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The worldwide market of athletic footwear is competitive, and brands that dominate are continuously revolutionizing to lead the competition. Consequently, there's a massive amount of data regarding the best- selling shoes and how people utilize them—and we've utilized it to make this blog for analyzing the best-selling shoe brands.
In this blog, we have done a product analysis in the best-selling shoe category of six top brands on Amazon, the world’s top eCommerce company. Using this, we aim to know the different financial strategies various brands have used to appeal to customers and their replies. We will explore some of the most common industry brands.
The 6 top brands we will analyze the following:
All the used datasets for visualization and analysis objectives include 632 records with the given fields:
Product URLs: This is the address of any particular products online.
Product’s Name: This recognizes a particular product.
Brands: This represents a brand that a product fits into, for instance, Nike.
MRP: This is a product’s market price.
Sales Prices: This is a product price after putting on discounts.
Discount (%): This percentage is subtracted from a product MRP.
Total Reviews: This is the total reviews any product has.
Star Ratings: This is a field utilized as a comparative performance measure. With higher ratings, the performance will be better.
We have used Pycharm Community, a Python IDE, to analyze and visualize datasets. Pandas is a Python library used for data analysis and manipulation. For the visualization, i.e., to plot graphs, we have used matplotlib, another Python library.
By utilizing these tools, we have analyzed data and planned the given eight graphs:
The product ranges are defined as variations of one similar yet different product. Different product versions are designed to target different customer sections. So, having an extensive product range is very important for brands because it helps them address the preferences and requirements of various customer segments.
Here, we have looked at a product range in the best-selling shoe category of six top brands given here. From this analysis, we have reached the following decision:
Discounts are a way of creating demand for products and fascinating new customers. When customers observe that they could save money, they are involved with it. They tend to share it; therefore, it is a real way of reaching new and stationary customers and making demands for new products.
Giving special discounts is an efficient way to keep regular customers faithful and fascinate new customers given by them. There is one more category for customers - the uncertain ones. They are unwilling to purchase a product because of high prices, and offering discounts encourage them to decide to purchase the products.
After data analysis, we can conclude from this graph that:
Whenever a brand has preserved competitive entry or exit pricing, it will interest more customers. The entry product prices in the brand is a product price with lowest pricing in the brand. Correspondingly, the exit product pricing in the brand is a product price with the maximum brand price. The difference of the latter and former provides a product price range of a brand. Maintaining the price range is important because a too high or too low price will turn off a customer's interest.
With data in hand, the entry & exit pricing of every brand is added, and we have observed the given:
The average discounted percentage is the average of all discounts the brand provides. In this context, this is an average of all brand discounts in a best-selling shoe category.
Discount generates demand and attracts more customers. It similarly impacts entry & exit pricing, i.e., too high or too low discounts can kill customers’ interest. The regularity of discounts also matters in the business scenario. Standard discounts decline the product value. In addition, it appeals to customers that purchase when there are discounts and might not value products. These customers might not be of good value in the long run. So, offering average discounts and maintaining discount frequency is essential to product sales.
The data analysis evaluates average discount percentages in the best- selling shoes category of these six brands, and here is the conclusion:
Rating is the feedback source from customers that have utilized a product. So, it has a significant impact on product sales and brand growth. Positive ratings increase the trust and confidence of a customer in products. In contrast, negative ratings result in losing customers.
During our analysis, we set 3.5 as the base positive rating. Ratings over 3.5 are measured as positive, while those under 3.5 are measured as negative. Here are the results of our analysis:
The average ratings are an average of different ratings of all brand products and indicate a brand’s performance. This has a similar importance as an individual product rating. Any good average ratings will interest customers and increase the market of that brand. Both negative and positive ratings contribute to this. So, we have used the product ratings in the best-selling shoe category of every brand.
The data analysis in hand suggests average ratings in the best-selling shoes category across every brand as given:
Discounts are a way of creating demand and getting new customers. However, discounts above and under drive customers to lose interest in the product or decrease product value. Considering this before providing discounts is vital because no brands want to lose customers.
By doing data analysis, we have reached the following results:
Mean pricing is defined as the average pricing of all the products in the best-selling shoe category, and median pricing is the middlemost product in the best-selling shoe category, organized from lower to higher. Though they provide different meanings, collected, they have an essential role in determining a brand image. A brand having mean & median pricing that is knowingly far apart suggests instability in a brand’s product prices. Therefore, mean & median pricing are vital factors for determining constancy in the brand’s product prices.
After analysis, we have observed that:
The eCommerce business has grown enormously in the past few years. To stay in the race, companies have to analyze a market trend within the company. So, visualization and analysis of competitors’ data play an essential part in the sustainability and development of any business.
This blog aims to help you better understand different financial strategies that different brands familiarize to improve their market and increase product sales. The analysis showed different factors that can disturb the company's performance and the reply of customers. The conception of results of analysis assists us in concluding quicker.
In this blog, we have visualized and analyzed different factors that can affect the performance of any brand and product demands. For that, we have taken data from products in the best-selling shoe category of six leading brands, visualized it, analyzed it, and made certain assumptions.
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