Understanding the effectiveness of various marketing efforts and campaigns is crucial in digital marketing. Businesses must determine which interactions bring them customers. One method that provides valuable insights into consumer interactions is last touch attribution.
Understanding the effectiveness of various marketing efforts and campaigns is crucial in digital marketing. Businesses must determine which interactions bring them customers. One method that provides valuable insights into consumer interactions is last touch attribution.
Last touch attribution assigns credit to a customer's last interaction with a business before making a conversion. This model determines which touchpoint prompts a user to take the desired action, whether it's making a purchase, signing up for a newsletter, or any other lead generation or conversion goal.
While marketing efforts often involve a series of touchpoints across various channels, the last touch attribution model brings clarity by pinpointing the final interaction that sways the customer's decision.
This attribution model plays a pivotal role in marketing, assigning credit to only one interaction. However, there are many types of marketing attribution, and the one you choose will ultimately depend on your goals. Keep reading to learn about the last touch attribution model and how it works.
What is last touch attribution?
Last touch attribution is an attribution model in digital marketing that assigns credit to a customer's last interaction with a brand before making a purchase or conversion.
In this model, the final touchpoint in the customer journey, whether it's a click on an ad, a visit to a website, or another interaction, is considered the decisive factor leading to the desired action, such as a purchase, sign-up, or converting website visitors into customers.
While other touchpoints throughout the sales funnel may have contributed to building awareness and consideration, last touch attribution focuses on the last touchpoint that directly precedes the conversion event. This model offers a clear and straightforward way to identify the touchpoint influencing a customer's decision to take a specific action.
How does last touch attribution work?
Again, the last touch attribution model gives full credit to whichever marketing channel a customer interacted with right before they converted. Every other touchpoint they encountered along the way gets zero credit.
Here's how the process typically unfolds:
Your marketing analytics platform tracks every interaction a customer has with your brand. When someone converts — whether they make a purchase, fill out a form, or complete another goal — the system looks back at their activity.
It identifies which channel they came from immediately before converting, like a paid search ad, an email campaign, or a social media post. That final channel receives 100% of the credit for the conversion.
Let's say a customer first discovers your brand through a Facebook ad, later reads a blog post from organic search, then receives an email promotion, and finally clicks a Google ad before making a purchase.
With last touch attribution, only that Google ad gets credit. The Facebook ad, blog post, and email all contributed to the journey, but they're invisible in this model.
This approach makes reporting straightforward. You can quickly see which channels are closing sales and allocate budget accordingly. However, it only tells you part of the story about what's actually driving your conversions.
Pros and cons of the last touch attribution model
The last touch attribution model is popular because there's only one marketing touchpoint you have to worry about.
However, your marketing efforts create many touchpoints; without monitoring them, you won't know how effective they are. While the last touch attribution model is practical and straightforward, it has limitations.
The pros of the last touch attribution model include the following:
- Simplicity: One of the main advantages of last touch attribution is its simplicity. It offers a straightforward approach to attributing conversions by focusing solely on the last touchpoint. This simplicity makes it easy to understand and implement.
- Ease of implementation: Last-touch attribution is more accessible to implement than complex multi-touch attribution methods. It requires less intricate tracking and analysis, making it accessible for businesses with limited resources or those looking for a quick initial attribution solution.
- Clarity in the last touchpoint: The model provides clear visibility into the last touchpoint that directly precedes a conversion. This clarity helps businesses identify the most effective channels or campaigns to drive customers to take the desired action.
The cons of last touch attribution models include the following:
- Oversimplification of the customer journey: A significant limitation of the last touch attribution model is its tendency to oversimplify the customer journey. Focusing only on the last interaction ignores the complexity of multiple touchpoints that contribute to customer awareness, consideration, and decision-making.
- Ignoring earlier touchpoints: The last touch attribution model disregards earlier touchpoints, contributing to brand awareness and consideration. This can lead to a skewed understanding of the customer journey, as the model neglects the impact of interactions before the final touchpoint.
- Potential misattribution: Last touch attribution assumes that the last interaction is the most influential in driving a conversion. However, this may not always be accurate, especially in cases where customers engage with various touchpoints before making a decision. Misattributing the entire credit to the last touchpoint can lead to inaccurate insights and decision-making.
When should you use last touch attribution?
Last touch attribution is particularly well-suited for specific scenarios where the customer journey is shorter and more direct, and the final touchpoint significantly influences the conversion decision.
A few situations in which last touch attribution makes sense include:
- E-commerce and online sales: Last touch attribution is commonly used in e-commerce and online sales environments. In these settings, customer journeys often involve quick decision-making processes, making it more feasible to attribute conversions to the last touchpoint.
- High-impact last touchpoints: When a business identifies specific touchpoints that consistently impact driving conversions, last touch attribution becomes valuable. This is particularly relevant when a specific channel or campaign consistently serves as the final catalyst for conversions.
- Limited-time offers: Campaigns featuring limited-time offers or promotions often have a sense of urgency, compelling customers to make quick decisions. In such cases, last touch attribution can attribute conversions to the last touchpoint, clarifying the impact of time-sensitive incentives.
- Abandoned cart recovery: The final interaction that successfully brings a customer back to complete a purchase is crucial for businesses implementing abandoned cart recovery strategies. Last-touch attribution helps in recognizing and attributing conversions to these recovery efforts.
- Promotional landing pages: When businesses create targeted promotional landing pages designed specifically for conversion, last touch attribution can highlight the effectiveness of these pages as the final step in the customer journey.
Comparing last touch to other attribution models
Last touch attribution isn't your only option. Different marketing attribution models assign conversion credit in different ways, and each one reveals something unique about how your channels work together. Here's how the main alternatives compare:
Attribution model | How it works | Best for |
Last touch | Gives 100% of the credit to the final interaction before conversion | Identifying what directly drives conversions |
First touch | Assigns all credit to the first interaction a customer has with your brand | Measuring awareness and top-of-funnel performance |
Linear | Distributes credit evenly across every touchpoint | Understanding the full customer journey |
Time decay | Gives more credit to interactions closer to conversion | Shorter sales cycles or fast-moving campaigns |
Data-driven | Uses machine learning to assign credit based on actual performance data | Teams with enough data to uncover deeper insights |
First touch attribution
First touch attribution is the complete opposite of last touch — it gives full credit to the first interaction a customer has with your business. If someone discovered you through a LinkedIn post six months ago and later converted through a Google ad, that LinkedIn post gets all the credit.
This model helps you understand which channels are best at introducing new people to your brand. The downside is that it ignores everything that happened between that first interaction and the final conversion.
Linear attribution
Linear attribution, a type of multi-touch attribution model, spreads credit evenly across every touchpoint in the customer journey. If someone interacted with five different channels before converting, each channel gets 20% of the credit.
This approach acknowledges that multiple channels contribute to conversions. However, it assumes all touchpoints are equally important, which isn't always true. The ad someone clicked right before purchasing probably had more influence than a blog post they read three weeks earlier.
Time decay attribution
Time decay attribution assigns more credit to the touchpoints that happened right before the conversion. The most recent interaction gets the most credit, and earlier touchpoints receive progressively less.
This model works well for businesses with a short sales cycle where recent interactions matter most. You still get visibility into the full journey, but with a weighted perspective that favors recency and helps you allocate ad spend more effectively.
Data-driven attribution
Data-driven attribution uses machine learning to analyze your actual conversion data and determine how much credit each touchpoint should receive. Instead of following a predetermined formula, the algorithm looks at patterns to figure out which channels and sequences actually lead to conversions.
This is the most sophisticated approach, but it requires substantial data to work properly. When you have that volume, data-driven attribution can reveal insights that simpler models miss entirely.
Best practices for using last touch attribution
When leveraging last-touch attribution to understand the dynamics of customer conversions, certain best practices can enhance its effectiveness. Recognizing that attribution models serve as tools rather than one-size-fits-all solutions is crucial.
Here are a few best practices for optimizing last touch attribution in your marketing strategy:
Combining models for a holistic view
Don't rely on last touch attribution alone. Use it alongside other models like first touch or linear attribution to get a more complete picture of your customer journey.
Last touch shows you which channels close deals, while first touch reveals where customers discover you. When you compare insights from multiple models, you can make smarter decisions about budget allocation and campaign optimization.
This approach helps you avoid over-investing in bottom-of-funnel tactics while neglecting the channels that drive initial awareness.
Tailoring attribution to your industry dynamics
Your industry and business model should influence which attribution approach you use.
Last touch attribution works well for businesses with shorter sales cycles and direct customer paths, like e-commerce or online services. However, if you're in B2B software or another industry with complex, multi-month buying processes, last touch alone won't give you the full story.
Consider how long your typical sales cycle runs and how many touchpoints customers usually encounter before converting. Match your attribution strategy to these realities instead of forcing a model that doesn't fit.
Using CRM data to validate attribution insights
Your CRM holds valuable information that can confirm or challenge what your attribution data suggests. Look at closed deals in your CRM and trace them back through the customer journey.
Do the conversion paths match what your attribution model indicates? If sales reps consistently mention that customers discovered you through webinars but last touch attribution points to paid search, there's a disconnect worth investigating.
Combining CRM insights with attribution data helps you spot gaps and refine your understanding of what actually drives conversions.
Setting up conversion windows for better accuracy
Conversion windows determine how far back your attribution model looks when assigning credit. If you set a 30-day window, any interaction older than 30 days won't count toward the conversion.
The right window depends on your sales cycle length. E-commerce businesses might use 7-14 day windows since purchase decisions happen quickly.
B2B companies often need 60-90 day windows or longer to capture the full buying journey. Test different window lengths and see which one best reflects your actual customer behavior patterns.
Get a better understanding of the customer journey
Understanding the dynamics of the customer journey is fundamental to optimizing marketing strategies, and last touch attribution can be a valuable tool in determining the effectiveness of various touchpoints.
While last-touch attribution simplifies the path to conversion, businesses must acknowledge its limitations and explore alternative attribution models for a deeper understanding.
Achieving a comprehensive understanding of the customer journey requires data. With Mailchimp, you'll have all the data you need to learn more about your customers and the effectiveness of your marketing campaigns.
Use our analytics, automation, and integrations to gain deeper insights into customer interactions, optimize touchpoints, and refine your marketing strategy for sustained success.