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Report

This page has a list of our sample reports

Profit & Refund Report

Marketing Analysis Report

This industry sample dashboard and underlying report analyze a manufacturing company named VanArsdel Ltd. This dashboard was created by the VanArsdel Chief Marketing Officer (CMO) to keep an eye on the industry and his company’s market share, product volume, sales, and sentiment. This is real data from obviEnce (www.obvience.com) that has been anonymized.VanArsdel has many competitors, but is the market leader in its industry. The CMO wants to increase market share and discover growth opportunities. However, for unknown reasons, VanArsdel’s market share has started to decline, with significant dips in June.

Through our analysis we have shown information about our market share, sales, and sentiment. Data is broken down by region, time, and competition. On market share you can see how the company is performing in different categories, how it is performing in last 12 months and the YoY change on market share. Also you will find the market share of competitors over the years. Also you will find the regions, segments and competitors from which there exists a growth opportunity. Thirdly you will find how the company is performing vis. a vis. top competitors. Finally you will also see comparison of sentiments for the company and competitors across the various districts and segments

eCommerce Analysis Report

Studying top products requires more than just product listings. You also need to know what sells well and what does not. This dataset contains data from www.wish.com. With this, you can finally start to look for correlations and patterns regarding the success of a product and the various components. This should facilitate better understanding of e-commerce sales and also help businesses optimize their stocks and sales.

Through our analysis we have tried to demonstrate how sensitive the customers are to price drop i.e. discounted price to original price. We have also identified the top categories of product by sales, inventory and revenue. Additionally we have also shown the correlation between sale of product and quality of product (ratings). Also we have shown the ration of shipping to pricing distribution across category.

Manufacturing Analysis Report

The Garment Industry is one of the key examples of the industrial globalization of this modern era. It is a highly labour-intensive industry with lots of manual processes. Satisfying the huge global demand for garment products is mostly dependent on the production and delivery performance of the employees in the garment manufacturing companies. So, it is highly desirable among the decision makers in the garments industry to track, analyse and predict the productivity performance of the working teams in their factories

This dataset includes important attributes of the garment manufacturing process and the productivity of the employees which had been collected manually and also been validated by the industry experts.

Using this data we have done a workforce analysis where you can see the distribution of workers across various teams, the distribution of idle workers across various teams and distribution of idle time across various teams. You will also find average productivity and average productivity gap distribution for different teams. You will also find a comparison of finished products and unfinished products across dates, weekdays and teams. Furthermore, you will also be able to find distribution of task time across various times intervals, distribution of average task time date wise, and distribution of task time for various teams. Finally, you will also be able to see distribution of overtime and incentives across dates and teams.

Supply Chain Report

This dataset is the sales & inventory data for a fictitious chain of toy stores in Mexico called Maven Toys. It includes information about products, stores, daily sales transactions, and current inventory levels at each location. Through the analysis we were able to add more dimensions and meaning to the product such as rotation speed, profitability, stock level tiers. Using these dimensions we could create a visual story that demonstrates which products are driving the biggest profit and how this is distributed across the various geographical location. We were also able to demonstrate how much money is tied up in inventory and how long will this last. You can also see holding patterns across product profitability levels for different stores. Additionally you will also see comparison of sales by product rotation speed and the distribution of sales by product rotation speed across stores. We have also shown a relationship between production rotation speed versus profitability. Finally you can also view the requirements versus actual stock of products categorized by product rotation speed.

Retail Store Data Analysis

This dataset contains household level transactions over two years from a group of 2,500 households who are frequent shoppers at a retailer. It contains all of each household’s
purchases, not just those from a limited number of categories. For certain households, demographic information as well as direct marketing contact history are included.

Through our analysis we have tried to show the profile of the customers linking it to their average weekly spending at the retail store. We have also shown the consumer behavior in terms of hour of purchase, stores from where they purchase, the average basket size and how they are motivated by retailer discount. Additionally we have shown the change in the spending of customer over time and how is that related to customer demographics. You will also be able to see the top departments by sales and relationship between top departments sales with customer demographics.Yet another report you will find is how the marketing have affected customers in shaping their spending. Finally you will also see a causal relationship between marketing slots and sales to understand which are performing better.