Multi-Touch Attribution Tools Compared: The Complete 2026 Guide

The Real Question

You're not here to read about 50 attribution tools. You're here because you need to pick one and get back to work.

Quick Answer

B2B SaaS?
→ mbuzz for LTV attribution + simplicity—see which channels drive long-term value
→ Factors.ai for account-based attribution
→ Ruler Analytics for call tracking + lead source

B2B SaaS with long sales cycles?
→ HockeyStack for fast setup + all-in-one
→ Dreamdata for customer journey visualization
→ Bizible if you're on Salesforce

Running a Shopify store?
→ mbuzz if you want to compare models and build custom logic
→ Triple Whale if you want plug-and-play simplicity
→ Northbeam for enterprise Shopify Plus with big ad spend

Want transparency, not a black box?
→ mbuzz—8 models you can inspect, custom rules you control

The Uncomfortable Truth

Most attribution tools fall into two camps: sophisticated but opaque (ML models you can't inspect) or simple but limited (basic rules that oversimplify). The "enterprise" tools charge $50K+ for algorithms you have to trust blindly. The cheap tools give you last-click with lipstick.

The real question isn't "which tool has the most features?" It's "which tool will I actually trust enough to make decisions with?"

Full disclosure: mbuzz is in this comparison. We'll tell you when competitors are the better choice.

The Market Gap: Sophisticated AND Transparent

Most attribution tools make you choose. The sophisticated ones (ML-powered, multi-model) are black boxes—you can't inspect how they calculate credit. The transparent ones are basic—simple rules you can understand, but limited depth.

The gap: Almost no one offers sophisticated attribution you can actually inspect and edit.

Black Box

Inspectable

← Sophistication →

Trust the Algorithm

Sophisticated ML you can't inspect

Best of Both Worlds ★

Sophisticated AND transparent

Platform Native

Built-in defaults, limited visibility

Simple & Clear

Easy to understand, limited depth

← Transparency →

The market gap: Most sophisticated tools are black boxes. Most transparent tools are basic. mbuzz gives you both.

Find Your Attribution Tool

Alternatives for: All tools mbuzz Triple Whale Northbeam HockeyStack Dreamdata Rockerbox Ruler Analytics

Price:

Free <$200 <$500 <$2000

Market: E-commerce / DTC B2B SaaS Enterprise Multi-Channel Lead Generation Unified Measurement

Features: Free tier Custom models Server-side LTV tracking MMM Call tracking

Setup time: < 1 hour < 1 day < 2 weeks < 2 months

Clear filters 11 tools

Tool	Best For	Starting Price	Key Features
mbuzz Server-side attribution with model flexibility		Free	Custom models Server-side LTV	Try Free →
Triple Whale Shopify-native attribution	Shopify stores, Easy setup	$129/mo	3 models	Alternatives →
Northbeam ML-powered DTC attribution	Enterprise DTC ($40M+), Dedicated media buyers	$400/mo	View-through 1 model	Alternatives →
HockeyStack All-in-one B2B attribution	B2B SaaS, Series A-C	$2200/mo	View-through 3 models	Alternatives →
Dreamdata B2B revenue attribution	B2B mid-market, Journey visualization	$999/mo (free tier)	View-through Journey viz 3 models	Alternatives →
Rockerbox Multi-channel attribution with MMM	Multi-channel brands, Podcast/TV advertisers	$200/mo (free tier)	View-through MMM 3 models	Alternatives →
Ruler Analytics Call tracking + attribution	Lead gen businesses, Call-heavy industries	£349/mo	Calls 3 models	Alternatives →
Hyros High-ticket attribution	High-ticket sales, Info products	$500/mo	LTV 3 models
Bizible (Adobe) Enterprise Salesforce attribution	Enterprise B2B, Salesforce-heavy orgs	Custom	View-through 5 models
Lifesight Unified measurement platform	Enterprise brands, Full measurement stack	Custom	LTV View-through MMM
Google Analytics 4 Free web analytics	Getting started, Budget zero	Free	2 models

No tools match your filters

Try adjusting your criteria or clear all filters

Our Pick: mbuzz

Mbuzz

Best for: Teams wanting flexible, server-side attribution without enterprise pricing

Why we built mbuzz:

Most sophisticated attribution tools are black boxes. You trust the algorithm or you don't. Most transparent tools are too basic—last-click or simple rules.

We wanted both: sophisticated models (Markov chains, Shapley values, time decay) that you can actually inspect. Plus the ability to define your own attribution logic.

8 attribution models, not 3. Compare first-touch, last-touch, linear, time-decay, U-shaped, W-shaped, plus data-driven Markov Chain and Shapley Value models side-by-side. See how credit shifts between channels under different models:

Custom models via simple rule editor. Don't wait for feature requests—write your own attribution logic in minutes:

within_window 90.days do
  within_window 30.days, weight: 0.6 do
    time_decay half_life: 7.days
  end

  within_window 30.days..60.days, weight: 0.4 do
    time_decay half_life: 14.days
  end
end

Strengths:
- Server-side tracking captures 95%+ of events (vs 60-70% with client-side)
- 8 built-in models including Markov Chain and Shapley Value
- Custom attribution rules via simple DSL—define your own logic
- Side-by-side model comparison shows how credit shifts
- LTV attribution tracks recurring revenue to acquisition source
- Native SDKs for Shopify, Rails, Django, Laravel, Node.js — setup guide
- Transparent pricing, no sales calls, export everything

Limitations:
- Newer player with less market presence
- No built-in podcast/TV proxy tracking (digital-focused)
- Non-Shopify platforms require SDK integration (straightforward for developers)

Who mbuzz is NOT For:
- Heavy podcast/TV advertisers → Rockerbox handles offline attribution better
- Teams who want a single "magic number" → mbuzz shows multiple models by design

Enterprise MTA Platforms

These tools are designed for large organizations with complex tech stacks, significant budgets, and dedicated analytics teams.

Adobe Marketo Measure (Bizible)

Best for: Enterprise B2B companies in the Adobe/Salesforce ecosystem

Strengths:
- Native Salesforce integration—no data sync issues
- Can run multiple attribution models simultaneously
- Strong ABM (account-based marketing) support
- Part of Adobe Marketing Cloud ecosystem

Limitations:
- Expensive and complex implementation
- Requires dedicated RevOps resources
- Fixed rule-based models (less flexible than ML-driven)
- Heavy Adobe/Salesforce lock-in

Best fit: Enterprise B2B companies already invested in Salesforce + Adobe Marketo who need account-level attribution and have RevOps teams to manage it.

Google Attribution 360 (GA360)

Best for: Large organizations in the Google ecosystem

Strengths:
- Deep Google Ads integration
- Data-driven attribution using Shapley values
- BigQuery export for custom analysis
- Connected TV and YouTube measurement

Limitations:
- Expensive
- Biased toward Google properties
- Limited non-Google channel visibility
- Requires 400+ conversions for data-driven model

Best fit: Large advertisers spending heavily on Google properties who want sophisticated modeling within Google's ecosystem.

B2B SaaS Attribution Tools

These platforms focus on long sales cycles, multiple stakeholders, and CRM integration.

Hockeystack

Best for: B2B SaaS companies wanting all-in-one revenue analytics

Strengths:
- Fast implementation (2 weeks vs months)
- Combines attribution with web analytics and surveys
- No-code setup
- Tracks dark funnel via "How did you hear about us?" surveys

Limitations:
- Expensive for smaller companies
- Reports of data trust issues at scale
- Can be outgrown by enterprise needs
- Flashy demos don't always match production reality

Best fit: Series A-C B2B SaaS companies with $5M+ ARR who want to move fast and consolidate marketing + product analytics.

See all HockeyStack alternatives →

Dreamdata

Best for: Data-driven B2B marketing teams focused on pipeline

Strengths:
- Strong customer journey mapping
- Connects marketing to pipeline and revenue
- Content analytics included
- Reasonable pricing for mid-market

Limitations:
- Lengthy setup process
- Challenging data verification
- Needs Looker for custom visualization
- Limited ABM features for enterprise

Best fit: Mid-market B2B companies ($2-20M ARR) who are data-driven and want clear pipeline attribution.

See all Dreamdata alternatives →

Factors.ai

Best for: B2B teams wanting AI-powered insights

Strengths:
- AI-powered recommendations
- Combines attribution with account identification
- More affordable than HockeyStack
- Expert support included in pricing

Limitations:
- Newer player, less market validation
- Limited enterprise features
- Smaller integration ecosystem

Best fit: Growth-stage B2B companies ($1-10M ARR) who want AI assistance and don't have large analytics teams.

E-commerce / DTC Attribution Tools

These platforms specialize in ad tracking, ROAS measurement, and e-commerce integrations.

Triple Whale

Best for: Shopify stores of all sizes

Strengths:
- Easiest setup for Shopify stores
- Affordable for smaller brands
- Simple, marketer-friendly interface
- Good for owner-operators and small teams

Limitations:
- Shopify-only (no WooCommerce, Magento, etc.)
- Click-through tracking only (no view-through)
- Less sophisticated modeling than enterprise tools
- Struggles at scale ($50M+ revenue)

Best fit: Shopify stores from startup to ~$30M revenue who want simple, affordable attribution.

See all Triple Whale alternatives →

Northbeam

Best for: Enterprise DTC brands with sophisticated media buying

Strengths:
- Machine learning that prevents over-attribution
- All sales sum to actual revenue (no double-counting)
- Advanced predictive analytics
- Built for sophisticated media buyers

Limitations:
- Complex interface, steep learning curve
- Expensive for high-traffic sites
- Overkill for smaller brands
- Best suited for $40M+ brands

Best fit: DTC brands spending $500K+/month on paid media with dedicated media buying teams.

See all Northbeam alternatives →

Rockerbox

Best for: Multi-channel brands including offline

Strengths:
- Tracks difficult channels (podcasts, TV, direct mail)
- Marketing Mix Modeling (MMM) included
- Good for brand + performance marketing mix
- Suitable for CMO-level strategic decisions

Limitations:
- Less suited for tactical daily optimization
- Complex for smaller teams
- Enterprise focus despite lower starting price

Best fit: Brands investing in awareness channels (podcasts, TV, influencers) who need to measure upper-funnel impact.

See all Rockerbox alternatives →

Hyros

Best for: High-ticket e-commerce and info products

Strengths:
- Strong for high-ticket/long sales cycles
- Claims 20% ROI improvement from AI optimization
- Deep ad platform integrations
- Works for info products, courses, coaching

Limitations:
- 6-month minimum commitment
- Invite-only, opaque pricing
- Less transparent than competitors
- Mixed reviews on actual AI performance

Best fit: High-ticket sellers ($500+ AOV) in the info product, coaching, or B2C space who want AI optimization.

Wicked Reports

Best for: E-commerce brands focused on LTV

Strengths:
- Strong LTV and cohort analysis
- Works for both B2B and e-commerce
- Integrates with Shopify, Klaviyo, ReCharge
- CPA and LTV metrics (unlike some competitors)

Limitations:
- Less brand recognition than Triple Whale/Northbeam
- Interface could be more polished
- Limited view-through attribution

Best fit: E-commerce brands with subscription revenue or high repeat purchase rates who care about LTV, not just first-purchase ROAS.

Multi-Model Attribution Platforms

These tools give you multiple attribution models to compare—not just one black-box answer. Our top pick here is mbuzz: 8 inspectable models + custom rules, covered in detail above.

Lifesight

Best for: Brands wanting complete measurement stack

Strengths:
- True unified measurement (MTA + MMM + model flexibility + causal AI)
- Real-time processing
- Cross-device tracking
- Designed for privacy-first world

Limitations:
- Higher complexity
- Newer, less market penetration
- Requires commitment to learn the platform

Best fit: Sophisticated marketing teams who understand triangulation and want a single platform for unified measurement.

Segmentstream

Best for: Privacy-first, cookieless attribution

Strengths:
- Built for cookieless future
- AI measures incremental (not just attributed) value
- Uses geo holdout tests to validate
- Automated budget allocation

Limitations:
- Newer approach, requires trust in AI
- May be ahead of what most teams can use
- Enterprise focus

Best fit: Forward-thinking teams preparing for cookie deprecation who want AI-driven, model flexibility-validated attribution.

Funnel

Best for: Data teams wanting MTA + MMM

Strengths:
- Combines MTA, MMM, and model flexibility
- 500+ data connectors
- Works with your data warehouse
- Flexible for data teams

Limitations:
- Requires data team involvement
- More infrastructure than plug-and-play tools
- Premium pricing

Best fit: Data-mature organizations with modern data stacks who want unified measurement without vendor lock-in.

Mobile Attribution (App-Focused)

These tools specialize in mobile app measurement, including install attribution, deep linking, and fraud prevention.

Appsflyer

Best for: Mobile-first companies needing full attribution

Strengths:
- Industry leader in mobile attribution
- Strong fraud prevention
- SKAdNetwork support
- Raw data access

Limitations:
- Expensive at scale
- Primarily mobile (limited web)
- Complex for simple use cases

Best fit: Mobile-first companies (apps driving >50% of revenue) who need accurate install attribution and fraud prevention.

Adjust

Best for: Privacy-conscious mobile apps

Strengths:
- Privacy-first approach
- Strong fraud suite
- Good automation features
- Acquired by AppLovin (resources)

Limitations:
- Less multi-touch than AppsFlyer
- AppLovin ownership raises neutrality questions
- Expensive at scale

Best fit: Mobile apps prioritizing privacy and fraud prevention, especially in regulated industries.

Branch

Best for: Cross-platform user experiences

Strengths:
- Best deep linking in the industry
- Good for web-to-app journeys
- Free tier for startups
- People-based attribution

Limitations:
- Deep linking focus—attribution is secondary
- Less sophisticated than AppsFlyer for pure attribution
- Complex setup for full features

Best fit: Companies with significant web-to-app flows who need seamless user experiences and measurement together.

Web/General Attribution Tools

These tools work for a variety of businesses without being specialized for B2B or DTC.

Ruler Analytics

Best for: SMBs with significant phone leads

Strengths:
- Combines web and call tracking
- First-party cookie focus
- Good for service businesses
- Affordable for SMBs

Limitations:
- UK-based (GBP pricing)
- Limited enterprise features
- UI needs modernization

Best fit: Service businesses (agencies, home services, B2B services) where phone calls are a significant conversion path.

See all Ruler Analytics alternatives →

Growify

Best for: E-commerce brands wanting flexibility

Strengths:
- Switch between attribution models easily
- Simple setup
- Multi-channel tracking
- Creative analysis features

Limitations:
- Less sophisticated than enterprise tools
- Newer player
- Limited integrations vs established tools

Best fit: Growing e-commerce brands who want to experiment with different attribution models without complexity.

How to Choose: Decision Framework

By Business Type

By Budget

By Tech Stack

The Future: Where MTA is Headed

Trend 1: Unified Measurement

Pure MTA is being replaced by triangulated approaches combining MTA + MMM + model flexibility. Platforms like Lifesight, Funnel, and SegmentStream are leading this shift.

Trend 2: Privacy-First / Cookieless

With iOS ATT and Chrome deprecating third-party cookies (eventually), AI-driven and first-party data approaches are the way forward. SegmentStream's visit scoring and Lifesight's causal AI represent this future.

Trend 3: Consolidation

Expect acquisitions: Adobe bought Bizible, AppLovin bought Adjust. Smaller players will be acquired or fade as the market matures.

Trend 4: AI Everywhere

Every tool now claims "AI-powered" attribution. The meaningful distinction is whether AI is cosmetic (chatbots on top of reports) or substantive (ML models that actually improve measurement accuracy).

Summary

The MTA market is crowded, but the right choice depends on your specific situation:

No tool is perfect. The best approach is often:
1. Start with a tool matched to your size and stack
2. Compare multiple models to understand how credit allocation shifts
3. Graduate to unified measurement as you scale

Alternatives by Tool

Looking to switch from a specific platform? See all alternatives:

E-commerce / DTC:
- Triple Whale Alternatives — Beyond Shopify-only attribution
- Northbeam Alternatives — Enterprise DTC options
- Rockerbox Alternatives — Multi-channel measurement

B2B SaaS:
- HockeyStack Alternatives — B2B attribution platforms
- Dreamdata Alternatives — Revenue attribution options

Holly Henderson

Co-Founder, mbuzz

Holly Henderson is Co-Founder of mbuzz. With 10+ years in marketing including roles at Westpac, Avon, and Forebrite, she's obsessed with making measurement actually useful.

Harvard Extension School Forebrite Westpac Avon