Campaign Performance Analysis

 

Description:

Study case Understanding Business Problem, Data Understanding, EDA using Excel & Spreadsheet

Deck Link:

HERE

Skill Set:

Understanding Problem Business, Data Understanding, Execl & Spreadsheet, EDA

About

The project revolves around T okoBli, focusing on their e-commerce initiatives. The main problems identified include the lack of actionable insights on campaign performance and uncertainty in determining the most cost-effective campaigns. The project aims to evaluate campaign performance across key metrics, analyze discount efficiency, identify high-performing product categories, and provide data-driven business recommendations for future campaigns.

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Context & Problem

The context of this project involves addressing key issues faced by TokoBli, an e-commerce platform. It identifies two primary business problems:

1. Lack of Actionable Insights on Campaign Performance : The current processes do not effectively extract meaningful information from various campaign scenarios (10/10, 11/11, 12/12). This gap hampers the company's ability to make data-driven decisions for future marketing strategies.
2. Uncertainty in Identifying Cost-Effective Campaigns : TokoBli seeks to determine which campaign scenario yields the best revenue growth and transaction volume while also optimizing the discount budget, utilizing a metrics-based analytical approach.

The project's objectives include evaluating campaign performance, analyzing discount efficiency (measured as Revenue/Discount Ratio), identifying high-performing product categories, and ultimately providing actionable business recommendations for future campaigns. These efforts aim to improve overall marketing effectiveness and support better decision-making going forward.

Objective

The project objectives for TokoBli focus on enhancing the effectiveness of their marketing campaigns through strategic analysis. The key objectives are:

1. Evaluate Campaign Performance : Assess the performance of various campaigns across key metrics to understand their impact on business outcomes.
2. Analyze Discount Efficiency : Calculate the Revenue/Discount Ratio to determine how effectively discounts are driving sales and overall revenue.
3. Identify High-Performing Product Categories : Investigate which product categories are performing well within the campaigns to inform future marketing efforts.
4. Provide Data-Driven Business Recommendations : Use the insights gained from the analysis to offer actionable recommendations for optimizing future marketing campaigns, ensuring better decision-making based on factual data.

These objectives aim to equip TokoBli with the knowledge needed to optimize their marketing strategies and enhance overall business performance.

Process

1. Data Collection : Gather relevant data from each campaign scenario (10/10, 11/11, 12/12), including metrics on revenue, transactions, product sales, and discount budgets.
2. Campaign Performance Evaluation : Analyze the collected data to evaluate the performance of each campaign against key metrics, such as revenue growth, customer acquisition, and sales volume.
3. Discount Efficiency Analysis : Calculate the Revenue/Discount Ratio for each campaign to assess how effectively discounts are being utilized to drive sales.
4. Identification of High-Performing Product Categories : Review the data to identify which product categories achieved the best performance during the campaigns.
5. Recommendations Development : Based on the insights gathered, develop actionable, data-driven recommendations for optimizing future campaigns.

Considerations

1. Data Accuracy : Ensuring the data collected is accurate and reliable is crucial for deriving meaningful insights.
2. Market Trends : Consider current market trends and consumer behavior, which might influence campaign performance and effectiveness.
3. Budget Constraints : Evaluate the limitations of the discount budget and its impact on campaign strategies to maximize ROI.
4. Stakeholder Input : Engage with stakeholders to gather insights on existing strategies and align recommendations with overall business goals.
5. Future Scalability : Consider how the findings and recommendations can be scaled for future campaigns, ensuring sustainability in marketing strategies.

Methodology

1. Define the Research Questions : Establish clear research questions based on the identified problems, such as:

   • How can TokoBli extract actionable insights from campaign performance data?
   • Which campaign scenarios yield the highest revenue growth while optimizing the discount budget?

2. Data Collection :

   • Gather sales and campaign data from the platforms used during significant campaign events (10/10, 11/11, 12/12).
   • Collect metrics including total revenue, number of transactions, number of customers, products sold, and total discount budget.

3. Data Cleaning and Preparation :

   • Process the collected data to eliminate any inconsistencies or errors, ensuring accuracy.
   • Organize the data in a structured format suitable for analysis.

4. Statistical Analysis :

   • Conduct a thorough analysis of campaign performance using statistical tools to evaluate key metrics.
   • Calculate the Revenue/Discount Ratio for each campaign to assess discount efficiency accurately.
   

5. Performance Comparison :

   • Compare the performance of different campaign scenarios to identify which strategies produced the best results.
   • Focus on identifying trends and patterns that reveal customer preferences and successful tactics.
   

6. Identifying High-Performing Categories :

   • Analyze the data to pinpoint which product categories enjoyed the most success during the campaigns.
   • Use this information to highlight potential areas for future marketing efforts.
   

7. Develop Recommendations :

   • Formulate actionable and data-driven recommendations based on the analysis findings.
   • Ensure that the recommendations consider budget constraints, market trends, and stakeholder input.

8. Report Findings :

   • Compile the results and insights into a comprehensive report, summarizing the analysis and the recommendations.
   • Present the findings to relevant stakeholders for informed decision-making.

Results & Learning

1. Understanding the Business Problem :

   The project successfully identified and clarified the key challenges faced by TokoBli, specifically the lack of actionable insights on campaign performance and the uncertainty in determining the most cost-effective campaigns. This understanding informed the analysis approach and set the stage for targeted evaluations.

2. Data Overview :

   The transaction dataset consisted of 10,159 unique transaction IDs, encompassing critical information, including transaction details, customer details, product specifics, and sales metrics. Key issues such as incompatible data types, missing data points, duplicated entries, and unorganized categories were identified, leading to a thorough data cleaning process to ensure quality and accuracy before analysis.

3. Exploratory Data Analysis (EDA) :

   EDA was performed using spreadsheet tools to visualize and summarize the data effectively. Key findings from the EDA included:

   • Identification of trends in customer purchases over different campaign periods.
   • Exploration of discount impacts on sales volume, revealing correlations between discount rates and transaction volumes.

4. Statistical Analysis :

   Statistical methods applied through spreadsheet software allowed for a comprehensive evaluation of campaign performance. Metrics calculated included:

   • Revenue and transaction growth rates across different campaigns.
   • Revenue/Discount Ratios to measure the efficiency of discount strategies.

   The analysis revealed actionable insights, such as which campaigns resulted in higher revenue and better transaction volume, alongside identifying high-performing product categories.

Learning Outcomes:

• Data Quality is Crucial : The analysis emphasized the importance of data quality and the need for meticulous data cleaning to draw valid insights.
• Data-Driven Decision Making : The project validated that a metrics-driven approach significantly enhances the quality and effectiveness of marketing strategies.
• Continued Research : Future opportunities for understanding customer behavior and preferences emerged from this project, indicating potential areas for ongoing investigation.