This comprehensive glossary delves into the world of revenue attribution modeling specifically for B2B SaaS companies. Whether you’re a marketing director trying to justify your budget, a revenue operations specialist building attribution frameworks, or a CMO seeking to align marketing activities with business outcomes, this resource will equip you with the terminology and concepts essential for navigating the attribution landscape.
As we explore these terms, remember that attribution is both an art and a science—combining data analysis with strategic interpretation to tell the story of how your marketing influences revenue generation.
Core Attribution Concepts
Attribution Model
A framework that determines how credit for sales and conversions is assigned to touchpoints in the customer journey. Different models distribute credit in various ways, reflecting different perspectives on the customer conversion path.
Touchpoint
Any interaction between a potential customer and your company. In B2B SaaS, touchpoints might include website visits, content downloads, webinar attendance, email opens, demo requests, or sales calls.
Customer Journey
The complete sequence of interactions a prospect has with your brand from initial awareness to becoming a customer and beyond. In B2B SaaS, these journeys are typically longer and more complex than in B2C contexts.
Conversion
The completion of a desired action. In B2B SaaS, conversions exist on a spectrum from micro-conversions (e.g., newsletter sign-ups) to macro-conversions (e.g., subscription purchases or contract renewals).
Attribution Window
The timeframe during which touchpoints are considered relevant for attribution. For B2B SaaS, this window may span months or even years, reflecting the typically longer sales cycles.
Types of Attribution Models
Single-Touch Attribution Models
Models that assign 100% of the credit to one touchpoint in the customer journey.
First-Touch Attribution
Attributes 100% of the revenue to the first interaction a prospect has with your brand. This model emphasises top-of-funnel activities that create initial awareness.
Last-Touch Attribution
Assigns all credit to the final touchpoint before conversion. This model highlights bottom-of-funnel activities that drive immediate conversions but may undervalue earlier nurturing efforts.
Lead-Creation Attribution
Gives full credit to the touchpoint where a prospect first identifies themselves by providing contact information. This model recognises the critical transition from anonymous visitor to known lead.
Opportunity-Creation Attribution
Attributes all revenue to the touchpoint that resulted in a sales opportunity being created. This model emphasises activities that generate qualified pipeline.
Multi-Touch Attribution Models
Models that distribute credit across multiple touchpoints in the customer journey, providing a more nuanced view of marketing effectiveness.
Linear Attribution
Distributes credit equally across all touchpoints in the customer journey. For example, if there are five touchpoints, each receives 20% of the credit.
Time-Decay Attribution
Assigns more credit to touchpoints closer to the conversion, with diminishing credit for earlier touchpoints. This model acknowledges that recent interactions may have more influence on the final decision.
U-Shaped Attribution (Position-Based)
Gives 40% credit each to the first touch and lead-creation touch, with the remaining 20% distributed among touchpoints in between. This model emphasises both awareness-building and lead-generation activities.
W-Shaped Attribution
Allocates 30% each to first touch, lead creation, and opportunity creation, with the remaining 10% distributed among other touchpoints. This model highlights three critical conversion points in the B2B journey.
Full-Path Attribution
Extends the W-shaped model by also giving significant credit to the close-won touchpoint, typically distributing 22.5% each to first touch, lead creation, opportunity creation, and closed deal, with 10% shared among remaining touchpoints.
Custom Attribution
Tailored models designed to reflect the unique characteristics of a company’s sales and marketing processes, often incorporating weighted values based on historical performance data.
Algorithmic Attribution
Uses machine learning and statistical modeling to dynamically assign credit to touchpoints based on their actual influence on conversions, rather than using predetermined rules.
Markov Chain Models
A probabilistic approach that calculates the likelihood of conversion at each stage of the customer journey and assigns credit accordingly.
Shapley Value Attribution
Borrowed from game theory, this approach calculates the marginal contribution of each touchpoint by comparing conversion rates with and without each touchpoint.
Machine Learning Attribution
Leverages AI to analyse patterns in customer journey data and determine the incremental impact of each touchpoint on conversion probability.
Attribution Metrics and KPIs
Return on Investment (ROI)
The ratio of revenue generated to marketing spend, calculated using attribution data to determine which channels and campaigns deliver the highest returns.
Customer Acquisition Cost (CAC)
The total cost of acquiring a new customer, which can be calculated more accurately when attribution data reveals which marketing activities influenced each acquisition.
Lifetime Value (LTV)
The predicted revenue a customer will generate throughout their relationship with your company. Attribution helps connect LTV to specific acquisition channels and campaigns.
LTV:CAC Ratio
A metric comparing customer lifetime value to acquisition cost, indicating the efficiency and sustainability of your growth strategy. Attribution provides channel-specific LTV:CAC ratios.
Marketing Influenced Revenue
The total revenue from deals where marketing touchpoints played a role in the customer journey, regardless of whether marketing gets primary attribution credit.
Marketing Sourced Revenue
Revenue from deals where marketing efforts initiated the customer relationship (first-touch attribution).
Pipeline Velocity
The speed at which prospects move through your sales pipeline. Attribution data can reveal which marketing activities accelerate pipeline movement.
Conversion Rate by Channel
The percentage of prospects from each channel who complete desired actions. Attribution models help calculate accurate channel-specific conversion rates.
Incremental Lift
The additional conversions generated by a specific marketing activity that wouldn’t have occurred otherwise, often measured through controlled experiments.
Attribution Implementation Concepts
Marketing Technology Stack
The collection of software tools used to execute, manage, and measure marketing activities. For attribution, this typically includes:
- Customer Relationship Management (CRM) systems
- Marketing Automation Platforms
- Analytics tools
- Attribution software
- Data warehouses
- Business Intelligence tools
UTM Parameters
Tracking codes added to URLs to identify the source, medium, campaign, content, and term that directed traffic to your website. Essential for digital channel attribution.
Tracking Pixels
Small, invisible image files or JavaScript code snippets placed on websites to track user behavior and conversions for attribution purposes.
Cookies
Small data files stored in a user’s browser that help track their interactions across multiple sessions. First-party cookies are increasingly important as third-party cookies are phased out.
Customer Data Platform (CDP)
Software that unifies customer data from multiple sources to create comprehensive customer profiles, enabling more accurate cross-channel attribution.
Identity Resolution
The process of connecting multiple identifiers (cookies, device IDs, email addresses) to a single customer profile for accurate cross-device and cross-channel attribution.
Data Silos
Isolated repositories of data that aren’t easily accessible across an organisation, creating challenges for comprehensive attribution modeling.
Data Governance
The framework for managing data quality, consistency, and security across the organisation, crucial for reliable attribution modeling.
Advanced Attribution Concepts
Multi-Channel Attribution
The practice of assigning credit across various marketing channels (email, social, search, events, etc.) that contribute to conversions.
Cross-Device Attribution
Tracking and crediting touchpoints that occur across different devices (mobile, desktop, tablet) used by the same prospect.
Online-to-Offline Attribution
Connecting digital marketing activities to in-person interactions such as sales meetings or events, particularly important in complex B2B sales processes.
Incrementality Testing
Experimental approaches (like holdout tests or geo-testing) that measure the true incremental impact of marketing activities by comparing test and control groups.
Attribution Bias
Systematic errors in attribution models that consistently over or under-attribute credit to certain channels or touchpoints.
Marketing Mix Modeling (MMM)
A top-down statistical analysis approach that determines the impact of various marketing tactics on sales and market share, complementing bottom-up attribution models.
Unified Measurement Approach
The integration of multiple measurement methodologies (e.g., multi-touch attribution and marketing mix modeling) to create a more comprehensive view of marketing effectiveness.
Account-Based Attribution
Attribution that considers all touchpoints across multiple contacts within a target account, aligning with Account-Based Marketing (ABM) strategies common in B2B SaaS.
Revenue Operations and Attribution
Revenue Operations (RevOps)
The alignment of sales, marketing, and customer success operations across the full customer lifecycle to drive growth through operational efficiency and improved customer experience.
Sales and Marketing Alignment
The strategic integration of sales and marketing teams, processes, and technologies to create a unified revenue generation system. Attribution models often serve as a shared framework for this alignment.
Service Level Agreements (SLAs)
Formal agreements between sales and marketing that define expectations for lead quality, quantity, and follow-up timeframes, often informed by attribution data.
Closed-Loop Reporting
A system where marketing receives data on what happens to leads after they’re passed to sales, enabling continuous improvement of marketing strategies based on actual revenue outcomes.
Revenue Cycle Modeling
Mapping the entire customer journey from first touch to revenue and beyond, identifying key conversion points and revenue opportunities throughout the process.