Apparel Retail Case Study

How an apparel retailer increased sales by 14%


One of the world’s biggest apparel retailers based in London, had opened up it’s branches in a country in South East Asia, and was looking for analytics solutions to improve it’s sales in the region. The retail chain is primarily a men’s fashion retailer but also manufactures products for women. The project requirement was also to know more about their customers (both visitors and buyers).


By using Face Analytics service, they got rich information about the kinds of visitors they were getting in different floors of the store. 4 cameras were installed. 1 for each floor and 2 for checkout counters. Using this they were able to get the demographics information of the visitors to the store, but also of the actual buyers.


Using the demographics data and the checkout system data, they were able to measure the conversions broken down by demographics (Age, Gender). It was noticed that there was :
1) Majority Female demographic during the weekday

2) Equal gender demographic during the weekend

3) Conversion % was much higher for middle-aged men during the whole week


According to the information gathered about the store, it was decided to stock more variety of women’s apparel in the stock and allocated some of the areas in men’s floor to that extra stock. This decision was taken to boost women’s conversions to improve the total conversion percentage. This was done by changing the men’s layout, so that there was no need to remove men’s stock to make space for the women’s stock. The increase is stock was also accompanied by adding advertisement in the form of mannequins at the store- front. This decision led to the following results :

1) The total sales for women’s products went up by 14% over the next 2 months.
2) The sales for men’s products for men’s products wasn’t affected.
3) The conversions as a whole increased
4) Because of the increased focus of women’s products the number of female visitors increased over the weekends.