Attribution helps you understand which campaigns, or campaign steps, contributed most to a prospective customer's decision to purchase. An independent shoe retailer from Brighton, for example, might launch a new range of wellies and decide to promote them using digital ads, email and social media. When a shopper purchases a pair of wellies, it's difficult for the business owner to know which form of marketing ultimately convinced them to buy, since they have interacted with multiple formats during the sales journey.

That's where attribution models come in. Attribution models are designed to help businesses track their sales, and different models emphasise different steps or aspects of the sales journey. Through attribution modelling, business owners can decide what to measure and what success looks like based on their particular goals. Google Ads makes it easy for businesses to access information that's helpful for creating strategies designed to win over new prospective customers.

There are seven main types of attribution model and which one a business owner chooses will depend on their goals.

Time decay

This model assigns more credit to clicks that happened closer to the time of the conversion. There's also a half-life here, of a week, and then two weeks. So a click seven days before the purchase would receive half the credit of one the day of, and a click 14 days before would receive half again credit, or a quarter.

This can be helpful for tracking the impact of short-term sale periods, for example. Let's say the wellie shopper read 50% off for two days only in an email from the brand. That clickthrough from the email to the website, which leads to them purchasing the boots, would carry more weight in a time-decay model than if they had opened the email, waited a week, and then returned to make a purchase.

Position based

This model recognises the importance of that first interaction with the business, as well as valuing when a prospective customer makes a purchase. For this, 40% credit for the sale is given to both the first and last click of the sales journey, with the remaining 20% distributed across other clicks.

The user buying wellies started by interacting with a Display ad from the shoe retailer (their first click, worth 40%) and completed their journey when they visited the website and made a purchase (their last click, worth 40%). However, they also interacted with the business via social media and email, so these are also considered (worth a combined 20%) in assessing how they made their purchasing decision.

Last click

Just like it sounds, the last click attributes the sale to the last thing a shopper clicked on to purchase. Businesses that rely on Display ads or have a short sales cycle might choose this attribution model because they don't have many other steps to track, and Display ads are likely to be their biggest investment. For the wellie shopper, the last click would be the product link on the business's website.

Last non-direct click

In this case, the model tracks the prospective customer's second-to-last click before they made a purchase. Analysing this model can offer insight into the type of outreach that leads users to the last step in the purchase, what's known as the direct channel. For the wellie shopper, the email would be the interaction that's tracked as the second-to-last click.

First click

Where did the potential customer click to start the chain reaction that ultimately took them to purchase? Tracking this metric tends to be a measurement of brand awareness more than direct conversion. This would be the Display ad the wellie shopper saw first before they found the brand on social media or signed up for their email updates.

Linear

Linear attribution distributes credit equally across all clicks leading to a sale. This is best for businesses that have very long conversion paths — meaning there are many interactions with the potential customer before they buy. This model doesn't put any more emphasis on the first or last click, which can be useful if your campaigns are designed to maintain contact and awareness with prospective customers throughout the entire sales cycle because you're tracking every step.

Consider the shoe retailer that sells wellies. Maybe they also sell outdoor kits, which cost significantly more than wellies. Some prospective customers take more than a year to weigh the purchase, so the business's goal is to keep their name in front of potential customers for months, via multiple channels. Tracking all these steps could help them determine the most effective parts of that advertising campaign.

Data-driven attribution

Using analytics from a Google Ads account, data-driven attribution (or DDA) tracks the entire sales journey online and credits all the touch points that lead to the sale. This method includes keywords too, to provide a fuller picture of exactly what is having the most impact. Everything the wellie shopper did, from the email to the social media to the purchase, is tracked in this model and given equal weight.

There are many ways to track touch points and decisions during the sales journey. Doing so offers insight into what's working, and what's not, to assess how businesses can improve their efforts. But just as all businesses aren't the same, the most helpful attribution differs too. That makes it important to understand the options and the goals of each type of attribution, to make the right tracking choices for your business.