Two people shaking hands at a business meeting

Automating Bundle Sales Analysis with Tableau for Improved Strategy and Performance

Consult With Our Experts

DIGITAL MARKETING

At a glance

Industry

Retail

Challenge

Challenges included limited data insights, time-consuming manual processes, and restricted app functionality, making it difficult to measure bundle performance and adjust marketing strategies effectively.

Success History

Automated data analysis cut manual work by 85%, boosted bundle sales by 11% YoY, and improved new bundle conversions by 10%. AI-driven insights enabled faster, more effective marketing decisions, increasing profitability.

Problem Statement:

In the retail e-commerce industry, selling bundles or kits is a proven strategy to enhance sales and conversion rates. However, we encountered a significant bottleneck: our native analytics tool lacked detailed data on bundle sales. This limited visibility made it challenging to identify high-performing products, evaluate sales impact, or implement data-driven marketing strategies

A question mark inside a gear surrounded by other gears.

Data transformation from one spreadsheet to another

The Challenges

1. Data Availability

The absence of detailed insights from the analytics platform hindered the ability to measure bundle performance.

2. Manual Process

3. Limited Functionality

4. Strategy Gaps

<a href="https://www.freepik.com/free-photo/problem-solving-concept-with-man-working_34200672.htm">Image by freepik</a>

Our Solution

To solve these issues, we integrated our custom analytics platform with a powerful data visualization tool, automating data extraction and analysis. This integration allowed for seamless synchronization of data, eliminating manual processing, and providing real-time insights. Custom dashboards were created to track key metrics, such as sales performance, profit margins, and conversion rates for each bundle.

To enhance the analysis further, we implemented AI-driven predictive analytics. The AI tools helped detect patterns, forecast bundle performance, and identify areas for optimization. By analyzing historical sales data, AI algorithms recommended the best-performing bundles and highlighted underperforming ones that required strategic adjustments. Automated reporting features allowed for date-specific filtering and easy export, ensuring quick access to critical data.

Business Outcomes

0%

Increase bundle sales (YoY)

0%

Improve conversion rates for newly launched bundles

0%

Reducing manual work