Pet Clothing Market Comprehensive Evaluation Of Impact of COVID-19 Via In-Depth Qualitative Insights 2018 – 2026

Pet clothing comprises garments used to protect pets from the cold and rain and to provide them extra warmth. Pet clothing includes coats, sweaters & knit wear, hoodies, jackets, shirts, dresses, pants, skirts, head & neck wear, raincoats, and swimwear. All these clothing serve specific purposes. For instance, sweaters offer extra warmth to pets that are hairless or suffer from cold. Pet clothing are used both for style and for functional purposes.

With an increasing number of pets and the rising popularity of their clothing and accessories, the industry is projected to witness steady sales growth over the forecast period. Increasing interest amongst pet owners regarding fashion trends for pets and the need to offer them comfort based on the climate conditions has raised their expenditure on pet clothes. Pet owners are essentially trying to figure out specialized and better quality products or garments for their pets. These factors have led to the growth of the pet clothing market globally. Furthermore, increase in the number of pets (especially cats and dogs) across the globe is also expected to influence the market growth over the forecast period. Rising concerns related to pet care, introduction of advanced cost effective pet clothing, and increasing health expenditure on pets is also anticipated to spur the demand for pet clothing in the coming years.

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Humanization of pets such as cats or dogs has led their owners to treat their pets as family.  The owners want to dress their pets according to the pet’s breed and age. These factors are also projected to boost the market growth in the coming years. According to American Pet Products Manufacturers Association (APPMA), pet owners in the U.S. are expected to spend more on their pets every year. This is further projected to boost the pet clothing market over the forecast period. However, high cost of pet clothing may hinder the growth of the market over the forecast period.

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