How To Use The Attribution Model Comparison Tool

By Stephanie White | @stephanieppcpro | Account Manager at Hanapin Marketing

Have you ever taken a deeper look into your customers’ behavior in Analytics?  For instance, how long does it take your customers to convert? Understanding your customers’ buying journey is a complex task, but it is worth exploring to understand how they typically shop. Discovering how long your customers take to convert can help you verify that you are measuring your conversions properly. Customer behavior may vary depending on product prices.

 

Multi-Channel Funnel Top Paths

 

Reviewing the Top Conversion Paths is a great way to determine if customers take longer to make a decision. In the first path in the image below, two visitors started with paid search and then visited the website directly six more times before converting. This data can be important in learning if your paid search is assisting conversions through other channels.

 

Top conversion funnels

 

Time Lag

 

How long does it take your customers to complete a purchase or submit a lead? Understanding your customers’ behavior can help you determine which attribution model you should be using for your paid advertising. This data can also help you determine if your conversion window is set correctly in AdWords. In the example above, the credit for most of these conversions would be given to the direct channel. Without this attribution information, you could make PPC decisions that decrease conversions in other channels.

 

In AdWords, under “Tools > Attribution” you will be able to see additional details about how long it takes your customers to convert. The default view includes all types of conversions. You can select a specific type of conversion, so in this case, we wanted to see additional information about how long it takes customers to make a purchase. You can adjust the history window to include 30, 60, or 90 days’ worth of data.

 

AdWords attribution days to conversion

 

This client’s customers take on average 19.55 days to convert. The reason for this length is because their products are expensive and require adequate space to install. Purchasing these products requires thought and would not be considered an impulse buy. These customers take longer to complete a purchase. If our conversion window was set at 30 days, some of our conversions would likely fall outside our window and would not show in our data.

 

In contrast, one of our lead generation clients’ customer journey is much shorter. Their customers convert in less than 24 hours. Their products are service oriented and customers are more likely to call within 2 days after clicking on their paid search ads. If you are tracking more than one type of conversion action, like phone calls and transactions, you might review each conversion action independently because they can vary.  It may take customers less time to pick up the phone to ask a question than moving forward to make a purchase.

 

Days to conversion

 

You may want also look in Analytics, under “Conversions > Multi-Channel Funnels > Time Lag.” This view can show you the average for all channels or you can specifically select Adwords. In this view, we changed the conversion action to transactions and increased our window to 90 days.

 

Analytics time lag report

 

In this example, the data shows us that it takes the customers longer to convert than what AdWords attribution had shown us. Only 32% of customers complete a transaction within the first 10 days. Over 37% of the customers who completed a transaction, did it with between 61-90 days after they initially clicked on our ad. It could take customers between 2-3 months to make a purchase from the initial click on the paid search ad.

 

Analytics time lag in days

 

Attribution Modeling

 

Another item to take into consideration, if customers take longer to complete a purchase, sometimes their path is more complex because they visit the website multiple times through different channels. Many times, we have found the direct channel is getting credit for paid-initiated conversions. For one client, we found that 75% of our paid initiated conversions were converting through the direct channel.

 

Paid initiated conversions by last click

 

Another issue we discovered was our revenue and CPA data were not lining up. In Analytics, we could see that Texas and California were in the top locations for revenue.

 

Geography by revenue

 

Our client had noticed that he was receiving a high volume of orders from California, Florida, and Texas. However, when we reviewed AdWords for non-brand geography, we found these locations had the highest CPAs. Normally, we would pull back on these locations, but we had a theory that AdWords was not telling the complete story. 

 

CPA by geography

 

Our theory was that non-brand was assisting in driving brand and direct conversions. So, we decided to increase our location bid adjustments in AdWords for the warmer states and monitor Analytics performance. What we found was that transactions and revenue increased for most locations. 

 

Transactions by state

 

We decided to test switching the attribution modeling from last click to first click. Two weeks later, when we compared the performance we found that brand saw a 62% decrease in conversion volume while non-brand saw a 45% increase in conversion volume.

 

Brand vs. non-brand

 

This data tells us that non-brand was likely contributing to the brand conversions. Our goal with switching from last click to first click modeling was to gain additional data in order to optimize our non-brand campaigns more efficiently.

 

This is why we recommend digging deeper into your customers’ buying cycle to make sure you are not making decisions off incomplete data from AdWords. This customer had such a high volume of direct conversions in Analytics that were initiated by paid search.