Marketing attribution is the practice of assessing and monitoring the effectiveness of your various marketing channels.
The ultimate objective of marketing attribution is to get a deeper understanding of all the different interactions & touchpoints that customers have with your brand on their journey to making a purchase.
By identifying the specific marketing channels and campaigns that have contributed to a conversion, you can make better decisions about where to allocate your resources and invest your time and money.
However, while this may seem easy in theory, effectively tracking and analyzing marketing touchpoints can be challenging in practice, despite the rise of marketing attribution software designed to help with this task.
In today’s world, marketing attribution is getting even more difficult for a couple of reasons such as:
- People tend to own multiple devices, such as smartphones, tablets, computers, and smart home devices. This means that the same customer may be counted as multiple visitors to a website, leading to inaccuracies in attribution data.
- There is a growing trend towards greater privacy and security in the digital landscape. Devices and web browsers are becoming more cautious about the types of user information and tracking data they allow to be stored as a result of GDPR regulations.
- The majority of attribution models used in marketing rely on click-based metrics to measure customer engagement. This approach is based on tracking user behavior using UTM parameters, which can lead to an incomplete understanding of customer interactions.
Does Perfect Marketing Attribution Exist?
It’s important to admit that there’s no such thing as 100% “true” marketing attribution.
Attribution models are designed to provide an approximation of how customers interact with different marketing channels, but they are not a perfect reflection of the real world.
There are many factors that can influence customer behavior, and it can be difficult to measure the impact of each one accurately and give credit for each touchpoints.
However, by using attribution models to gain a general understanding of how different marketing channels are performing, you can make much better decisions about how to use your resources and improve your marketing strategies over time.
While attribution modeling may not provide a complete picture, it can still be a valuable tool for you to get insights into customer behavior and improve overall marketing effectiveness.
To achieve accurate attribution modeling, there are a few key areas that you need to focus on:
- Set up tracking tools correctly & properly
- Make sure to have a consistent & decent system for UTM tagging and tracking
- Understand the strengths and limitations of different attribution models
Types of Attribution Marketing Attribution Models
There are several different models that you can choose from, depending on your specific goals and priorities.
In general, there are seven different types of attribution models that you can use to get a better picture of different marketing touchpoints throughout the customer journey.
Each model has its own strengths and limitations, and it's important to carefully consider which one is most appropriate for your needs.
By selecting the right attribution model, you can gain a clearer understanding of how different marketing channels are performing, and make more informed decisions about how to utilize your resources to drive better results.
1. Last click attribution
It is one of the most widely used marketing attribution models, which is often the default option for many marketing platforms and attribution tools.
This model is particularly useful if you focus on driving conversions, as it assigns all of the credit for a conversion to the last ad that a customer clicked on, along with the corresponding keyword.
While this approach can provide valuable insights into which lower-funnel campaigns are most effective at driving sales, it can also be somewhat limited in scope.
As last-click attribution ignores any interactions that customers may have had with other ads or channels along their journey, it may not provide a complete picture of how different touchpoints are contributing to overall success.
2. First click attribution
This is a single-touch attribution approach that assigns all of the credit for a conversion to the first touchpoint that a customer encounters on their journey.
This model is particularly useful if you focus on building traffic and reaching new audiences, as it prioritizes spending on campaigns that can help achieve those goals.
Yet, it can also be somewhat limited in scope, as it ignores any interactions that customers may have had with other ads or channels along their journey.
3. Last non-direct click attribution
This model assigns credit to the last touchpoint that a customer interacts with before making a purchase on your site, excluding direct traffic.
It assigns all credit to that touchpoint, such as an email campaign or social media ad, which helps filter out direct traffic, allowing you to focus on the last marketing activity that led to the conversion.
By using the last non-direct click model, you can more accurately determine which marketing activities are driving conversions and make more informed decisions about your marketing strategy.
4. Linear attribution
It gives equal credit to each touchpoint in a customer's journey to purchase. This means that all marketing interactions are given importance in the path to conversion.
While this model ensures that no interactions are missed, it may not give a clear indication of which marketing channel had the greatest impact on the final purchase decision.
Nonetheless, the linear model provides a simple and straightforward approach to multi-touch attribution.
5. Time decay attribution
This is a multi-touch attribution model that gives credit to interactions leading up to conversion, giving more weight to clicks that occurred closer in time to the conversion.
This model is similar to last-click attribution, but it distributes credit across all touchpoints on the customer's journey, rather than just the last click. The closer in time a touchpoint is to the conversion, the more credit it receives.
6. Position-based attribution
It gives equal importance to the first and last click on a customer's path to purchase. Specifically, each of these interactions is given 40% of the conversion credit, while the remaining 20% is distributed equally among the other clicks in between.
According to this model, the first and last clicks are the most valuable interactions in a customer's journey, but it does not necessarily take into account other significant touchpoints in the middle.
7. Algorithmic attribution
It’s a flexible and adaptive approach to attribution that relies on machine learning algorithms to analyze historical data and allocate credit across different touchpoints based on their contribution to the overall customer journey.
While this model can provide the most accurate and insightful results, it requires a large amount of historical data to work effectively. Additionally, it can be challenging to interpret the outputs of a custom attribution model without a solid understanding of the underlying algorithms and data analysis techniques.
Discrepancies Between Platforms
It is all about how different marketing platforms might provide different values and credit for conversions depending on the report you look at.
All of the reports generated on platforms such as Google Ads, Facebook Ads, Google Analytics, Bing Ads or Shopify are technically "correct," but they just view marketing differently.
In essence, different marketing platforms use different attribution models and measurement techniques, which can lead to differences in reported metrics.
For instance, Google Ads might use last-click attribution while Facebook Ads might use a different multi-touch model. As a result, each platform might assign different values to each touchpoint in a customer's journey.
That’s why you should see the differences between these platforms and their attribution models in order to make better decisions. Instead of relying on a single source of truth, it’s always a good idea to look at multiple platforms and reports to get a more complete picture of their marketing performance.
Google Ads
The Google Ads platform only tracks traffic that originates from Google Ads. It does not track or deduplicate conversions from other advertising campaigns on different platforms.
This means that it will only take credit for any user who interacts with a Google Ads campaign, even if they later interact with other campaigns on platforms such as Facebook/Instagram or via email, or if they visit your website directly and convert.
Google Ads' default attribution model is data-driven with a 30-day attribution window. This helps advertisers track their ad campaign effectiveness and determine which touchpoints drive conversions. Since the data-driven attribution model relies heavily on the data it collects from conversion actions, it may be beneficial for advertisers to start with the "position-based" model for newly opened conversions. This allows for a sufficient amount of data to be collected before switching to the data-driven attribution model. By doing so, advertisers can make more informed decisions and optimize their ad campaigns accordingly.
However, it's important to note that you can adjust the attribution window in Google Ads and choose a different attribution model to better align with your business goals.
Facebook Ads
The Meta advertising platform (formerly Facebook Ads) only tracks traffic and interactions from Facebook Ads (which also includes Meta-owned properties like Instagram).
It doesn't deduplicate data from other advertising campaigns on different platforms and will take credit for any user who sees or clicks a Facebook ad within a certain time span, even if they later interact with a Google Ads campaign or email, or visit your website directly and convert.
Facebook defaults to last-click attribution with attribution windows of within 24 hours of viewing your ad and within 28 days of clicking your ad.
It is the only one of the more detailed advertising platforms that will take credit for users who potentially "see" an ad (even without clicking it) and convert in another way. It's recommended that you change the settings to be click-based if you're looking for a better comparison of your results across platforms.
Google Analytics
It tracks user interactions across multiple channels, including paid and unpaid sources. You can also configure Google Analytics to connect external/offline data sources, user ID, and other web properties that are not directly part of your online store.
Google Analytics will deduplicate conversions from all channels and give credit to the last touchpoint in a conversion journey unless it was a direct visit to your site. In that case, it will give credit to the last non-direct touchpoint.
It's important to note that Google Analytics uses a last non-direct click attribution model by default, but this can be customized to fit your business needs.
Additionally, Google Analytics offers a Data Import feature that allows you to upload data from other sources and incorporate user IDs to include the majority of your customer interactions across platforms in one place.
Overall, Google Analytics provides a more comprehensive view of your marketing performance across channels.
Shopify
Shopify's default attribution model is similar to Google Analytics in that it removes duplicate conversions and gives credit to the last touchpoint in a conversion journey.
However, the key difference is that Shopify will give credit to the last touchpoint even if it's a direct visit to your store.
This means that if a customer interacts with multiple marketing channels before making a purchase, including visiting your store directly, Shopify will attribute the sale to the last touchpoint, which could be a marketing channel that drove them to your store in the first place.
It's worth noting that Shopify also offers multi-touch attribution reports that allow you to see the impact of each touchpoint in a customer's journey.
Still, these reports require additional setup and integration with third-party analytics tools.
Marketing Attribution Is Not Flawless
Yet, having a clear understanding of the different marketing attribution models and their limitations can help improve tracking, enhance customer databases, and facilitate better decision-making.
Although marketing attribution is a complex process, its benefits cannot be denied, as it provides valuable insights into customer interactions with your brand and their purchase journey.
Despite its imperfections, marketing attribution remains a powerful tool for improving marketing strategies and maximizing ROI.
