Market-Analysis-sales-data

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SUPERMARKET SALES ANALYSIS REPORT

Prepared by Thatayotlhe Dinona
Date: 23/11/2024

PROJECT OVERVIEW

This analysis intends to investigate the market sales of an imaginary supermarket to gain insights and identify areas of improvement and optimize operations to drive growth and profitability.

OBJECTIVES

  1. To determine the times of the day when sales are highest?
  2. To analyse customer ratings to gauge satisfaction levels?
  3. To determine the payment methods used by customer?
  4. To determine which product line are most profitable?
  5. To analyse sales by customer demographic (gender and member)
  6. To compare sales performance across branches
  7. To determine the total sales revenue over a specific period?

DATA ANALYSIS METHODOLOGY

This is a systematic process of inspecting ,cleaning, transforming data with the goal of discovering useful information and this was done using python with libraries such as pandas, matplotlib , seaborn and numpy imported.

  • DATA COLLECTION

    The dataset used was from Kaggle the dataset shape is 1000 rows and 13 columns. Data quality assessment was conducted to ensure the data is accurate, free from null values and consisent and also relevant to the analysis objectives.

  • DATA CLEANING

    The following common data quality issues were checked with the help of pandas library which is well suited for data manipulation and data cleaning.

  • Missing data
  • Inconsistent data formatting
  • Outliers
  • Duplicates
  • Incorrect data type
  • Renaming columns data cleaning

The dataset was further refined by correcting erros of data type mismatches , renamed columns and further removed columns which were not applicable to my analysis.

  • DATA EXPLORATION

    Data exploration techinques were employed which involves descriptive statistics to provide summary statistics(mean, mode, median, quartiles,standard deviation,etc) to have a rough understanding of the data before diving deep into earthing insights. Histograms, boxplot/whisker, kernel density were of use to help with identifying outliers,patterns and trends in the dataset. heatmap summary stat The density distribution of customer ratings shows a single peak around a rating of 7, suggesting that this is the most common rating. The curve is relatively wide, indicating a high variability in customer ratings. ratings ditribution

  • DATA VISUALISATION

    Visuals were created to support analysis and visualise patterns, trends and insights of the data.

  1. Total sales revenue over a specific period?

    The figure below illustrates the sales trends across different months. It shows that sales fluctuated significantly over this period. Sales_revenue_over_specific_period

  2. Payment methods used by customer?

    The figure below illustrates the most used payment methods by customers, which are e-wallet and cash. This insight can help us better cater to their preferences. Payment methods used by customer

  3. Customer ratings to gauge satisfaction levels?

    The figure below depicts customer ratings for different products and services. This can help us understand customer perceptions. Health and beauty products received the lowest ratings, indicating a need for review and improvement to enhance their appeal.

Gauge ratings (1)

  1. Sales by customer?

The bar chart below shows the total sales categorized by gender. From the chart, we can see that the total sales for females are higher than those for males. This information is crucial for understanding the purchasing behavior of different genders, which can help in tailoring marketing strategies. The higher sales among females suggest that marketing efforts could be more focused on products that appeal to women to maximize revenue. Overall, the chart indicates that females contribute more to total sales, highlighting the importance of targeting this demographic in future campaigns.

Demographics

  1. Most profitable product line ?
    Food and Beverages and fashion accessories product line shows the highest gross income, it might be beneficial to invest more in this category to maximize profits while Health and Beauty show the lowest gross income. Overall, the chart highlights the product lines that contribute the most to the supermarket profitability, guiding strategic and targeted advertising.

    Screenshot 2024-11-23 203136

  2. Sales by Branch name
    The bar chart below illustrates the total profitability of different branches. From the chart, we can see that Branch C has the highest total profitability compared to the other branches. This indicates that Branch C is performing exceptionally well in terms of generating revenue and managing costs effectively. The high profitability of Branch C suggests that it might have a larger customer base, higher sales volume, or more efficient operations compared to the other branches. Overall, the chart highlights the success of Branch C, which could serve as a model for other branches to improve their profitability. sales performance

    RECOMMENDATIONS

    • Focus on High-Performing Product Lines:
      Recommendation: Invest more in less profitable products by consider expanding the product range or offering promotions to boost sales further. This can help maximize revenue.
    • Improve Low-Rated Products:
      Recommendation: Conduct a detailed review of the health and beauty products, which received the lowest ratings by gathering customer feedback to understand specific issues and make necessary improvements because by enhancing these products can improve customer satisfaction and potentially increase sales in this category.
    • Cater to Preferred Payment Methods:
      Recommendation: Ensure that e-wallet and cash payment options are prominently available and easy to use, as these are the most preferred payment methods by customers. Also, making the payment process smoother can enhance the customer experience and encourage repeat purchases.

CONCLUSION

  • Product Line Profitability:
    Conclusion: The analysis shows that certain product lines, such as food and beverages and fashion accessiories, are significantly more profitable than others. This indicates a strong customer preference and higher sales volume for these products.
  • Customer Ratings:
    Conclusion: Customer ratings reveal that health and beauty products are not meeting customer expectations. This calls for a review and improvement of these products to enhance their market performance.
  • Payment Methods:
    Conclusion: The most used payment methods are e-wallet and cash. This insight can help tailor the payment options to better meet customer preferences, improving the overall shopping experience.