Path Analysis Page Quick Tutorial

This is a brief tutorial on how to use the Path Analysis Page.

• In the Analysis page, you can access the Path Analysis by clicking on the three-pronged arrow in the table below.

• For simplicity sake, let's break down your Analysis page by "Product". Scroll down to the table and find your top product. On the left of its name, click on the three-pronged arrow next to it to dive into the Path Analysis of that product. You can do this for any breakdown.

• Now, you should see a banner on the top that says "Path Analysis Mode". Just like the Analysis page, on the top left, you can change the date range to the past 7 days, past 30 days, past 90 days, etc.

• New buttons to note are:

  • Frontend Filter : it allows you to pick which frontend item (whether it's a platform, funnel, product, utm, or affiliate) whose backend activity you want to analyze

  • Attribution : same as Analysis Page

  • Backend Breakdown : it allows you to break down the backend activity by the same breakdowns as in the Analysis page.

• For example, if you want to see what products your customers are buying after having first purchased Product A, then you would need:

  • Frontend Filter = "Product A"

  • Backend Breakdown = "Product"

• Below these buttons are only 2 graphs - LTV and LTV Gain Graph.

  • Pay attention to the LTV Gain Graph on the right. This shows you who is buying what and when.

• You can apply a "Backend Breakdown" by "Product" to see what products people are purchasing after that first product (which is the "Frontend Filter").

• If you want to see the traffic channels through which people are purchasing, you can apply a "Backend Breakdown" by one of the utms and see whether people are buying through a specific email sequence or autoresponder or whatever you've set up in your system.

• Below the table, you will see a bar that shows your "Frontend Customers", the "Frontend Revenue" brought in by these customers, their Day 0 and Day 90 LTV, and the "Lifetime Revenue" brought in by these customers (in the long run).

• Below that is a table. Pay attention to the number of customers that purchased the backend items and the amount of time it takes for them to purchase (on average).