Best eCommerce Attribution Models

12/20/2023

In the realm of online retail, attribution models serve as invaluable tools for unraveling the complexities of consumer behavior. As we delve into the intricacies of eCommerce attribution models in this blog post, we will shine a spotlight on why ecommerce attribution is important, revealing how businesses can leverage these models to optimize marketing strategies and boost conversions, while also navigating their pitfalls and weaknesses. Understanding the limitations of attribution models is crucial for brands seeking a comprehensive view of their marketing landscape. Let’s dive in!

 

eCommerce graphic

 

 

Why is Attribution for eCommerce Important?

 

Attribution in eCommerce is crucial because it provides valuable insights into the customer journey and helps businesses understand the various touchpoints that contribute to a conversion. By accurately attributing sales or conversions to specific marketing channels, campaigns, or interactions, brands can optimize their marketing strategies and allocate resources effectively. Attribution aims to help eCommerce businesses identify the most impactful marketing channels, measure the ROI of their campaigns, and make data-driven decisions to enhance overall performance. Without proper measurement, it becomes challenging to determine which marketing efforts are driving success and which ones need adjustment. By gaining a comprehensive understanding of customer behavior and the factors influencing their purchasing decisions, eCommerce brands can tailor their marketing efforts to target the right audience at the right time, ultimately improving conversion rates and maximizing revenue.

 

 

Common eCommerce Attribution Models

 

Different attribution models offer different perspectives on how credit should be distributed throughout the customer journey. Here are some of the most common attribution models in eCommerce:

 

Last Click (or Last-Touch) Attribution

 

last-touch attribution graphic

 

In this model, all credit for a conversion is given to the last touchpoint or interaction before the purchase.

 

The pros of last click attribution:

 

The cons of last click attribution:

 

First Click (or First-Touch) Attribution

 

first-touch attribution graphic

 

This model attributes the entire conversion value to the first touchpoint or interaction in the customer journey.

 

The pros of first click attribution:

 

The cons of first click attribution:

 

Fractional (or Rules-Based) Attribution

 

fractional (or rules-based) attribution graphic

 

This model attempts to assign weights, factors or “rules” to give credit to different points in the funnel.

 

The pros of fractional attribution:

 

The cons of fractional attribution:

 

“U” and “W” Shaped Attribution

 

"U" and "W" shaped attribution graphic

 

This model also attempts to assign weights, factors, or “rules” to  give credit to different points in the funnel, usually by assigning more credit to the first and last ads in the sequence. In the “W”, more credit is given to the “mid-funnel” with the assumption that it contributes more too.

 

The pros of “U” and “W” shaped attribution:

 

The cons of “U” and “W” shaped attribution:

 

Algorithmic Attribution

 

algorithmic attribution graphic

 

This model is a more complex approach that sometimes uses predictive models and correlations to calculate across sequences, typically requiring an expensive 3rd party solution to provide marketing measurement.

 

The pros of algorithmic attribution:

 

The cons of algorithmic attribution:

 

 

Custom Attribution Models

 

Some brands opt to create their own attribution models tailored to their specific needs and objectives, which can be useful for those with unique customer journeys or specific marketing strategies that standard models may not capture accurately. However, this is extremely difficult to execute because it is time-consuming, resource-draining, and requires analytic expert(s).

 

 

How to Choose an Attribution Model for Your eCommerce Site

 

eCommerce website

 

Choosing the right attribution model for your eCommerce site involves considering various factors related to your business, customer journey, and marketing objectives. Here are steps to help you make an informed decision:

 

1. Understand Your Customer Journey

 

Analyze your customer journey to identify key touchpoints and interactions. Consider the typical stages a customer goes through before making a purchase. Understanding this journey is essential for choosing an attribution model that aligns with your customer behavior.

 

2. Define Your Goals

 

Clearly outline your business goals and what you want to achieve with your attribution model. Whether it’s increasing brand awareness, driving first-time purchases, or encouraging repeat business, your goals will influence the type of attribution model that makes the most sense for your objectives.

 

3. Consider Your Product and Sales Cycle

 

The nature of your products and the length of your sales cycle can impact the relevance of different attribution models. For products with a longer sales cycle, models that give credit to multiple touchpoints over time (e.g., time decay or position-based) may be more appropriate.

 

4. Review Existing Data

 

Examine historical data and performance metrics of your marketing channels under different attribution models. Consider how each model impacts the perceived effectiveness of your channels. This analysis can provide insights into which model aligns better with your actual customer behavior.

 

5. Test Multiple Models

 

Conduct A/B testing or use split testing to compare the performance of different attribution models. Implementing multiple models simultaneously can help you assess their impact on decision-making and understand which one provides the most actionable insights.

 

6. Be Adaptable

 

Consumer behavior and marketing landscapes change. Regularly reassess your chosen attribution model to ensure it remains relevant and aligned with your evolving business goals and strategies.

 

7. Utilize Technology and Analytics

 

Leverage analytics tools and technologies that support advanced attribution modeling. Some platforms offer built-in capabilities for experimenting with different models and visualizing the impact on conversion paths.

 

8. Seek Professional Advice

 

If you find the decision challenging, consider consulting with digital marketing experts or data analytics professionals who specialize in attribution modeling. Their expertise can provide valuable insights and guidance tailored to your specific needs.

 

Remember that the “best” attribution model is context-dependent and can vary from one eCommerce brand to another. It’s crucial to choose a model that fits your unique circumstances and supports your overarching business goals. Regularly reassess and refine your approach based on changing market dynamics and business requirements.

 

 

Weaknesses of eCommerce Attribution

 

"weaknesses" red button

 

While attribution models in eCommerce may offer valuable insights into the customer journey and the effectiveness of marketing efforts, they also have some inherent weaknesses and limitations. It is important to be aware of these challenges to make informed decisions and interpretations. Here are some common weaknesses of eCommerce attribution:

 

Simplification of Complex Customer Journeys

 

Attribution models often simplify the complexity of customer journeys by assigning credit to specific touchpoints. In reality, customer decision-making can be intricate, involving multiple channels and interactions. Attribution models may struggle to capture the full complexity of these journeys.

 

Overemphasis on Last Click Attribution

 

Last click attribution, while simple, tends to give disproportionate credit to the final touchpoint before conversion. This may overlook the contribution of earlier interactions that played a crucial role in influencing the customer’s decision.

 

Difficulty in Quantifying Brand Awareness

 

Metrics related to brand awareness, which may influence customer decisions indirectly over time, are challenging to quantify accurately using traditional attribution models. Building brand equity may not be adequately reflected in models that emphasize direct response channels.

 

Fixed Attribution Rules

 

Most attribution models operate on fixed rules, distributing credit based on predetermined algorithms. These fixed rules may not capture the dynamic and evolving nature of customer behavior, leading to inaccuracies in assigning credit.

 

Ignoring Cross-Device Behavior

 

Many customers use multiple devices during their journey, such as switching from mobile to desktop. Attribution models may struggle to track and consolidate these cross-device interactions, resulting in incomplete data.

 

External Factors and Market Dynamics

 

Attribution models often don’t account for external factors that can influence customer behavior, such as economic conditions, seasonal trends, or industry developments. These factors can significantly impact the effectiveness of marketing efforts.

 

Data Quality and Accuracy

 

The accuracy of attribution models depends on the quality of the data they rely on. Issues such as data discrepancies, incomplete data sets, or inaccurate tracking can compromise the reliability of attribution insights.

 

Limited Insight into Assisted Conversions

 

Some attribution models may not provide sufficient insight into assisted conversions, where multiple touchpoints contribute to a sale. This can make it challenging to understand the holistic impact of various marketing channels.

 

Subjectivity in Custom Models

 

Custom attribution models, while flexible, can be subjective and dependent on the biases of the model creator. Different stakeholders within an organization may have varying opinions on how credit should be assigned, leading to disagreements.

 

 

Best eCommerce Attribution Software

 

The bottom line is that any attribution software solution or model that relies on PII and/or consumer tracking is currently facing major issues with data loss and regulatory risks, and getting worse over time. These privacy related issues make traditional attribution using PII a bad fit for any brand, eCommerce-centric or not. 

 

Wondering if attribution models just might not be the best option for your brand? If that is the case, consider going beyond traditional eCommerce attribution models and into the world of Marketing Mix Modeling.

 

person jumping from ledge that says "traditional attribution models" to ledge that says "marketing mix modeling"

 

Moving away from touch-based attribution and utilizing Marketing Mix Modeling (MMM) in eCommerce presents several advantages:

 

Interested in learning more about how a Marketing Mix Modeling solution like OptiMine could help your eCommerce brand measure their marketing? Contact us today!

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