What You Need to Know About Attribution Modeling

Digital marketing shouldn’t be a guessing game. If you want to grow your business through paid advertising online, you should rely on data to make confident decisions that will enhance your marketing strategy, improve your performance, and bring in profit. You need to fully understand which campaigns are the most successful in order to allocate your budget most effectively.

Attribution modeling is one way of using the data to inform your decision making. We’ll talk about what it is and what you should know about it in order to scale your account!

What is attribution modeling? 

Attribution modeling is a way of determining the amount of credit that user touchpoints in conversion paths receive. 

A customer’s journey that leads them to a purchase or conversion is incredibly complex. A user may perform a Google search on their mobile device, which leads to them seeing an ad on their Facebook app for a certain company or product a day later. They may see a display ad in their inbox on their desktop device that afternoon and click on it, but leave the website, only to go to their tablet a few days after that and enter the url of the site to purchase something/contact someone. 

This is a realistic example of these user touchpoints, which could include many more channels and devices. If your company is trying to understand how your users found you and why they converted (so you can improve and replicate that process, optimizing your customer acquisition process, you need to have a grasp of which ads influenced the final decision the most and be able to compare the value of all of your marketing channels. 

Enter attribution modeling, a feature in Google Analytics that helps you do just that. You can adjust your settings so that Google assigns percentage attributions to different parts of your conversion funnel. For example, the default setting in Google Ads is the Last Interaction model, which gives 100% credit to the final click that directly come before sales or conversions, but you can change that to the Linear model, which gives 25% credit to each touchpoint. 

So which model should I choose?

There are several different attribution models available to you. You want to select a model that best fits with your company’s goals. Depending on your industry, the size of your business, your budget, and how many channels/what kind of channels you advertise on, some attribution models will be more beneficial to you than others. We’ll discuss that more shortly, but for now here is a basic overview:

-First InteractionIn this model, 100% of the credit goes to the first touchpoint, the click that first drove your visitor to your website. It is simple and easy to implement, but overemphasizes promoting awareness (though that may be useful for some businesses). It is also subject to technological error; if the interval between first interaction and conversion is longer than the 30-90 day expiration on the tracking cookie, the model will give credit to the first interaction within the cookie expiration window, and not the actual first click.

-Linear In this model, credit for each touchpoint in the conversion path is evenly distributed (25%). It gives credit to each of the marketing channels you use, which helps you begin optimizing for the overall customer journey instead of a single activity, but does not take into account the amount of influence that each touch has.

-Time Decay In this model, more credit is given to the touchpoints closest to the conversion, and credit is distributed using a 7-day half-life (a click 1 day before a conversion gets twice as much credit as a click 8 days before a conversion). This is helpful information for companies to use in order to optimize for touchpoints that increase the likelihood of a conversion in the near future. However, earlier touchpoints that may have been significant are not given credit, even though they may be more valuable in reality.  

-Position-Based In this model, 40% of the credit is given to the first and last interactions with the other 20% distributed evenly among the other touches in between. This model, a compromise between the linear and time decay model, does a great job of recognizing every touchpoint in the customer journey and still allows companies to optimize for first and last interactions. However, assigning more credit to first and last touches means that they may be overemphasized while influential interactions in the middle are underemphasized. 

-Last Interaction In this model, 100% of the credit goes to the final touchpoint that drove the conversion. It gives great insight into campaigns that have high conversion rates, especially for companies that have a single-minded focus on driving conversions, but does not give any credit to earlier clicks that were significant. 

-Last Non-Direct Click In this model, all direct traffic is ignored, and 100% of the credit goes to the last channel that the user went through before converting. This model eliminates the misleading nature of including “direct” traffic, which may have come from improperly tagged sources, but like the last interaction model, does not give credit to first interaction clicks.

-Last Google Ads Click In this model, 100% of the credit goes to the first click from a Google ad. This model is by nature biased towards the paid search channel, but comes standard with Analytics and can be useful to gauge how valuable Google Ads is to you. 

Let’s take a look at a real example of an Ecommerce store. This particular store has multiple sources of traffic, and we want to know what sources are the best for prospecting so we can scale those campaigns. We will take a look at a few different models, and you will see how dramatically the results can differ based on the attribution model chosen.

 

You can see that the CPA is much higher with the default model, last click, overall (with the exception of the first campaign). This can be for a few reasons. First, Google Ads may have been the first touchpoint for this customer. They may have completed an email form or come back to the site from a remarketing campaign. Whichever the case, Google Ads (the original source that brought in the customer) lost the credit.

When we change the model to First Interaction, you can see how the CPA is dramatically reduced for most campaigns.

This tells us that Google Ads is playing a much larger role in bringing in new customers. This is valuable knowledge, because now we know there is room to scale our efforts in Google rather than cutting a profitable source of traffic.

Evaluating your attribution model when you are evaluating campaign performance is going to greatly increase the success of your campaigns over time. If you need help using this feature in Google Ads or want to understand how you can grow your business through digital marketing, contact us! 

Empirical360 likes to win. We’re a highly skilled, highly experienced team of PPC experts that knows what it takes to beat the competition, lower your spend, and increase your return on investment. We’ve managed millions of dollars for our clients and produced millions more, and we’re Google Partners (which means we have a proven track record of success). If you want to know more about how we can help you take your online marketing to the next level, get in touch with us!