Uncovering Insights in Sales Dynamics
We monitor the whole sales life cycle, from the first order placed through numerous channels (online or in-store), via many warehouses, and ultimately to the customer's door. We are also getting to know consumers along the route by learning more about their places of residence, and purchases. In addition to providing insightful business information, this study helps in planning next campaigns for marketing and sales. Various data operations has been performed to produce the visualisations, in order to understand the information which provides a thorough comprehension of the context of this data, including consumer preferences, sales dynamics, and the efficacy of sales teams.
Sales and Profits
The study of sales and profit points to important trends and numbers. The monthly sales average is approximately $2.58 million, with significant fluctuations over time but we saw a noticeable variation throughout the epidemic, indicating how much it affected consumer behavior and the dynamics of the market in the month of march where we can see a dip in the sales and profits trends. With an average monthly profit of around $964,834, the profitability trend is steady. With an average profit margin of 37.34%, the revenue to profit ratio is strongly converted. Understanding growth rates and seasonal effects is essential to expanding our knowledge because they have a big impact on our business plan.
Sales Channel Insights
We identified significant trends in our sales study from May 2018 to December 2020. In-store sales accounted for the majority of sales ($34 million), it somewhat decreased in 2020, probably as a result of limitations related to the pandemic. An impressive 70% growth in 2019 and ongoing expansion through 2020 have been observed in the Online channel, which confirmed to the shift of consumers toward digital platforms during the pandemic. While wholesalers and distributors had significant growth in 2019, wholesale experienced a slump in 2020. These revelations highlight how the pandemic affected consumer behavior and how quickly we adjusted to these shifts in the market.
Sales Channel Insights
California is in the lead with an outstanding total of 7,605 orders, demonstrating the state's substantial market presence. On the other hand, with just 74 orders, Arkansas offers a striking contrast and suggests future market expansion opportunities. The data indicates a wide range of regional demand patterns, with order volumes varying significantly from as few as 74 to as many as 7,605 and with total orders of 36,162 . The average number of orders per state is approximately 709. Higher orders are typically reported in wealthier or more urbanized states, suggesting a relationship between consumer behavior and economic status. Strategic planning can benefit greatly from this investigation, which shows areas where market activities should be adjusted or increased for improved outreach and resource allocation.
Average Shipping time by City
A comparison of shipment time across different cities provides some interesting information. With a standard deviation of approximately 1.69 days and an average shipment time of about 15.15 days, there is an appropriate level of variance in shipping times between cities. The dataset's extremes are especially helpful: Rockford (Township) has the quickest delivery time of 11.24 days, while Shreveport has the longest shipping time of 19.43 days. A closer look at the data reveals that 25% of the cities have shipping times of less than 13.91 days, while the median shipment time is 15.25 days, indicating a fairly even distribution of shipping times. Significantly, 75% of the cities have shipment timeframes of less than 16.28 days, highlighting the overall effectiveness in the majority of the places evaluated.
Average Product Turnaround Time by Warehouse (Procurement to Delivery)
Inventory management and associated costs are major expenditures for an organization. The bar chart depicts the average days, the product was held in stock across different warehouses. Over the course of three years, all warehouses have turnaround times that fall into a similar range: 105 to 112 days. This implies a uniform operation throughout. For all of the warehouses, there has been no apparent pattern or change over the years, indicating consistent process times. The small range shows that dedicated efforts were made to manage the inventory within that range. With an average turnaround time of 130.46 days, WARE-NBV1002 is the warehouse that is requiring the longest to turn around products. This could be attributed to a slower processing time or to different product kinds that need longer storage. The average days in inventory for the firm is 109 days, compared to Amazon, which has the highest days in inventory at 35.38 days in the last 13 years, which is very high. Above 60 days in inventory is considered high for an organization.
Lead time of the Orders
Important insights for maximizing customer happiness and operational effectiveness are revealed by a thorough delivery data analysis. Since most things are delivered in 21–22 days, this makes customers have reasonable expectations. Significant differences in delivery times between warehouses point to areas where procedures should be strengthened. The trend toward longer lead times, particularly in the 17–36 day range, suggests areas where shipping and storage operations could be made more efficient. The distribution looks similar to central limit theorem suggesting the number of deliveries fall into the buckets near to the mean. In order to provide with more consistent delivery experiences, one should be dedicated to minimizing the few occasions of exceptionally short (3-6 days) and very long (37-38 days) deliveries.
Analysis of Sales Channel and Regional Performance
With 3,298 orders, "In-Store" becomes the most popular sales channel, demonstrating a significant inclination toward traditional retail. The 'Northeast' lags behind with just 970 orders, indicating a region primed for expansion, while the 'West' leads with 2,784 orders in regional sales, indicating a strong market presence there. With 893 orders, the 'Wholesale' channel has the least activity, suggesting that it is not as popular as it could be. Sales vary significantly between channels and between areas, which highlights the significance of customized approaches. Different patterns of channel performance are seen in each location, which highlights the importance of region-specific strategies.
Analysing on Product Sales Over Time
In this graph we can see how the prodcut sales are changing over the time, what are products are popular during a particular time, it can be seen that the products in the top 10 has been constantly changing, For example sculptures rallied alot for 2 months in the year 2018 from oct to november, but decreased after, and acceessories rallied in the end, this graph can show dynamic demand of the top products that are top currently, using this inventory and supply can estimated and maintained. Another important observation that can be done is table lamps sales in nov to jan 2018 and again in nov - jan 2019 this can be due to winter season and its getting dark faster.
The dot chart shows the total sales for each product, and the order quantity is shown by the size of each dot. With larger dots denoting more orders, this visual representation makes it easy to immediately determine which products are the best performers in terms of sales and order quantity. The figure is especially helpful for quickly recognizing patterns and outliers. In terms of order quantity, "Collectibles" ranks in the top 10 products and has the largest sales. "Serveware" ranks among the top in order quantity and follows closely in sales. The large order quantities for "Wall Frames" and "Rugs" account for their high sales numbers. Because of their significant impact on overall sales and order quantity, these products likely require particular focus in sales strategy and inventory management. It's also feasible that some goods are more expensive per unit, which would account for their notable sales numbers in spite of the large order quantity.
Analyzing the Impact of Median Income on Total Sales
The sales data scatter graph demonstrates a wide range of sales variability across various median incomes, with a significant concentration at lower income levels, indicating a strong client base in that area. Sales remain substantial at higher income levels despite a decrease in data points, suggesting a market for expensive products. The lack of a clear upward trend suggests that variables like variety of products and local economic conditions are also important, implying that sales are not exclusively influenced by median income.
Analysing on Sales Representatives Performance
For an organization, keeping track of performance parameters and motivating individuals who perform above the required norms is important. The performance indicator visualization compares the average sales of the Salesperson against the average sales in a month. For example, Adam Hernandez and Keith Griffin have continued to perform above the national average continuously, and Todd Roberts and Anthony Torres have performed below the national average. Hernandez's total sales in 2019 came to approximately above one million USD. This complete perspective supports training, rewarding sales accomplishments, and making strategic decisions.