Understanding the Last-Click Attribution Model: Pros, Cons, and Best Practices

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Today, we will dive into the last-click attribution model, the OG of marketing attribution models. It is very straightforward to implement but has limitations. Marketers can better understand and optimize the customer journey by understanding its strengths and weaknesses and integrating them into a broader attribution strategy. Most platforms, including Google Analytics, use this as their default attribution approach.

What is the Last-Click Attribution Model?

Last-click attribution as the name suggests assigns credit for a conversion to the last interaction by a customer before making a purchase. In this model, the entirety of the credit for a conversion is given to the last interaction that the customer engaged with before making a purchase or completing a desired action. This means that regardless of how many interactions occurred along the customer journey, the final touchpoint before conversion is considered the most significant and receives 100% of the credit.

How Does the Last-Click Attribution Model Work?

Here’s a step-by-step breakdown of how the Last-Click Attribution Model works:

1. Customer Journey Tracking: All customer interactions with your marketing channels are tracked and recorded. These interactions could include clicks on ads, visits to your website, email opens, social media engagements, and more.
2. Identification of the Last Touchpoint: Among all the recorded interactions, the last touchpoint before the conversion is identified. This could be the last ad clicked, the final email opened, or the last visit to your website.
3. Credit Assignment: The model assigns 100% of the conversion credit to this last touchpoint. All previous interactions are disregarded in terms of attribution.

For example, if a customer discovers your product through a Facebook ad but decides not to buy it. Later the customer changes his mind and clicks on a Google search ad to make a purchase. Finally, once the item is purchased the Google search ad will get 100 percent credit for the purchase.

Advantages of the Last-Click Attribution Model

• Simplicity: The Last-Click model is easy to understand and implement as it doesn’t require a lot of data analysis or advanced tracking.
• Focus on Conversion: Marketers can identify which channels are best for driving conversions by focusing on the last interaction.
• Clear Results: It provides clear and definitive results, making it easier to measure the direct impact of specific marketing efforts.
• Widely Supported: Many analytics and advertising platforms, such as Google Analytics and Facebook Ads Manager, support last-click attribution by default, making it a convenient choice for marketers.

Disadvantages of the Last-Click Attribution Model

• Ignores the Customer Journey: This model needs to consider the influence of earlier interactions, which can provide valuable insights into the customer journey. Early interactions like initial ads or awareness campaigns play a critical role in shaping customer decisions but receive no credit.
• Overemphasis on Last Interaction: Giving all credit to the last interaction, may lead to underestimating the importance of other channels that play a significant role in building awareness and consideration. This can result in skewed perceptions of which marketing efforts are most effective.
• Potential Misallocation of Budget: Relying solely on last-click data may result in misallocating marketing budgets, neglecting channels that contribute to long-term brand building and customer engagement. For instance, channels that are crucial for awareness and nurturing might be underfunded because their impact isn’t directly visible in last-click analysis.

Best Practices for Using this Model

• Analyze Conversion Paths: Examine the entire conversion path to understand the role of each interaction, rather than focusing solely on the last interaction. Tools like EasyInsights can help map out these paths and provide deeper insights.
• Use for Specific Campaigns: The Last-Click model can be particularly useful for short-term, direct-response campaigns where the goal is immediate conversions. For instance, flash sales or time-limited promotions where the final interaction is crucial can benefit from this model.
• Regularly Review and Adjust: Continuously monitor and adjust your attribution strategy based on campaign performance and evolving marketing goals. Regular reviews can help identify if the Last-Click model is still providing valuable insights or if adjustments are needed.
• Combine with Other Models: Think of last-click as a single piece of a larger puzzle. While it reveals the final move in a customer’s journey, it doesn’t show the entire picture. Here’s where last-click excels when used in conjunction with other attribution models:

• First-Touch Attribution: This model sheds light on the initial interaction that sparked a customer’s interest. Used together, you can see how the initial spark (e.g., a social media ad) interacted with the final push (e.g., a retargeting ad) to drive the conversion.
• Multi-Touch Attribution: This model goes a step further, assigning credit to all the interactions a customer interacts with on their way to conversion. Combining it with last-click allows you to see the complete customer journey, giving insights into which channels are most influential at different stages.

When to Use the Last-Click Attribution Model

Last-click attribution offers a clear-cut answer to a crucial question: what drove that conversion?  That being said, it can miss the broader narrative. Here are instances when the last click model may be beneficial and when you may need to explore other attribution models:

• Limited Resources:  For marketing teams with limited resources or technical expertise, the simplicity of last-click attribution is a major perk. Data is readily available in most marketing platforms, requiring minimal setup and analysis. This makes it a user-friendly option for startups or businesses just getting started with attribution.
• Direct Response Campaigns or Flash Sales: Campaigns focused on driving immediate actions, such as sales promotions or time-sensitive offers, the Last-Click model can provide clear insights into what drove the final action. It is particularly effective for understanding the final push that led to a conversion.
• Complementary Analysis: By understanding the strengths and limitations of the Last-Click Attribution Model, marketers can better decide when and how to use it effectively. While it offers simplicity and clear insights into direct conversions, integrating it with broader attribution strategies ensures a more comprehensive understanding of the entire customer journey. This balanced approach can lead to more informed decision-making and optimized marketing efforts.

Alternatives to Last-Click Attribution

To address the limitations of last-click attribution, marketers often turn to other models that provide a more holistic view of the customer journey:

• First-Click Attribution: This gives all of the credit to the first click, regardless of the length of the conversion path, and whether or not that marketing campaign directly influenced the sale. 
• Linear Attribution: This distributes credit for the conversion evenly across every click in a user’s journey.
• Time-Decay Attribution: According to this, the closer the click is to the conversion, the more credit it gets. This model uses a complex algorithm to distribute and attribute the credit to the useful interactions, taking note of the interactions or channels that were in the closest proximity of the conversion, and working backward. It lays more emphasis and assigns more and more credits as the interactions arrive at the conversion.
• Position-Based Attribution (U-Shaped): This assigns the maximum ( about 40%) of the credit to the first- and last-click and distributes the remaining 20% of credit points across the other ad clicks.

Also Read: Which Attribution Model should you be using for Google Ads

To Conclude

While the last-click attribution model offers simplicity and clarity in identifying the direct driver of conversions, its reliance solely on the final interaction overlooks the broader narrative of the customer journey. Ultimately, a balanced approach to attribution leads to better insights, improved resource allocation, and enhanced marketing performance.

Amidst this need for a more comprehensive attribution model and the evolving digital landscape, future-proofing your marketing strategy is essential, especially with the phasing out of third-party cookies. EasyInsights offers a reliable solution for attribution challenges, leveraging server-side tracking to gather first-party data. This enables seamless navigation of digital complexities and unlocks valuable insights for growth.

Book a demo to learn more.