What is Multi-Touch Lead Attribution?

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Multi-touch attribution is a method of measuring the impact of various marketing channels and campaigns on customer conversions. By analysing the customer journey and assigning credit to each touchpoint that contributes to a sale, technology companies can gain a deeper understanding of their marketing efforts. This information can then be used to optimise future marketing campaigns and allocate resources more efficiently to acquire new customers.

Unlike traditional single-touch models that attribute all credit to the final touchpoint (e.g., the click that immediately precedes a conversion), multi-touch models distribute credit among all interactions that contribute to a lead or conversion. This more holistic view provides a more accurate understanding of customer journeys and helps optimise marketing strategies for increased sales.

Multi-Touch Attribution Emerges as a Solution for the Future

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What we see today in a B2B SaaS space is that CMOs face increasing pressure to prove the value of marketing investments to their C-suite counterparts. What’s not helping is the fact that CMOs are expected to do more with less. According to the 2024 Gartner CMO Spend Survey, a mere 24% of CMOs feel they have sufficient budget to execute their 2024 strategies. The expectations for measurable results continue to rise while the challenge to demonstrate marketing's contribution to revenue is compounded by the complexities of B2B sales cycles.

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One significant obstacle lies in the traditional siloed approach to sales and marketing. When sales teams manage the bottom of the funnel and often operate independently, it becomes difficult to accurately attribute conversions to specific marketing efforts. Gartner’s research (2024)  found out that marketing and sales teams typically collaborate on only three out of 15 commercial activities. This lack of collaboration hinders the ability to track the full customer journey and measure the impact of various touchpoints. The same research pointed out that companies that enable their sales and marketing teams working alongside the buying journey, see 2.3 times higher sales conversion rates. 

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The Attribution Arms Race: Sales vs. Marketing vs. Partnerships

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In B2B sales, the battle for lead attribution has intensified. Sales teams, eager to claim credit for their hard work and secure larger bonuses, often insist on a last-touch attribution model that assigns all credit to the final interaction before a sale. Marketing departments, on the other hand, argue for the importance of multi-touch attribution, recognising the contributions of various touchpoints throughout the customer journey, especially early on during demand generation activities. 

Additionally, C-level executives within partnerships are increasingly demanding greater visibility into the effectiveness of their joint marketing efforts. As businesses seek to maximise ROI on their partnerships, they want to understand how their investments are contributing to revenue generation. Multi-touch attribution can provide this clarity by demonstrating the value of each partner's contributions to the customer journey, enabling more informed decision-making and stronger partnerships. As the stakes rise, the battle for attribution becomes a strategic game of influence, with significant implications for resource allocation and performance evaluation. It helps to break down the silos between sales and marketing. By working together, GTM teams can gain a deeper understanding of customer behaviour, optimise marketing efforts, and ultimately drive greater revenue.

Key benefits of Multi-Touch Attribution

Better understanding of the customer journey

These models reveal the complex paths customers take before making a purchase, identifying critical interactions and touchpoints that influence decision-making.

Campaign Optimisation

By understanding which marketing channels and activities are most effective at different stages of the customer journey, businesses can allocate resources more efficiently and tailor their campaigns for maximum impact.

Improved Lead Quality

Multi-touch attribution can help identify leads that are more likely to convert by analysing the interactions they had with the brand. This information can be used to prioritise leads and allocate sales resources accordingly.

More insights into the ROI Measurement

 By accurately attributing credit to all touchpoints, multi-touch attribution provides a more reliable measure of marketing ROI. This enables businesses to make data-driven decisions about their marketing investments.

In the following sections, we will explore some of the most common multi-touch attribution models and discuss how they can be applied to improve sales.

Most Common Lead Attribution Models and Its Implications

1. First-touch lead attribution

Definition: Assigns credit to the initial touchpoint that introduces a potential customer to the brand.

Example: A user visits a company's website through a paid search ad. Even if they convert later through a different channel, the first-touch model attributes the lead to the paid search ad.

Drawbacks: May overvalue early-stage touchpoints and undervalue later-stage interactions that are more directly responsible for conversions.

Best suited for: Partnerships with a strong focus on initial awareness and lead generation: If the primary goal of a partnership is to introduce the brand to a new audience and generate initial leads, first-touch attribution can be effective. It highlights the importance of the initial touchpoint in driving awareness and consideration. In some cases, the first touchpoint may be a unique or highly valuable interaction, such as a referral from a trusted source. 

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2. Last-touch lead attribution

Definition: Assigns credit to the final touchpoint that occurs immediately before a conversion.

Example: A user clicks on a social media ad and then converts on the website. The last-touch model attributes the lead to the social media ad.

Drawbacks: Can undervalue earlier-stage touchpoints that are essential for nurturing leads and building brand awareness.

Best suited for: 

• Partnerships where the final touchpoint is directly responsible for the conversion: If the partner's contribution is primarily focused on the final stage of the customer journey, such as providing a demo, closing the deal, or offering a discount, last-touch attribution may be appropriate. It highlights the impact of the partner's direct interaction in driving conversions.
• Partnerships with a clear, linear customer journey: If the customer journey is relatively straightforward, with a clear sequence of interactions leading to a conversion, last-touch attribution can provide a reasonable approximation of the partner's contribution.

Conclusion:

While first-touch and last-touch models provide basic insights, they often oversimplify the customer journey. More sophisticated models, such as multi-touch attribution, are becoming increasingly popular as it provides more accurate understanding of how all of their teams’ efforts contribute to conversions.

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3. Linear Attribution

Definition: Assigns equal credit to each touchpoint in the customer journey.

Example: If a customer interacts with four touchpoints before converting, each touchpoint receives 25% credit.

Best suited for: 

• Partnerships where all interactions are considered equally valuable. If the customer journey involves a clear sequence of steps with each touchpoint contributing significantly to the conversion, linear attribution can provide a reasonable approximation of the partner's involvement.
• When both partners contribute equally to the customer journey, linear attribution can recognize the value of each party's involvement.
• If no single touchpoint is significantly more influential than others in driving conversions, linear attribution can provide a fair distribution of credit.

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4. Time Decay Attribution

Definition: Assigns more credit to recent interactions, assuming they had a stronger influence.

Example: A conversion might be attributed 40% to the last touch, 30% to the second-to-last, and 20% to the third-to-last touch.

Best suited for: 

• Partnerships where recency is a key factor: If the partner's most recent interactions are believed to have a significant impact on the customer's decision, time decay attribution can accurately reflect this influence.
• In industries where customers make quick decisions, recent interactions may play a more dominant role in the conversion process.
• If the partner's primary role is to provide ongoing support or address customer concerns, time decay attribution can recognise the importance of their recent interactions in maintaining customer satisfaction and loyalty.

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5. Position-Based Attribution

Definition: Assigns significant credit to the first and last interactions, assuming they had the most impact.

Example: A conversion might be attributed 40% to the first touch, 40% to the last touch, and 20% to the remaining touchpoints.

Best suited for: 

• Partnerships where the initial and final interactions are crucial: If the partner's role is to introduce the brand to new customers or provide the final push to close the deal, position-based attribution accurately reflects the importance of these interactions.
• Industries with a clear customer journey: If the customer journey is relatively straightforward with well-defined stages, position-based attribution can effectively capture the influence of the initial and final touchpoints.
• Partnerships with a focus on brand awareness and lead generation: If the partner's primary goal is to introduce the brand to a new audience and generate initial leads, position-based attribution can recognise the value of their early-stage contributions.

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6. W-Shaped Attribution

Definition: Assigns more credit to the first, last, and middle touchpoints, assuming they had the most impact.

Example: A conversion might be attributed 30% to the first touch, 20% to a middle touch, 30% to the last touch, and 20% to the remaining touchpoints.

Best suited for: 

• Partnerships where mid-journey interactions are crucial: If the partner's role is to provide key information, demos, or support at specific stages of the customer journey, W-shaped attribution can accurately capture the influence of these interactions.
• Industries with complex customer journeys: If the customer journey involves multiple stages and decision points, W-shaped attribution can effectively recognise the importance of mid-journey touchpoints.
• Partnerships with a focus on customer education and nurturing: If the partner's role is to provide valuable content, resources, or support to educate and nurture customers, W-shaped attribution can highlight the impact of these mid-journey interactions.

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7. Custom Attribution

Definition: Allows you to create a model based on your partnership's unique dynamics and goals.

Example: If you know that Partner A's marketing efforts consistently drive high-quality leads, you might assign a higher percentage of credit to them.

Best suited for: 

• Partnerships with complex dynamics: If the partnership involves multiple touchpoints, varying levels of influence, and unique factors that affect the customer journey, custom attribution can be used to create a model that accurately reflects these complexities.
• Partnerships with specific requirements: If the business has specific goals or requirements for measuring partner contributions, custom attribution can be used to create a model that aligns with these objectives.
• Businesses with advanced data capabilities: Custom attribution often requires access to detailed data and analytics tools. Businesses with advanced data capabilities are better equipped to create and implement custom models.

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8. Algorithmic Attribution

Definition: Uses algorithms to analyse large datasets and determine the optimal attribution model.

Example: Machine learning models can identify patterns in customer data to assign credit to touchpoints.

Best suited for:

• ​​Partnerships with access to extensive data: These models require a large amount of data to accurately analyse customer behaviour and interactions. Businesses with access to detailed data from various sources, such as website analytics, CRM systems, and marketing automation platforms, are well-suited for algorithmic attribution.
• Partnerships with a desire to leverage advanced analytics: Algorithmic attribution leverages sophisticated algorithms and machine learning techniques to provide insights that may not be possible with traditional attribution models. Businesses that want to harness the power of advanced analytics can benefit from algorithmic attribution.
• Partnerships with complex customer journeys: Algorithmic attribution can handle complex customer journeys with multiple touchpoints and varying levels of influence. This makes it suitable for partnerships in industries with long sales cycles or intricate decision-making processes.

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Top 10 Considerations for Implementing Multi-Touch Attribution

Implementing multi-touch attribution can provide valuable insights into your marketing efforts. Here are ten key considerations to get started:

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1. What are your goals?

Clearly articulate what you want to achieve with multi-touch attribution. Are you looking to measure campaign effectiveness, optimise resource allocation, or improve customer journey understanding?‍

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2. Which attribution models suit your business needs?

Select a model that aligns with your business objectives and data availability. Common options include first-touch, last-touch, linear, time-decay, and U-shaped.

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3. Can you access all the necessary data? 

Ensure you have access to the required data, such as website traffic, email opens, click-through rates, and CRM data. Consider using a data management platform (DMP) to consolidate information.

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4. Can you integrate all your marketing, sales and partner tools?

Connect your marketing tools (e.g., CRM, marketing automation, analytics) to enable data sharing and analysis. By integrating with marketing automation tools, PRM systems can enable targeted marketing campaigns to partners. This helps to nurture relationships, increase engagement, and drive lead generation. This data can be used to optimise marketing strategies and improve partner satisfaction. The right PRM solution will enable multi-touch lead attribution for your partner teams, including events, emails, UTM links and social media posts or any other interaction with the customer that influenced the customer journey.

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5. What are your attribution windows?

Determine the timeframe for attributing conversions to specific touchpoints. This can vary depending on your industry and sales cycle. For companies with longer sales cycles, it may be necessary to extend the attribution window to capture the full impact of touchpoints that occurred earlier in the process.

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6. Have you addressed privacy concerns?

Comply with relevant data privacy regulations (e.g., GDPR, CCPA) and obtain necessary user consent. Ensure that users clearly understand how their data will be used for attribution purposes and provide a clear affirmative action to grant consent. Also, clearly disclose the types of data collected, how it will be used, and the potential consequences of not consenting. As a last step, provide users with the option to opt out of data collection or processing for attribution purposes.

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7. What are your technological limitations?

Be aware of potential limitations in data tracking and attribution due to factors like cookie blocking or ad blockers.

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8. What are the trends and insights from your lead attribution?

Regularly analyse attribution data to identify trends, insights, and areas for improvement.  Identify the channels that are most effective in generating new leads and allocate resources accordingly. Make sure you understand the typical steps customers take before converting and optimise marketing efforts to align with this journey.

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9. Is your GTM team aligned on the partnership goals?

Promote collaboration between sales, marketing, and other departments to ensure effective use of attribution data. Everyone involved in the buying journey should have a solid understanding of the desired outcomes and objectives. Lastly, remember to define specific tasks and expectations to avoid confusion and ensure accountability.

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10. Are you continuously optimising your efforts?

Regularly review and adjust your attribution strategy based on evolving business needs and data insights.