What is click attribution?
Click attribution is a way to determine what sources or campaigns are driving the most sales for your brand. Many brands use click attribution because it allows them to track whether paying customers come from a particular site, email, ad, or another source.
Click attribution also allows brands to track and analyze the relative performance of different messages, campaigns, or marketing techniques. Plus, it is a strong signal of intent or interest. If someone clicks on a piece of content, you can assume that they found it compelling or interesting enough to investigate further.
What types of attribution models are there?
The most common click attribution models are first-click attribution, last-click attribution (these are also referred to as first-touch attribution and last-touch attribution, as any interaction with your brand or its content is called a “touch”), and linear attribution. There can be many variations of attribution models that assign different values based on the type of transaction and channels involved.
First-click attribution, last-click attribution, and linear attribution are common attribution models that most tools will use as defaults.
What is first-click attribution?
First-click attribution is an attribution model that assigns 100% of the credit for a sale to the first channel that a user clicked through. Some customers convert on the very first interaction with a brand, but many will have at least two interactions during their journey to purchase.
The first-click attribution model rewards the marketing channels or activities that “introduced” a potential customer to a brand.
First-click attribution example
If a customer visits your website for the first time after clicking on a Facebook ad, and they make a purchase after clicking through an email, 100% of the credit for that sale would go to Facebook. So if you sold a $50 item, Facebook would get the full credit for that $50 sale.
What is last-click attribution?
Last-click attribution is a model that assigns 100% of the credit for a sale to the last known channel that a user clicked through.
Last-click attribution is the most commonly used attribution model for eCommerce Analytics and is the default attribution model Google Analytics uses.
Last-click attribution example
Going back to our previous example, If that same customer clicks on a Facebook ad, lands on your website, leaves, and then comes back to make a purchase after clicking through an email, 100% of the credit for the $50 sale would be applied to email.
What is linear attribution?
Linear attribution breaks the credit for a sale or action into equal parts pending how many touchpoints (places where a customer has interacted with your brand or any of its content in some way) were measured in the course of the customer’s purchase journey. If the customer had four marketing channel interactions that ultimately resulted in a sale, each channel would be assigned an equal credit for the sale (25% in this case).
Linear attribution example
Let’s update the example from first-click attribution and last-click attribution and say that a customer first clicked on your Facebook ad (1st touchpoint – Paid Social), then searched for your brand (2nd touchpoint – Organic Search), then clicked through an Instagram post (3rd touchpoint – Organic Social), then finally purchased a $50 item after clicking through an email (4th touchpoint – Email).
Each of the four channels (Paid Social, Organic Search, Organic Social, and Email) would get an equal 25% of the credit for the $50 sale.
How to choose attribution models
Most brands will choose one attribution model to use in standard reporting, which is typically last-click attribution.
Last-click attribution will favor channels or marketing activities that are lower in the conversion funnel, meaning that the customer is ready to make a purchase rather than being in their discovery or shopping phase (higher in the conversion funnel).
When evaluating the results of last-click attribution, companies should consider their entire marketing mix and targeting strategies. The truest measure for last-click attribution is an email or text channel. Almost immediately upon receiving these messages, customers are more likely to immediately make a purchase.
Other channels, such as search, paid social, or podcasts, are likely driving awareness and interest for your brand, but they are probably not driving an immediate purchase.
Think about it like a consumer: if you are listening to a podcast or scrolling through social media, you might be intrigued by an ad from a brand you haven’t heard of, but it’s rare that you are ready to buy after hearing about a brand for the first time. On the flip side, if you are subscribed to a brand’s email list, and you often click on their messages, it’s more likely that you are ready to make a purchase.
How your attribution rules are configured can make a difference in the end result (which channels or activities get “credit” for the conversion) and should match your marketing strategy.
Now, a more complex click attribution example
Company X runs a marketing campaign that includes paid social ads, podcast ads, and online display banners. A podcast listener hears a podcast ad and is curious, so they look up the company in a search browser and visit the website to learn more, but they do not make a purchase.
After visiting the website, the customer receives online display ads and paid social ads advertising the company and product. They hear another podcast ad the following week and hear a promo code offering for a discount.
Later that day, the customer clicks a paid social ad, shops on the site, and at checkout, they enter the promo code from the podcast before submitting their order.
Depending on how last-click attribution rules are configured, this order could be attributed in two ways. Either it would either be classified as Paid Social, since that was the last channel that the customer clicked on before making the purchase, or it would be classified as Podcast, since that channel is associated with the promo code used at checkout. Ultimately, the order can only be classified to one channel.
Which channel do you think should be deemed responsible for driving this purchase?
This example may seem complex, but in reality, this is a simple example.
Understanding and analyzing attribution is both an art and a science. There are many algorithms available on the market and countless companies trying to crack the code of having the most accurate tracking, but none can solve this for every piece of information or every touchpoint a consumer has.
This is why comparing first-click attribution and last-click attribution models is a good place to start.
Google Analytics attribution models can be great for this too because they include first click attribution and last-click attribution by default. With this, you can easily compare sales that were measured side-by-side across multiple channels.
Additional ways to improve attribution models
As the example above shows, promotional codes are another method for improving attribution accuracy. They’re often used as a measurement and attribution tactic for social influencers, on podcasts, radio, tv, and in direct mail.
A great way to add an additional layer to your attribution models is to ask customers what caused them to purchase or how they learned about the company (“Where did you hear about us?”).
By asking this one question, you can gain a better understanding of which interaction the customer found most memorable.
Marketing Analytics Platform
Combining all of these data sources to draw insights using a marketing analytics platform will give you a good idea of how your marketing activities are performing. Ultimately, you will have a range of performance depending on which data sources you use.
Understanding which activities are upper conversion funnel (introducing your brand to new potential customers) and which are lower conversion funnel (capturing the sale from someone ready to purchase) will further help you determine what the corresponding metrics should be.
At the end of the day, there is no silver bullet to having the perfect attribution model. By collecting as much data as possible and considering the role your media mix plays in a customer’s path to purchase, you can optimize your marketing spend to customer conversion based on what your optimal channel mix looks like.
Learn more about attribution models with Daasity
Daasity has approached attribution analysis in multiple ways. Daasity uses additional data beyond Google Analytics to prioritize attributes such as specific promo code usage, post-checkout survey results, or map orders to marketing channels.
With Daasity, you can slice and dice your data by initial order marketing channel to better determine how your marketing channels are performing.
Additionally, you can easily view results by first-click attribution, last-click attribution, and ad platform (view + click) in one simple graph to help gauge results.