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Guess is a high-end clothing brand which sells products from clothing and shoes to handbags and accessories.
The company wanted to increase sales by making it easier for customers to determine item availability. This would benefit customers who are out and about as well as those who are searching from the comfort of their own home.
The Find in Store feature allows customers to locate which Guess branch has stock of their sought after item. Users can then find the closest store to them with available items and make their way to that location.
To explore our target audience, I interviewed individuals who shop online and those who have previously placed orders with Guess. From these interviews I was able to identify the following pain points:
Users want to know where to go and how soon they need to get there in order to get the item they want.
Users want the most convenient option, so they’d like to see which is the closest location to them.
Users don’t want to go to a store and find out the item is sold out, so they’d like to know how much of an item is left.
Users were disoriented because they forgot which store the pin represented.
“Oh okay, I don’t know where this is. Let me go back quickly.”
Users were overwhelmed by the number of stores that appeared.
“I’m gonna scroll to the bottom just to check. Wow this is a long list.”
Users were confused by the wording of tags. The word ‘stock’ seemed unclear
“I’m not sure about this. Ah okay I see now. Got lost for a minute.”
For 3 to 6 months following the launch of the ‘Find in Store’ feature our team will review conversion rates(CVR), average order value(AOV) and units per transaction(UPT). Based on our findings we will decide whether to include it for other brands such as Armani, YSL and L’Occitane.
For this project I would like to have conducted A/B tests because the key terminology was new. In particular words like ‘In Stock’, ‘Available’ and ‘Find in Store’ should be further tested. This region is extremely multi-cultural so finding the clearest English wording is crucial to many users understanding.