This use case shows how a customer data analyst can use journey channel analysis to help drive revenue growth for a new product launch.
Part 1: Setting the goal
Last year, CityCool unveiled a cutting-edge electronic watch called Sleekfit. After a profitable market response and positive feedback from consumers, CityCool is ready to launch Sleekfit 2.0. Anthony, a Customer Data Analyst at CityCool, wants to support the Sleekfit 2.0 launch to help meet the business goal of increasing revenue by 10%.
Anthony wants to understand the paths that led to the purchase of a Sleekfit 1.0 to discover whether there are any interaction patterns that CityCool's customer experience designers would find useful for their design of the Sleekfit 2.0 campaign.
Part 2: Configuring the report
CityCool has a subset of buyers who tend to spend the most—the top-tier buyers. Anthony wants to know what it will take to get these customers to purchase the Sleekfit 2.0. He would like to understand what paths these top-tier buyers take, so he decides to limit his report to show only the paths that were taken by these buyers. He selects Top Tier Buyers from the Audience menu.
Anthony wants to see the top five most-traveled paths that meet his criteria. He selects this option from the Report options menu.
Next, Anthony selects the Cart Purchased event as the end touch point of the paths that he wants to see. Only paths that resulted in a cart purchase will be included in his report. Anthony filters the Cart purchased event to include only purchases that included a Sleekfit 1.0.
Now that Anthony has defined all of the criteria for the paths he wants to see, he is ready to run the report.
Part 3: Analyzing the results
The journey channel report results show the paths that led to a Sleekfit 1.0 purchase. Each path shows the channels that customers used to interact with the brand. The paths are sorted by most traveled in descending order, but the report also provides metrics for Anthony to compare paths by duration, average revenue, and number of unique customers.
To visually compare the top paths along the time dimension, Anthony switches to the Time-lapsed view. In this view, he can quickly gauge the time elapsed between individual channels within a path.
Part 4: Drilling into channel activity
Anthony drills into the most frequently traveled path in the channel summary for deeper insights. He sees an aggregate view of the customer interactions that the top-tier buyers completed in the different channels along their path to purchasing a Sleekfit 1.0. He notices that a majority to the customers who traveled this path to purchase began by opening the promotional email with a 10% discount offer. Next, they clicked the email link to the product summary page on the website, and then launched the Sleekfit promotional video before making their purchase.
Part 5: Sharing insights
Anthony shares what he has learned with CityCool’s user experience design team. The designers can then design a storyboard template as the foundation for new customer experience designs for the Sleekfit 2.0 launch.