A new flow for Wish Assistant
Scenario: Wish Local is a shipping option that allows customers to pick up their orders from a local store.
Customers have 14 days from when the order arrives in the store to pick up their order.
Once an order arrives in-store & is scanned in, Wish sends the customer a confirmation notification.
Afterward, Wish sends the same notification every 3 days until the 14-day pickup window is done. If the order is not picked up, it is auto-canceled and refunded.
Problem statement: The auto-refund for abandoned Wish Local orders was costly. On average, customers new to Wish Local have a ~13% lower pickup rate than regular Wish Local customers.
The refund policy and decrease in pickup rates made our refund rates skyrocket.
Our solution: Roll out a new policy requiring customers to contact support for a refund if they can’t pick up an order.
We’d no longer auto-refund abandoned orders and needed to communicate this new policy through our chatbot, Wish Assistant.
Thanks to this project, the weekly overall refund rate was reduced by 30% year over year!
As the lead UX content writer for the Wish Assistant experience, my goal was to create content to inform new and existing Wish Local customers of the policy changes happening, encourage them to pick up their items before the expiration date and tell them how they can get the help they need if they miss the deadline.
Customer Journey Mapping: I needed to experience the existing conversation to create a map of the existing flow. After running through a simulation flow, I mapped it for visual reference. This way, my stakeholders and I can assess the entry points, outdated processes, and any missing or redundant prompts.
The existing flow included: