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Based on the data files and fields you provided, here are some suggestions for
visualizing and analyzing your inventory data:
1. Sales Performance: Visualize the sales performance by product, season,
and distribution channel. This can be done by linking the product_id in
the COGS.xlsx and Retail_price.xlsx files with the product_syle_color in
the New_Core_Classification.xIsx file.
2. Inventory Turnover: Calculate the inventory turnover ratio by dividing
the cost of goods sold (from COGS.xlsx) by the average inventory during
the same period. This can help you understand how efficiently your
inventory is being managed.
3. Profit Margin: Calculate the profit margin for each product by
subtracting the cost price (from COGS.xlsx) from the selling price (from
Retail_price.xlsx). This can be visualized over time to see how profit
margins are changing.
4. Seasonal Sales Trends: Analyze the lauch_season and sales_season
fields in the New_Core_Classification.xIsx file to understand seasonal
sales trends. This can help with forecasting future sales and managing
inventory levels.
5. Product Status: Use the final_status field in the
New_Core_Classification.xIsx file to track the status of each product. This
can be useful for identifying products that are discontinued or out of
stock.
6. Assortment Decisions: Analyze the b2c_assortment, b2b_assortment,
and total_assortment fields in the New_Core_Classification.xIsx file to
understand business decisions. This can help you identify trends and
make future assortment decisions.
7. Distribution Channel Analysis: Use the Distribution Channel.xIsx file to
analyze the performance of different distribution channels. This can
include visualizing sales by region, city level, store concept, trade term,
and store type.
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8. Store Performance: Analyze the start_month, start_year, end_month,
and end_year fields in the Distribution Channel.xIsx file to understand
the lifespan and performance of different stores.
Remember, these are just suggestions. The specific visualizations and analyses
will depend on your business needs and objectives. It's also important to
ensure that your data is clean and accurate before starting any analysis. Hope
this helps! �