Feeling lost in the dark about which marketing efforts truly drive results? You are not alone. Multi-touch attribution (MTA) offers a way to illuminate the path, connecting marketing spend to actual revenue, providing clarity on what strategies are working.
MTA is a method to assess the effectiveness of your campaign components. However, it is not a perfect answer, especially with modern consumer privacy changes on the web. It still can provide insights when other tools aren’t a fit.
Table Of Contents:
- Understanding Multi-Touch Attribution
- Multi-Touch Attribution Models
- Moving Beyond Multi-Touch Attribution to Alternative Measurement
- Multi-Touch Attribution and The Changing Privacy Landscape
- Using Multi-Touch Attribution (For Nonprofits)
- Conclusion
Understanding Multi-Touch Attribution
Marketing has evolved beyond simple cause and effect. It once seemed obvious that a roadside billboard or a TV ad directly brought customers into a store. The customer journey isn’t so clear-cut anymore.
Customers now interact with brands across numerous touchpoints. This includes everything from social media ads to Google searches. So, how do you determine which interactions genuinely influence a purchase?
Multi-touch attribution acknowledges that every touchpoint plays a role. Instead of assigning all the credit to the initial click or the final conversion, it considers the entire customer journey. It is about understanding the cumulative impact, rather than focusing on a single event.
The Basics of MTA
How does multi-touch attribution work in practice? Data is collected from many places and channels, applying rules or formulas. These models distribute credit for a conversion across the customer’s multiple interactions, reflecting their contribution.
This method helps you understand the combined effect of various touchpoints. For instance, consider a customer who researches multiple companies before eventually signing up for your webinar. All those research interactions impacted the final decision.
This process relies on tracking and sending important touchpoints. This could be done with Javascript on a web page, special campaign parameters (like UTMs), and connecting systems together. API access allows systems to send those touchpoints directly to measurement systems.
Why the Old Ways Don’t Cut It Anymore
Traditional methods, like last-touch attribution, assign 100% of the credit to the final interaction before a purchase. These old approaches only tell a small part of the story. This overlooks all other actions and limits full measurement.
Imagine only thanking the person who handed you your diploma at graduation. You would be excluding the support and influence of parents, family, professors, and advisors. It does not make sense to discredit others who helped along the way.
Multi-Touch Attribution Models
Not all attribution models are the same. Choose a model, with an attribution tool, that accurately represents your customers’ typical journey. Here’s an examination of various attribution options, so you can find one aligned with your specific business requirements.
Linear Model
The linear model is simple and gives equal weight to every touchpoint along the customer journey. It’s straightforward. This can be helpful for companies with new attribution needs.
The downside of this method is no point is given any greater priority. All parts get the same amount of credit, no matter what the consumer does.
Time Decay Model
This model assumes that the actions taken closer to the purchase have a greater influence. Earlier touchpoints still receive credit, but their value diminishes over time.
Earlier interaction points aren’t completely disregarded, preventing an incomplete picture of the customer’s decision-making process. The earlier touchpoints get lower credit in the final results.
U-Shaped Model
This model emphasizes the importance of both the beginning and the end of the customer journey. The “U” shape indicates that 40% of the credit is given to both the first and last interactions. The remaining 20% is distributed among the touchpoints in between those points.
It prioritizes only a limited set of the entire customer journey. Those details that happen in the middle still have impact on the full view. It helps track things.
W-Shaped Model
This model is more complex and distributes credit across key stages of the customer journey. Here’s how the distribution breaks down:
- First touch.
- Lead creation.
- Opportunity creation.
These points and final touch all get more of the credit. For intricate B2B services, involving multiple stakeholders, this model could provide helpful insights on what caused a consumer’s decision.
Algorithmic Models: Letting the Data Speak
Algorithmic models leverage data, sophisticated math, and AI to eliminate guesswork. They assess the impact of each touchpoint and distribute credit accordingly. This often takes into consideration variables such as campaign settings, advertisements used, and other relevant factors.
This level of detail enables more granular recommendations and adjustments. For companies with vast datasets, that need automatic handling, would be perfect. Automation can help calculate results and what impacts they have.
Custom Models: Building Your Own Approach
For businesses where customers follow a less standard path, a custom attribution model gives flexibility. It helps to design a model aligned to how consumers interact and make a final choice. These fit requirements for unique circumstances.
Customizing may give better decisions. But it requires great time and dedication, to construct all rules from nothing. The building process has to consider many consumer factors.
Moving Beyond Multi-Touch Attribution to Alternative Measurement
Multi-touch models, in all their variations, depend on gathering individual user data to function correctly. Assigning credit to specific channels, times, or actions requires access to some level of personal information. It’s impossible to not do that.
A customer journey map, generated from multi-touch data, necessitates a connection point for tracking user behavior across multiple platforms. This often relies on tracking user habits. Modern web privacy standards and laws can affect this type of data collection.
Various alternative measurement options are emerging. Here’s a simple chart that shows different kinds of approaches, besides multi-touch attribution:
| Attribution Modeling Concept | Overview Description |
|---|---|
| Incrementality Testing | Involves testing real advertisements in authentic settings. Incrementality Testing assesses the effectiveness of ads in their natural context by evaluating how much ad spend contributes to increased purchases or conversions, beyond the baseline level achieved without advertising. |
| Cohort Analysis | Groups with similar characteristics are analyzed, revealing common purchase patterns. It shows bigger patterns without following the actions of just one person in isolation. |
| Media Mix Modeling (MMM) | This approach reviews historical advertising data. All of that past activity combines and is matched with sales data to figure out better strategies. This is used for fund usage, aiming for extra impact from money spent. |
| Geo-Testing | Divides regional testing. Some places will see new things. Testing shows effects from different marketing by keeping places unique. |
Incrementality, Your Next Frontier
Consider expanding your focus beyond assigning credit to individual touchpoints. Go to an assessment of the combined effectiveness of all marketing activities. Incremental testing helps find impact on full customer activity.
Begin by investigating the incremental value derived from different variables. This could include media channels or targeting strategies. Determine the influence of particular campaigns by quantifying the incremental changes they generate, encompassing all marketing tools and approaches.
Multi-Touch Attribution and The Changing Privacy Landscape
There are growing concerns about gathering so much data on individual behavior. Maintain consumer data rights at the forefront of the strategy. Data regulations continue to evolve.
Prioritizing Privacy: A Must-Do
Gathering data needs careful handling and to follow guidelines. Get consent before tracking and watching what users do online. Keep people aware of practices used.
Maintain open lines of communication with consumers about their rights. People’s information needs protection, respect, and must comply with any rules.
Adapting to a Cookie-less World
Web browsers increasingly block older data collection methods, like cookies set by one site and tracking a consumer to many other websites. IDFA identifiers are also disappearing. These actions show increasing concern over user information.
Traditional ways of multi-touch tracking can fail to track, going forward. Marketers should pivot and consider changing to newer approaches, for tracking data and campaign impact.
Using Multi-Touch Attribution (For Nonprofits)
It might appear that multi-touch attribution is only for normal business purposes. However, that’s not the case and is useful for non-profits, too. Multi-touch attribution is valuable for nonprofits in tracking donation journeys.
It offers useful information and thoughts about future planning and improvements. It connects donors, increases gifts, and helps the non-profit do more.
Conclusion
Multi-touch attribution aims to provide a comprehensive view of your marketing performance, moving beyond guesswork. Stop the guessing about campaigns. Custom multi-touch attribution models can give full reports for making smarter choices beyond first-touch and last-touch attribution.
Carefully assess the ongoing viability of gathering highly detailed user data. Consumer web privacy continues to grow with changing requirements. It impacts custom multi-touch capabilities, as real-time linear multi-touch attribution testing provides actionable insights and allows for rapid adjustments, with a different path to testing performance, and respects personal data by design.
