Multi-touch attribution is a marketing measurement model that assigns value to multiple customer touchpoints along the journey to conversion, rather than crediting a single interaction. The multi-touch attribution model is similar to marketing mix modeling, but with a more comprehensive and data-driven approach. Multi-touch and multi-channel attribution are also different—while multi-channel assigns value on a channel-by-channel basis, it neglects specific touch points along the way.
Unlike single-touch attribution, multi-touch attribution plots out a complete customer journey with several touch points. A single-touch approach credits a single point without room for nuance, which is far too broad if you have a strict marketing budget or need to determine which Google Ads campaign to prioritize.
What is the Goal of Multi-Touch Attribution?
The ultimate goal of any marketing attribution model is maximizing your marketing dollar by funneling time and budget where they’ll generate the most leads for the least amount of money.
Multi-touch attribution is important because it offers a more detailed look at the customer journey than other attribution models like first-touch or last-touch attribution.
The difference between first-touch and last-touch campaign attribution is emphasizing the customer’s first interaction with your brand versus their last interaction before ultimately converting—multi-touch leaves room for both, including every touch point along the way.
What are the Benefits of Using a Multi-touch Attribution Model?
The benefits using a multi-touch attribution model include:
- More visibility into conversions: When you understand how each touch point contributes to conversion rate optimization, you can prioritize and repeat processes that see the most results.
- Easier prioritization for successful campaigns: As you create a content timeline, leverage your findings to funnel more money and attention into high-performing touch points.
- Marketing campaign efficiency: Multi-touch attribution lets you see which touch points aren’t beneficial along the customer journey to cut underperforming campaigns and reallocate those resources somewhere more beneficial.
- Better allocate spending: Make smarter budgetary decisions and increase paying conversions while simultaneously proving campaign effectiveness to key stakeholders.
- Better customer insights: Leverage marketing analytics to learn more about your customers as you assess touch points in multi-touch attribution modeling. By mapping customer engagement, you get a sense of where they spend their time and what marketing messages appeal to them.
Types of Multi-Touch Attribution Models
There are several typeas of multi-touch attribution models. Popular multi-touch attribution models include:
U-Shaped Attribution Models
U-shaped attribution models, also called position-based attribution, assigns 40 percent of credit to the first and last touch point, while the rest distributes evenly across all the touch points in between.
W-Based Attribution Models
W-based attribution models assign the most weight to the “first discovery” touch point—when the customer first learns of your product or business—as well as the lead capture and final conversion touch points.
Linear Attribution Models
Linear attribution models divide credit equally across each touch point in the customer journey.
Time-based Attribution Models
Time-based attribution model focus on touch points closest to the moment of conversion, like the first or last touch point. Remaining touch points decrease in weight the farther they are from those conversion events on the customer journey timeline.
Custom Attribution Models
Many businesses have the most success with a custom attribution model. Though highly efficient, custom models are challenging to create without professional help or specialized tools like a customer data platform.
Learn more about different types of attribution models, and how they can help measure the effectiveness of marketing campaigns here
FAQ
What is the best multi-touch attribution model?
The best model depends on your business context, sales cycle, and marketing goals. Linear attribution works well when all touchpoints contribute equally, while time-decay is better for businesses with shorter sales cycles where recent interactions matter most. Many organizations find that custom attribution models—tailored to their specific customer journey and channel mix—produce the most accurate and actionable insights.
How is multi-touch attribution different from marketing mix modeling?
Multi-touch attribution tracks individual customer journeys across digital touchpoints to assign credit at a granular, user-level basis. Marketing mix modeling uses aggregate statistical analysis on historical data to measure the overall impact of marketing channels on business outcomes without tracking individuals. MTA excels at tactical digital optimization, while MMM is better for strategic budget planning across both online and offline channels.
What are the challenges of multi-touch attribution?
The biggest challenges include cross-device tracking (customers switching between phone, tablet, and desktop), the deprecation of third-party cookies that limits cross-site visibility, and walled garden platforms that restrict data sharing. Offline touchpoints like in-store visits or phone calls are also difficult to incorporate into digital attribution models. Many organizations address these gaps by combining multi-touch attribution with other measurement approaches like marketing mix modeling and incrementality testing.
Related Terms
- Incrementality Testing — Measures the true causal lift of marketing actions beyond attribution
- Campaign Analytics — Tracks performance metrics across campaigns that attribution models evaluate
- Customer Journey Analytics — Visualizes the full journey that multi-touch models assign credit across
- Return on Ad Spend (ROAS) — Revenue-to-cost metric that attribution data helps optimize