The benefits & drawbacks of linear marketing attribution

In today’s digital marketing landscape, understanding the customer’s journey is paramount to your success. One method that allows you to track this journey from the first point of contact to the final conversion is Linear Marketing Attribution.

It offers a fair and balanced approach, attributing equal importance to each touchpoint in the customer’s journey. This introductory guide will help you leverage the power of Linear Marketing Attribution, enabling you to optimize your marketing strategies, maximize ROI, and ultimately improve your bottom line.

What is linear attribution?

Linear Attribution is a model in digital marketing that assigns equal credit to each touchpoint in a customer’s journey towards conversion. This model is founded on the principle that each interaction – e.g. initial advertisement view, video view, email open, and final conversion – plays an equally significant role in influencing the customer’s decision. Therefore, by using linear attribution, marketers can gain a holistic view of the effectiveness of their campaigns across all channels, enabling them to make data-driven adjustments and optimize their strategies.

Benefits of linear attribution

The Linear Attribution model offers a multitude of benefits to marketers. First and foremost, it provides a more comprehensive view of the customer journey compared to single-touch attribution models. By equally distributing credit across all touchpoints, it allows for the assessment of the overall effectiveness of a marketing strategy, rather than focusing on individual interactions. This can lead to more accurate, well-rounded insights, empowering marketers to refine their campaigns and make more informed decisions. Furthermore, the model helps to eliminate biases towards certain channels or interactions, thereby encouraging a more balanced and fair evaluation of marketing efforts. As a result, businesses are better equipped to allocate their resources optimally, maximizing the potential for conversions and enhancing ROI.

Example of linear attribution

B2B linear attribution example

Let’s consider a hypothetical B2B marketing attribution scenario where a potential customer interacts with your brand five times before making a purchase.

1. Google Search Ad click
2. A few days later sees a sponsored LinkedIn post that generates a click to the website
3. This website visit generates a newsletter sign-up
4. A remarketing ad drives the user back to a case study page
5. Finally, an email converts the user to a free trial SaaS sign-up

In a Linear Attribution model, each of these five touchpoints would receive equal credit for the conversion. This means that the Google search ad, LinkedIn post, newsletter sign-up, display ad, and email click will each be attributed 20% (100% divided by 5 touchpoints) of the conversion credit. It clearly illustrates how each channel contributed to the final purchase, providing valuable insights for future marketing efforts.

B2C linear marketing attribution example

Let’s take another hypothetical scenario where a consumer has six interactions with your brand before making a purchase.

1. A user sees an Instagram ad and follows the link to your website.
2. Later, they stumble upon a Facebook ad that redirects them to your blog.
3. A few days later, they receive a push notification about a sale and visit the website but don’t make a purchase.
4. They read an email newsletter highlighting a customer testimonial that piques their interest.
5. A YouTube video review convinces them about the product’s value.
6. Finally, a personalized email offering a discount code motivates them to make a purchase.

In this Linear Attribution model, each of these six touchpoints would be attributed equal credit for the conversion. Each touchpoint, Instagram ad, Facebook ad, push notification, email newsletter, YouTube video, and the final personalized email, would each receive approximately 16.67% (100% divided by 6 touchpoints) of the conversion credit. This approach provides a comprehensive view of how each interaction influenced the customer’s decision, equipping marketers with invaluable insights for strategic planning and resource allocation.

Downside of linear attribution (in comparison to other attribution models)

While the Linear Attribution model offers a balanced view of customer interactions, it’s not devoid of drawbacks.

Its primary limitation lies in its assumption that all touchpoints within the customer journey are equally influential. This model fails to account for the potential varying significance of different touchpoints. For instance, a customer’s final interaction before the purchase might have a greater impact than an initial advertisement.

Moreover, it does not consider the unique impact of a touchpoint based on the customer’s stage in the buying process.

As a result, the insights gleaned may not entirely reflect the true effectiveness of individual marketing activities. Therefore, while the Linear Attribution model is a valuable tool for broad assessment, marketers should consider using it in conjunction with other models for a more nuanced understanding of their marketing effectiveness.

Linear attribution vs W, Z, or U-shaped attribution

Comparing Linear Attribution to W, Z, or U-shaped attribution models poses some interesting insights. These models assign varying weights to different touchpoints in the customer journey, providing a more nuanced view of conversion paths.

The W-Shaped model, for example, gives more weight to the first visit, the lead creation, and the opportunity creation stages, offering insights into the effectiveness of initial engagement and lead nurturing activities.

In contrast, the U-Shaped model assigns significant credit to the first and last interactions, while distributing the remaining credit equally among the middle touchpoints. This model recognizes the importance of the first interaction that piqued the customer’s interest and the last interaction that led to conversion.

Lastly, the Z-Shaped model, most suitable for B2B businesses with longer sales cycles, extends the W-Shaped model by adding another touchpoint – the customer close.

Each of these models provides more specific insights that can help marketers understand which touchpoints are most effective at different stages in the customer journey. Thus, while Linear Attribution offers a broad overview, the W, Z, or U-shaped models can provide a more detailed and nuanced understanding of your marketing strategy’s effectiveness.

What’s the best attribution model for you?

Choosing the best attribution model for your business depends on various factors, including the nature of your customer journey, your sales cycle length, and your marketing objectives. Shorter, simpler customer journeys might benefit from the simplicity of the Linear Attribution model, while longer, more complex journeys might require the nuanced insights offered by the W, Z, or U-Shaped models. Additionally, it’s important to remember that no single model will perfectly capture the intricacies of customer behavior. Therefore, it’s often beneficial to use multiple models in conjunction, providing you with a diverse range of insights and aiding in the development of a robust, data-driven marketing strategy.