Marketing Attribution Models 101: Understanding the Impact of your Ads

Marketing Attribution Models 101: Understanding the Impact of your Ads

Afe Mevhare

Afe Mevhare

Reporting & Analysis


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Marketing attribution models help marketers understand how different marketing efforts (ads, social media posts, etc.) contribute to sales. By assigning credit to each touchpoint a customer has with your brand before buying, marketers can see which tactics are most effective. There are two main attribution approaches: single-touch models (crediting one touchpoint) and multi-touch models (crediting multiple touchpoints). Choosing the right model depends on your business goals, customer journey complexity, and the data you have available.

When we talk about understanding the impact of our ads, we're really asking a simple question: "Which of our ads are convincing people to take action, like making a purchase or signing up for more information?" This is where marketing attribution comes into play. It is a process of identifying and crediting different or multiple touchpoints or points in a customer purchase journey. It's an important way of figuring out which parts of your marketing campaigns or marketing channels are working the best.

Attribution models define how each touchpoint is given (or attributed) credit for each conversion. They help us see not just the impact of a single ad but how all our ads work together to influence someone's decision. Choosing the right model can make a big difference in how well we understand our marketing efforts and, more importantly, how we make them better over time.

Approaches and Types of Marketing Attribution Models

When we start looking closer at how to track the effectiveness of our ads, we come across two main approaches: Single-Touch Models and Multi-Touch Models. Let's play out a hypothetical customer journey across different ad touch points of a person named Alex before purchasing a pair of running shoes.

  1. First Touch: Alex sees a Facebook ad for the shoes while browsing their feed.

  2. Middle Touches:

    • Alex later searches for reviews and finds a Google search ad linking to a blog post comparing different brands.

    • A week later, Alex watched a YouTube review about the shoes after seeing a video ad.

  3. Last Touch: Finally, Alex receives an email with a promotional offer and clicks on the link to buy the shoes.

Single Touch Attribution Model

These models simplify things by focusing on one key moment in a customer's journey to making a purchase or taking action. They're like putting a spotlight on either the first impression or the last push that leads to a decision. Examples are:

  1. First-Click Attribution Model: Also known as the first touch attribution model. This shines a light on the very first ad that a customer interacted with.

    This model gives all the credit to the Facebook ad, the very first touchpoint that introduced Alex to the shoes.

    Measure your store's sales performance by first-visit UTMs.

  2. Last-Click Attribution Model: Also known as the last interaction attribution model. This is all about the final nudge.

    The last ad the customer clicked before making a purchase gets all the credit. This model assigns all the credit to the email that Alex clicked right before making the purchase.

    Measure your store's sales performance by last-visit UTMs.

Track your Shopify Sales Performance by First and Last-Visit UTMs.

Track your Shopify Sales Performance by First and Last-Visit UTMs.

Track your Shopify Sales Performance by First and Last-Visit UTMs.

Track your Shopify Sales Performance by First and Last-Visit UTMs.

Multi-touch Attribution Model

These different attribution models do, on the other hand, recognize that the journey from first seeing an ad to taking action is rarely a straight line. They spread the credit across multiple points, acknowledging that it often takes a series of interactions to lead to a decision. Examples are:

  1. Linear Attribution Model: This model divides the credit evenly among all the ads a customer interacts with.

    In this model, the Facebook ad, the Google search ad, the YouTube video, and the email would all share equal parts of the credit for influencing Alex’s decision.

  2. Time Decay Attribution Model: This model places increasing importance on the ads closer to the purchase.

    So, while the Facebook ad and the Google search ad would get some credit, the YouTube video and especially the email would be deemed more crucial in driving Alex to make a purchase. The closer to the purchase, the more credit the touchpoint receives.

  3. Position-Based Attribution Model: Also known as U-shaped, this model recognizes the special roles of the first and last touchpoints but also gives credit to the middle interactions.

    In Alex’s case, both the initial Facebook ad and the final email would receive a larger share of the credit (say, 40% each), and the remaining 20% would be split between the Google search ad and the YouTube video. This approach acknowledges the importance of sparking interest and sealing the deal, while still valuing the journey in between.

  4. Data-Driven Attribution Model: This assigns conversion credit by analyzing the actual data from each interaction in the conversion path, rather than following preset rules. This method tailors attribution to your specific account data, providing a nuanced view of each click's contribution.

    In Alex's journey to buy running shoes, which included ads on Facebook and YouTube, followed by an email promotion, data-driven attribution might reveal that, although the email was the final touch, the YouTube ad had a significant impact on Alex's decision. This approach allows for more precise budget allocation, emphasizing the true influence of each ad based on real interactions. This attribution model is accessible in Google Analytics.

Understanding Attribution Windows

An attribution window is essentially the timeframe used to determine which advertisements effectively lead to conversions. The length of this window is crucial - too short, and you might overlook influential ads from earlier on; too long, and irrelevant ads could receive undue credit. The ideal duration varies based on the product and the typical decision-making time of your customers. Regular adjustments to this window are necessary as you gain insights into your customers' behaviors, ensuring you accurately assess the impact of your advertising efforts. By fine-tuning the attribution window, marketers can better allocate their budget to the most impactful ads, optimizing their overall advertising strategy.

Let's consider Alex, who took a month from seeing the first ad for running shoes to making a purchase. If we set an attribution window of just one week, we'd miss the initial Facebook ad that sparked Alex's interest. But with a month-long window, we can capture the entire journey, from the first Facebook ad to the final email that led to the purchase. Adjusting the window to match Alex's decision-making process ensures we understand which ads truly influenced the buying decision.

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Criteria for Selecting an Attribution Model

Choosing the right attribution model is crucial before performing any data analysis. You want to make sure it fits your marketing strategy, goals and gives you the best insight into your ad campaigns. Here are some things to consider:

Business Goals

Determining which attribution model to use starts with understanding your primary business goals. If spreading awareness about your brand is your top priority, the First-Click Attribution model can highlight the crucial role of initial advertisements in introducing your brand to potential customers. On the flip side, if your aim is to boost sales, the Last-Click Attribution model offers valuable insights into which ads are effectively closing sales. For brands aiming to foster deeper engagement across various platforms, the Linear Attribution model presents a comprehensive view by equally valuing each touchpoint along the customer's journey.

Understanding Customer Journeys

The complexity of your customer's decision-making process also plays a pivotal role in model selection. Single touch models, such as First-Click or Last-Click, are best suited for straightforward, quick decisions due to their focus on a singular influential touchpoint. Conversely, more intricate decision processes that involve thorough research and consideration benefit from multi-touch models like Linear, Time Decay, or Position-Based, as they provide a more detailed picture of the customer's entire journey.

Data Availability

The extent of your data collection capabilities can significantly influence the choice of an attribution model. Limited data suggests starting with a simpler approach, such as Last-Click Attribution, to glean actionable insights without becoming bogged down. However, with a more robust data infrastructure, you can harness the nuanced insights offered by complex models that account for multiple interactions across the customer journey.

Marketing Channels Used

The selection of an attribution model should also consider the diversity and role of marketing channels in your strategy. If your approach is heavily weighted towards a particular marketing channel at the start or end of the customer journey, single touch models can underscore the impact of these critical touchpoints. Meanwhile, strategies that incorporate a variety of channels throughout the journey necessitate multi-touch models to accurately assess the contribution of each channel to the final outcome.

Navigating Challenges in Marketing Attribution

When it comes to figuring out which of your ads are working best, you're bound to run into some challenges. Here are some ways to tackle these issues:

Dealing with Data Overload

Sometimes, you have so much information that it's hard to make sense of it all. It's like trying to find a needle in a haystack. The key is to focus on the data that matches your goals. If you're trying to boost sales, concentrate on the ads that lead directly to purchases. Tools that simplify data analysis can also be a big help, turning that overwhelming data into clear insights.

Non-linear Customer Journeys

Customers rarely take a straight path from seeing an ad to making a purchase. They might see an ad on one device but buy on another, or they might take days or weeks to decide. To get around this, use models that consider the whole journey, not just the last ad they clicked. Surveys can also help you understand how customers really make their decisions.

Omnichannel Attribution

Not all ads are online; some might be on TV, radio, or billboards. It's tricky to track these the same way you do with online ads. Digital tracking methods like QR codes printed on product packaging, or coupons mentioned only in certain ads, can also link offline marketing efforts to online actions. However when considering the entirety of your marketing efforts, you may wish to shift the focus away from attribution, and towards identifying your Marketing Efficiency Ratio instead

Read: What is Marketing Efficiency Ratio (MER)?

Keeping Up with Privacy Regulations

With rules around customer privacy getting stricter, collecting data can be tough. The key is to be transparent with your customers about what data you’re collecting and why. Offering value in exchange for their data, like exclusive content or discounts, can also encourage customers to share the info they need.

Afe Mevhare

About the Author

Afe is the Growth Analyst at Airboxr. He works on internal data analysis and reporting and works with the team to develop customized reports for DTC brands. He is passionate about data and enjoys music.

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