Lab 1 S5 T Year Customer Number Of Orders Per Year Sales Per ✓ Solved

Lab 1 S5 Tyearcustomer Number Of Orders Per Year Sales Per Yearcoupo

The Excel table shows years 2018 and 2019 data related to the number of orders and dollar sales per customer for a certain company. The manager asked you to perform the following analysis related to sending discount coupons:

Develop a pseudo code that will offer the following discounts:

  • $159, % coupon for those customers whose $ Sales per year were less than $200,000.
  • $147, % coupon for those customers whose $ Sales per year were between $200,000 and $300,000.
  • $203, % coupon for those customers whose $ Sales per year exceeded $300,000.

Develop your if statements in column E so that E2 … E49 will show the coupon value based on the criteria above.

Format the $ Sales per year column with a graded color scale (do not manually highlight).

Edit your work so that random number generations stop in both the Number of Orders and $ Sales per year columns.

Rearrange your spreadsheet so that listings are organized based on coupon value.

Make sure you keep saving your file and submit to Blackboard before time is up. You may email your file as a last resort; however, it won't be considered submitted on time if modifications took place past the due date.

Sample Paper For Above instruction

The purpose of this study is to design a systematic approach via pseudo code and Excel functionalities to analyze customer sales data for implementing targeted discount coupons. The goal is to utilize customer purchase history, specifically annual sales data, to determine appropriate coupon values that incentivize continued patronage while maintaining profitability. Furthermore, the study aims to enhance data visualization through conditional formatting and organize data efficiently for strategic decision-making.

Introduction

In modern retail management, personalized discounts are essential tools for fostering customer loyalty and increasing sales. Companies often rely on detailed customer data to craft tailored incentives. This research outlines a step-by-step methodology involving pseudo code development, Excel formulas, conditional formatting, and data organization to execute targeted discounting strategies based on annual sales figures.

Methodology

Developing Pseudo Code for Discount Logic

The initial step involves creating pseudo code to categorize customers based on their total sales per year. Pseudo code is a simplified, language-agnostic outline that facilitates translating logic into Excel formulas. The required conditions are:

  • If sales are less than $200,000, assign a $159 coupon.
  • If sales are between $200,000 and $300,000, assign a $147 coupon.
  • If sales exceed $300,000, assign a $203 coupon.

Example pseudo code:

FOR each customer in dataset:

IF sales

coupon_value = 159

ELSE IF sales >= 200000 AND sales

coupon_value = 147

ELSE

coupon_value = 203

END FOR

Implementing IF Statements in Excel

The above logic can be translated into nested IF statements within Excel. Assuming the $ Sales per year are in column C starting from C2, the formula in column E (e.g., E2) would be:

=IF(C2

Dragging this formula down from E2 to E49 applies the logic to all relevant rows.

Conditional Formatting with Graded Color Scale

To visually interpret sales performance, apply conditional formatting to the $ Sales per year column (column C). Select the range C2:C49, then navigate to Conditional Formatting > Color Scales > choose a gradient (e.g., green to red). This highlights high and low sales dynamically based on data distribution.

Filtering Random Number Generation

To stop random number generation in both the Number of Orders and $ Sales per year columns, replace formulas with static values. Select the entire columns, copy, then paste as values. This halts automatic recalculations, ensuring data stability for analysis.

Rearranging Data by Coupon Value

To organize the spreadsheet based on coupon values, select all data and apply a sort by the coupon value column (E). This restructuring prioritizes customers based on their assigned discounts, aiding targeted marketing campaigns.

Conclusion

The integration of pseudo code, Excel formulas, conditional formatting, and data organization provides a comprehensive framework for targeted customer incentives. By tailoring coupons based on sales data, the company can foster stronger customer relationships and optimize promotional strategies. The outlined steps facilitate efficient data analysis and decision-making processes in retail management contexts.

References

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