commerce attribution tools. B2B attribution requires account-based tracking that can tie multiple stakeholders, offline sales pipelines, and long sales cycles (often 3 to 9 months) back to the original marketing touchpoints.

The best B2B attribution software platforms are grouped below by their core strengths to help you choose the right fit for your tech stack.

📊 Top B2B Attribution Platforms Compared

💡 Deep Dive: Which One Should You Choose?

➡️ Dreamdata: Best for Account-Based Journeys & Long Sales Cycles

In B2B, a single account might have 5 different people visiting your site before a demo is booked. Dreamdata excels because it merges fragmented individual data into a single company-level timeline.

• Why it works: It offers specialized B2B multi-touch models (like W-Shaped or Custom Data-Driven) that assign revenue value to the first touch, lead creation touch, and opportunity creation touch.
• The Catch: It can require clean CRM data to map effectively, meaning setup takes time.

➡️ HockeyStack: Best for GTM Customization & Speed

If you want to quickly build visual maps showing exactly how content or ads drive pipeline, HockeyStack is a top contender.

• Why it works: It integrates marketing, product usage (SaaS), and sales data without requiring complex code. You can answer questions like, "Did our LinkedIn ad campaigns lead to product activation?"
• The Catch: It is heavily focused on modern B2B SaaS setups and may not fit old-school enterprise hardware sales pipelines as natively as Marketo Measure.

➡️ Cometly: Best for Paid Media Optimization

If a large portion of your B2B pipeline comes from paid channels like LinkedIn Ads, Meta Ads, and Google Ads, Cometly is designed for this exact scenario.

• Why it works: Because of privacy updates and ad blockers, standard browser pixels miss data. Cometly uses server-side tracking and a cookieless pixel to bypass these blocks, sending clean customer data back to ad algorithms to optimize your cost per acquisition (CPA).
• The Catch: It is heavily weighted toward paid media attribution rather than purely organic, account-based intent data mapping.

➡️ CaliberMind: Best for Auditable ABM Reporting

For marketing teams that need to defend their budget numbers to the CFO or the board, CaliberMind is an excellent, underrated choice.

• Why it works: It provides a Salesforce-native platform that blends multi-touch attribution (MTA) with marketing mix modeling (MMM). Its calculations are open and clear, allowing you to trace numbers from raw data to the final dashboard.

⚠️ Hidden Costs and Implementation Pitfalls

Before buying any attribution platform, map out these three critical factors:

1. CRM Cleanliness: Attribution software only mirrors the state of your CRM. If your sales reps do not change deal stages accurately in Salesforce or HubSpot, your attribution models will fail.
2. The "Dark Social" Blindspot: No attribution software can track word-of-mouth, Slack groups, or organic podcasts cleanly. Combine your software with a self-reported attribution field on your forms (e.g., "How did you hear about us?").
3. Implementation Time: Expect a 30 to 90-day onboarding window to properly configure tracking scripts, integrate data warehouses, and validate the incoming data stream.

To help narrow down the perfect software option for your team, please let me know:

• What CRM and marketing automation platforms do you currently use? (e.g., HubSpot, Salesforce, Marketo)
• What are your primary marketing channels ? (e.g., LinkedIn Paid Ads, SEO/Content, Events, Cold Outbound)
• Roughly what is your annual or monthly ad spend?

For a B2B sales cycle, I’d avoid basic web analytics attribution tools. You want something that can connect anonymous web activity → known people → accounts → opportunities → closed revenue, including multiple stakeholders and long sales cycles.

My shortlist

🥇 My pick: HockeyStack

For a new implementation today, I'd start with HockeyStack.

It is built around the actual B2B buyer journey and can connect marketing and sales data through closed-won revenue. It supports multiple attribution models and, importantly, has incrementality/lift analysis—which helps distinguish "this touchpoint was present in the journey" from "this marketing actually caused more conversions."

That's a significant distinction. Traditional multi-touch attribution can tell you:

LinkedIn → webinar → Google search → demo → opportunity → closed won But you ultimately want to know:

Did LinkedIn actually create pipeline, or were the people who saw those ads already going to buy? HockeyStack's incrementality capabilities are designed to address that second question.

🥈 Dreamdata

I'd look very closely at Dreamdata if your primary requirement is reliable B2B revenue attribution rather than the broader GTM intelligence functionality.

Its account-based approach is particularly relevant to B2B: instead of treating one browser/user as the customer, it can connect multiple stakeholders' journeys to the same account.

It also offers several attribution models—including linear, U-shaped, W-shaped and data-driven—so you can compare how different methodologies affect your conclusions.

🥉 Marketo Measure

If you're already running Salesforce + Marketo/Adobe, Marketo Measure is a very credible choice.

It supports first-touch, lead-creation, U-shaped, W-shaped, full-path and custom attribution models. Experience League Experience League It also handles online/offline interactions and can incorporate sales activities such as calls and emails.

The downside is that I'd be less inclined to introduce it from scratch into a modern B2B stack unless you're already invested in the Adobe ecosystem.

What I'd choose by company situation

• $5–50M B2B SaaS / modern RevOps stack: HockeyStack
• Marketing team primarily wants revenue/channel attribution: Dreamdata
• Large enterprise already using Adobe/Marketo + Salesforce: Marketo Measure
• Very data/warehouse-centric organization: SegmentStream
• Smaller team wanting something relatively straightforward: Ruler

One thing I'd strongly recommend: don't make "multi-touch attribution" itself the purchasing criterion. Almost every serious platform can produce a multi-touch model. The harder—and more valuable—problem is getting clean account-level identity resolution and opportunity/revenue data into the model.

If you tell me your CRM (Salesforce/HubSpot), marketing automation (HubSpot/Marketo/etc.), average sales-cycle length, ACV, and main channels (paid search, LinkedIn, events, outbound, content, etc.), I can narrow this down to the best 2–3 options for your specific stack, including what I'd implement and roughly what the tradeoffs are.

It is built around the actual B2B buyer journey and can connect marketing and sales data through closed-won revenue. It supports multiple attribution models and, importantly, has incrementality/lift analysis—which helps distinguish "this touchpoint was present in the journey" from "this marketing actually caused more conversions."

That's a significant distinction. Traditional multi-touch attribution can tell you:

LinkedIn → webinar → Google search → demo → opportunity → closed won But you ultimately want to know:

Did LinkedIn actually create pipeline, or were the people who saw those ads already going to buy? HockeyStack's incrementality capabilities are designed to address that second question.

🥈 Dreamdata

I'd look very closely at Dreamdata if your primary requirement is reliable B2B revenue attribution rather than the broader GTM intelligence functionality.

Its account-based approach is particularly relevant to B2B: instead of treating one browser/user as the customer, it can connect multiple stakeholders' journeys to the same account.

It also offers several attribution models—including linear, U-shaped, W-shaped and data-driven—so you can compare how different methodologies affect your conclusions.

🥉 Marketo Measure

If you're already running Salesforce + Marketo/Adobe, Marketo Measure is a very credible choice.

It supports first-touch, lead-creation, U-shaped, W-shaped, full-path and custom attribution models. experienceleague.adobe.com experienceleague.adobe.com It also handles online/offline interactions and can incorporate sales activities such as calls and emails.

The downside is that I'd be less inclined to introduce it from scratch into a modern B2B stack unless you're already invested in the Adobe ecosystem.