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Attribution 101: Navigating Popular Marketing Attribution Models

You've probably heard of the concept 'attribution', which is a very common concept in digital marketing and at Billy Grace. But what is it? And what models exist? In this blog, we'll clarify each model and discuss their importance as well as their downsides. But first, we need you to understand what marketing attribution is. So, without further ado:

1. Understanding Marketing Attribution

To start explaining this, we first need to establish the fundamentals of marketing attribution, which begins with the customer journey. Imagine a customer’s journey as a story, starting when they first learn about a product and ending with a purchase or other conversion goal. Each step is a point where they interact with a brand – through an ad, a website visit, or a store experience.

“Why is it important?”

Marketing attribution aims to understand which of these steps were most influential in leading the customer to buy, helping businesses refine their marketing strategy for better results.

To better understand marketing attribution, think of each marketing channel (like social media, email campaigns, or Google search) as a player on a soccer team. The ultimate goal for both marketing channels and soccer players is to score – in marketing, this means achieving a conversion.

In a football match, when a goal is scored, the question arises: who gets the credit? Is it just the striker who scored, or also the players who passed the ball, set up the play, or even the goalkeeper who initiated the attack? Similarly, in marketing attribution, the challenge is to determine which channel deserves credit for leading to a conversion.

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The attribution aspect within marketing is akin to post-match analysis. It examines the entire play (or customer journey) to decide how much credit each channel gets for the conversion. Some models may give all credit to the final channel that directly led to the sale (like crediting only the striker). Others might distribute credit among various channels that played a part in the journey, acknowledging the roles of those who assisted in building up to the conversion. This understanding helps marketers invest wisely in the most effective channels.

2. Traditional Attribution

With traditional attribution, you manually assign the most important part of the customer journey. If you think the most important part of the journey is the converting ad, then you could use last-click attribution.

Last-Click Attribution

Focusing on the last-click method, we specifically look at the last ad a person clicked on before making a purchase. So, in soccer terms: the one who scores is king.

Consider this scenario: A person spots a laptop ad on a YouTube video, later reads a blog post about the same laptop, and eventually clicks on a link in a promotional email. If, after all these interactions, the person decides to buy the laptop, last-click attribution would highlight the email promotion as the influential factor, because it was the final click before the purchase.

By using this technique, businesses can determine which of their marketing strategies are best at sealing the deal with potential customers.

3. Data-Driven Attribution models

Using a data-driven attribution approach means diving deep into user data to understand the role of each advertisement in the customer’s journey. Unlike methods that focus just on the last interaction, this method takes all online touchpoints a customer has with a brand into account. If we go back to the soccer analogy, this would mean analyzing every player on the field and taking everyone’s participation into account.

This method is particularly suitable for businesses with abundant data and complex customer journeys. It offers a holistic view of your marketing impact, allowing adjustments and refinements to your strategies based on comprehensive data insights.

There are 3 important data-driven attribution models which we will discuss: Multi-Touch Attribution (MTA), Marketing Mix Modeling (MMM), and Unified-Marketing Measurement (UMM).

Multi-Touch Attribution (MTA)

MTA accounts for all online touchpoints in the customer journey, from the first click on an ad to the purchase (Note: this model only uses clicks to measure everything), and assigns credit to each of the channels. The real benefit of MTA is that it provides a more granular view than other methods, and it helps marketers improve customer experience with insights that can be implemented on a tactical level. Furthermore, it aids in achieving a higher ROI by eliminating low-performing channels.

The pros of MTA include its ability to offer a comprehensive understanding of the customer journey by considering all touchpoints across various channels. This approach allows for a more accurate measurement of the ROI of each marketing channel by attributing value to each individual touchpoint. However, there are challenges. Implementing and managing MTA can be complex, especially for businesses operating across numerous channels and touchpoints. Additionally, MTA relies on high-quality, granular data for accurate attributions. A lack of such data or the inability to accurately track all touchpoints can lead to inaccurate results, undermining the effectiveness of this model. Lastly, since MTA relies solely on clicks, branding campaigns focused on views rather than clicks are excluded from this equation.

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Marketing Mix Modeling (MMM)

MMM offers insights into all the offline touchpoints, as it doesn’t just evaluate ad performance in isolation but also considers external factors influencing sales, such as pricing changes, economic conditions, and even weather patterns. For example, an umbrella might sell more during the rainy season, but is it because of a clever ad, or simply because it’s raining?

The pros of MMM include being an effective tool that provides a foundational starting point for high-level, overall marketing budget planning and offering a much-needed holistic view of general marketing trends, giving a 360-degree perspective. However, its limitations are notable: MMM lacks a granular view of marketing data, and its effectiveness and accuracy hinge on the scale of the company and its media budget, requiring significant data to be meaningful.

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Unified-Marketing Measurement (UMM)

UMM blends Multi-Touch Attribution (MTA) and Marketing Mix Modeling (MMM) for a holistic marketing analysis.

By merging both online and offline marketing, it unifies media data and sales channels, facilitating better insights into marketing performance on a strategic as well as a tactical level. Unlike MTA, UMM incorporates views (similar to MMM) in addition to clicks, addressing one of MTA’s limitations (its exclusive reliance on clicks).

UMM is a contemporary approach that addresses challenges such as user-level data in a future without cookies and is prized for enhancing omnichannel marketing, making it a preferred choice for marketers seeking comprehensive insights into their efforts. It is a more advanced combination of MTA and MMM, as it takes the strengths of both. We believe this is currently the best attribution model as it provides the most insights into performance.

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In conclusion, there are many attribution models, each with its unique capabilities. But in our view, one model stands out, which is UMM. It combines the best of the data-driven attribution models and negates each downside of the others. Want to know more about attribution or other topics within digital marketing? Visit our website.

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