Overview of Journey Analytics Calculation
- Pete Trevitt
The data below shows activity by Customers A & B, engaging with the brand over a 30 minute period. The Locations the Visitors interact with are captured and as seen here, and can be viewed in the traditional looking table of Events for all Customers. But this table view doesn’t clearly display activity by a single Customer and therefore is not suitable for display in the Journey Analytics flow. The data needs to change to answer the questions a CX Analyst is interested in.
Customer A | Visit Homepage | 12:00 |
Customer B | Product Search | 12:05 |
Customer B | View Product Information | 12:06 |
Customer A | Enter Live Chat | 12:10 |
Customer B | Add Item To Basket | 12:11 |
Customer A | View Product Information | 12:12 |
Customer B | Purchase Basket | 12:13 |
Customer A | Add Item To Basket | 12:30 |
Customer A | Sign Out | 12:31 |
Alterian’s database Engine can “pivot” this data to separate activity streams for each Visitor, therefore logically creating 2 interaction streams, showing transition from one Location to the next, to produce a data representation as seen here:
Key | Events |
Customer A | Visit Homepage ---> Enter Live Chat ---> View Product Information ---> Add Item To Basket ---> Sign Out |
Customer B | Product Search ---> Personalised Homepage ---> Add Item To Basket ---> Purchase Basket |
Once the data has been pivoted in this way, whether on the Visitor or Conversation Key, these streams can be over-layed and analysed to find the most commonly occurring streams, and itt is these streams that are then analysed and visualised within the Journey Analytics.