Sunday, May 5, 2019
Aritzia Statistics Project Example | Topics and Well Written Essays - 1000 words
Aritzia - Statistics Project ExampleSpring and autumn prove to a host the countrys best weather. However, the geography of England means that the weather can change in short distances (Woodlands, 2014). The surrounding sea gives England a varied climate but generally there be warm summers but they are cooler than those on the continent. The winters are also milder and do not go below 0 degree centigrade usually. The summer temperature is around 32 degrees and is often damp and subject to frequent changes. The warmest month in England is July and around the coastal area, February is normally the coldest month (Woodlands, 2014).These conditions can greatly affect the return range which should be present at Aritzia. This means that the range of jackets and sweaters must not be excessively heavy duty. Really warm fur or fleece line of productsd jackets and sweaters would not be competent for the generally mild winters. Warm woolen ranges should suffice for the winters in the United Kingdom.Their category of blouses, dresses, jeans, t-shirts and jumpsuits etc. should be extensive and not made of cloth that is too warm. Seeing the damp and summery conditions, their clothing line should include clothes made of material that breathes and is suitable for the mild hot and damn summers.To make dear use of the brand equity of Aritzia and to successfully compete with the competition, it will be required to set up a local subsidiary in the United Kingdom. Aritzia is a Canadian womens fashion dress shop that was started in Vancouver in 1984. It has stores in North America including Seattle, San Francisco, Toronto, Chicago and New York (Aritzia, 2014). It is a brand endorsed by many celebrities including Megan Fox, Emma Stone and Eva Mendes (Fashion Base, 2014). Hence in order to make full use of this brand equity, it is necessary to have full brand presence in the country and not rely on articulate ventures of sales agents which might
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