Fashion retailer Aritzia Inc. has reopened all the stores it closed due to COVID-19 pandemic lockdowns in March, *but ongoing related issues are blamed for* lower revenue and a net loss in its most recent fiscal quarter.
The Vancouver-based company behind the TNA, Babaton and Wilfred brands reported a net loss of $900,000 on revenue of $200 million in the 13-week period ended Aug. 30, beating analyst expectations for a net loss of $5.3 million on revenue of $191 million, according to financial markets data firm Refinitiv.
It reported net income of $17.9 million on revenue of $241 million in the comparable period last year.
“Despite shuttering our retail operations in March, we were thrilled by the response of our people and our clients. As we reopened and began the recovery of our retail operations in early May, this enthusiasm continued into Q2,” said CEO Brian Hill on a conference call on Wednesday.
“As a result of keeping all of our people employed during the shutdown, and starting to plan our reopening as soon as we closed our doors, we were able to reopen our boutiques quickly and efficiently,” he said.
Aritzia’s optimism about the upcoming holiday season is tempered by recent increases in COVID-19 positive case rates and new government restrictions in some of its key markets, Hill cautioned.
The Vancouver-based retailer started a phased reopening of its 96 stores in May, with the last store reopening in early September.
The decline in quarterly revenue was mainly due to ongoing COVID-19 occupancy restrictions, reduced operating hours and partial boutique closures, Aritzia said, partially offset by continued momentum from e-commerce revenue, which increased by 82.3 per cent from the year-earlier period.
The company is already starting to hire and train staff for the Christmas season – its most important sales period, said president Jennifer Wong on the call.
She said the company has enhanced its online presence with “digital selling tools” and will launch an artificial intelligence tool this month to help customers with size and fit optimization based on their measurement data and preferences.
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