Use Case

March 12, 2024

Sales Analysis Use Case

Step by step Sales Analysis Use Case to implement effective sales strategies to maximize revenue & market share?

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Coca-Cola, the global beverage giant, serves up refreshment to billions worldwide with its vast array of soft drink brands spanning over 200 countries. Picture this: every single day, a whopping 1.9 billion servings of its fizzy concoctions are enjoyed by thirsty consumers.

Behind the scenes, there's a ton of data swirling around – everything from making drinks to getting them to your local store. Coca-Cola navigates this data sea using a smart, data-driven strategy to steer their big decisions.

In this article, we'll understand how companies like Coca-Cola might uses sales analysis to hit its annual revenue target of $45 billion and take a closer look at How to use Sales Analytics use case to implement effective sales strategies to maximize revenue & market share.

About Dataset 

Alright, let's take a closer look at our Dataset: Beverage Sales Dataset

So, we've got this awesome Beverage Sales Data. We can see what drinks are selling where, whether it's online or in vending machines. You've got everything from transaction dates to retailer details to product specifics. It covers all sorts of beverages and sales channels, like online or vending machines.

And the best part?

This data is super helpful for spotting trends, figuring out what customers like, and seeing how well new drinks are doing and best suitable for sales analysis.

Each row in the dataset corresponds to an order made by a customer. We have the following features:

Sales Information
Transaction Information
Column Name Data Type Unique Values Description
SalesChannel String 11 The platform or method through which the sale was made.
ChannelType String 4 Categorizes the sales channel (e.g., Online, Retail).
OrderQty Integer 250 The quantity of items ordered in the transaction.
SalesValue Float 2481 The total value of the sales transaction.
Discount Float 4 The discount amount offered on the MRP for the transaction.
Country String 13 The country where the transaction occurred.

Product Information
Transaction Information
Column Name Data Type Unique Values Description
ProductItemID String 153 Unique identifier for the product.
Category String 2 The category to which the product belongs.
Brand String 16 The brand of the product.
SpecificProductName String 39 The specific name of the product.
Packaging Type String 5 Details about the product's packaging (Type, Quantity, Category).
Packaging Quantity Integer 23 Details about the product's packaging (Type, Quantity, Category).
Packaging Category String 2 Details about the product's packaging (Type, Quantity, Category).
PackagingQty_N_ml Integer 23 The quantity of the product in milliliters for standardized comparison.
MRP_UnitPrice Float 16 Maximum Retail Price per unit of the product.
Product_Launch_Date Date 152 The date when the product was launched in the market.
IsNewProduct Boolean 2 Indicator whether the product is new (True) or not (False).

Financial Information
Transaction Information
Column Name Data Type Unique Values Description
CostPerUnit Float 23 The cost incurred per unit of the product.
MarginPercentage Float 3 The percentage of margin made from the transaction.
Profit Float 2272 The profit earned from the transaction.

Retailer Information
Transaction Information
Column Name Data Type Unique Values Description
RetailerId String 650 Unique identifier for the retailer.
RetailerName String 263 The name of the retailer.
State String 53 The geographical location of the retailer (State, City).
City String 57 The geographical location of the retailer (State, City).
Lat Float 206 Latitude and longitude coordinates of the retailer's location.
Long Float 205 Latitude and longitude coordinates of the retailer's location.

Transaction Information
Transaction Information
Column Name Data Type Unique Values Description
SrNo Integer 25000 Serial number of the transaction.
TransactionDate Date 1492 The date when the transaction occurred.

How to implement effective sales strategies to maximize revenue & market share?

Before diving into the intricacies of data analysis and strategy implementation, it's crucial to establish a solid foundation. We will follow the 4 factors of Data Analysis and that are : 

1. Identify the users or stakeholders for the dashboard.

2. Design Empathy Map to define Users' Goals and Challenges or pain points.

3. Identify Metrics or KPIs Matter the Most.

4. Understand the Objectives and Goals.

5. Ask Business Questions

I know it looks a bit overwhelming that’s why in this article, we'll lay the foundation for a top-notch sales analysis. 

Step 1: Identify the users or stakeholders for the analysis.

The first step in any this analysis is to identify the primary users or stakeholders who will interact with the sales dashboard. These individuals play a crucial role in shaping the dashboard's design, functionality, and content.

User Persona: Sales Manager

This individual is responsible for steering the sales team towards meeting revenue targets and expanding market share. Understanding the background, roles, responsibilities, needs, and pain points of this persona allows us to tailor the sales dashboard to meet their specific requirements effectively.

  • Develop and implement effective sales strategies: Create and execute sales strategies tailored to diverse markets and consumer segments to maximize revenue generation.
  • Lead and motivate the sales team: Provide leadership, guidance, and motivation to the sales team to achieve and exceed sales targets.
  • Analyze sales data and performance: Utilize data analytics to assess sales performance, identify growth opportunities, and refine sales tactics.

  • Strong leadership and communication skills: Ability to lead and communicate effectively with the sales team and stakeholders.
  • Analytical and strategic thinking abilities: Proficiency in analyzing data and developing strategic plans to drive sales growth.
  • Results-driven mindset and adaptability: Motivated by achieving sales targets and adaptable to changing market conditions.
  • Customer-focused approach: Dedication to understanding customer needs and delivering excellent service to build long-term relationships.

  • Navigating competitive market conditions and responding to competitor strategies.
  • Adapting sales strategies to changing consumer preferences and market trends.
  • Managing and motivating a diverse sales team to achieve high performance.
  • Ensuring product availability and visibility across a wide range of retail environments.

Step 2: Design Empathy Map 

To design a sales dashboard that truly resonates with the persona, you need to understand their thoughts, feelings, and experiences.

You'll explore what they see, hear, think, feel, say, and do.

By empathizing with your persona's perspective, you'll gain insights into their aspirations for revenue growth, their concerns about market changes, and their determination to drive success. Understanding their goals and challenges enables us to develop a sales dashboard that addresses their pain points and supports their objectives.

Step 3: Identify the Key Performance Indicators (KPI’s)

Key Performance Indicators (KPIs) serve as the compass guiding our persona's journey towards revenue growth and market expansion. These metrics provide tangible benchmarks for measuring success and identifying areas for improvement. Identify KPIs such as

KPI Name Columns Used Formula Description
Sales Volume OrderQty Sum(OrderQty) Total units sold, reflecting market demand.
Market Penetration Rate IsNewProduct, OrderQty (Sum(OrderQty of New Products) / Sum(OrderQty)) * 100 Percentage of new products sold compared to all products, indicating success of launches.
Discount Impact Discount, SalesValue, Profit Average(Discount), Correlation(Discount with SalesValue and Profit) Average discount provided and its effect on sales volume and profitability.
Product Mix Diversity ProductItemID, OrderQty Count(Distinct ProductItemID), Sum(OrderQty) per ProductItemID Variety of products sold, indicating market reach and consumer preference diversity.
Geographic Market Share State, City, SalesValue Sum(SalesValue) per State/City Sales distribution across different regions, showing market dominance.
Sales Channel Effectiveness SalesChannel, OrderQty, Profit Sum(OrderQty) and Sum(Profit) per SalesChannel Performance of different sales channels in terms of volume and profitability.

By tracking these KPIs through the sales dashboard, our persona gains real-time visibility into the health and performance of the sales organization.

Step 4: Understand the Goals & Objectives of User

Now, on the basis of Empathy Map and KPI’s, we need to define our goals and objectives of the Users. So, that it will align with the data story functionalities to ensure decision making. Here are the Key Objectives & Goals 

  • Develop and implement effective sales strategies to maximize revenue and market share for beverage products.
  • Analyze sales data to identify opportunities for growth and areas for improvement in both product offerings and sales tactics.
  • Drive the sales team towards achieving and surpassing sales targets through motivation, training, and performance monitoring.

  • To achieve or exceed sales targets for Coca Cola's range of beverage products.
  • To increase brand presence and market share in existing and new markets.
  • To effectively launch new products and ensure their success in the market.
  • To enhance customer satisfaction and loyalty through excellent service and product availability.

Based on the defined goals & objectives, your next step will be to provide actionable insights to make a mark on Business Decisions.

Step 5: Ask Relevant Data Question

Finally, to conclude your analysis, you need to ask right questions. These questions should be directly tied to the objectives and goals identified earlier and should guide our exploration of the data. By asking insightful questions, we can uncover hidden patterns, identify areas for improvement, and generate actionable insights that drive informed decision-making. Here are following Business Questions to ask:

1. What is the total order quantity and sales amount for all time? How has sales changed over the years?

Metric: Order Quantity, Total Sales Amount

Insights: This analysis will provide the total sales generated in terms of total order quantity and amount i.e. sales of $366.4 M with 6.3 M orders. As we can see that there are not many changes in sales over the years.

SQL Code: Order Quantity
  SUM([OrderQty]) [sumorderquantity]

SQL Code: Total Sales Amount
   SUM([SalesValue]) [sumsale] 

SQL Code: Sales by year
  DATEADD (YEAR, DATEDIFF (YEAR, 0, [TransactionDate]), 0) transactiondate,
  SUM([SalesValue]) [sale]
  DATEADD (YEAR, DATEDIFF (YEAR, 0, [TransactionDate]), 0)
  [transactiondate] ASC;

2. What are the top 10 countries and brands by sales?

Metric: Total Sales

Insights: India seems to be a major market for the sales of Beverages as it is generating sales of 25% overall sales. In terms of brand, most of the sales are generated from sales of Coca-cola with 15%, followed by Georgia and Fanta.

SQL Code: Top 10 Country by Sales
  top 10 [Country] country,
  SUM([SalesValue]) [sale]
  [sale] DESC;

SQL Code: Top 10 Brands by Sales
  top 10 [Brand] brand,
  SUM([SalesValue]) [sale]
  1 = 1
  AND [Country] IN ('India')
  [sale] DESC;

3. Is there any correlation between cost per unit and total sales? Does low cost per unit mean more sales?

Metrics: Cost per Unit, Sales

Insights: Brands such as Coca-cola, Fanta, Limca, Sprite and RimZim are generating high sales with low cost per unit, while brands like Honest Tea, Schewppes are performing badly despite their very low cost per unit.

SQL Code: Cost per Unit
  [Brand] brand,
  SUM([SalesValue]) [sale],
  AVG([CostPerUnit]) [costperunit]


  • With this analysis, we were able to observe the total sales of beverages and sales being constant over the years. We can assess the need for more strategic campaigns as sales have been stagnant in recent years.
  • As most of the sales are coming only from India, the focus on the other countries with market potential should be prioritized.
  • With some of our beverages performing poorly despite having low cost per unit is a big concern. The strategies should be made for those products as they are not contributing significantly to overall sales.

Explore Sales Analytics Data Story Here👇

Slideshow Demo
Sales Analysis Project

By framing this data story in alignment with business goals, organizations can get deeper insights that drive impactful decisions.


By combining a user-centric approach with data-driven insights and strategic inquiries, organizations can navigate the complexities of their sales with confidence and agility. The end goal is not just efficiency but the creation of a sales that adapts, evolves, and serves as a strategic asset in a competitive marketplace.

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