At a glance
Industry
Retail Industry
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.
Our
Process
The Challenges
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Data Availability: The absence of detailed insights from the analytics platform hindered the ability to measure bundle performance.
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Manual Process: The Third-party Bundle app required manual data handling, which was time-consuming and prone to errors.
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Limited Functionality: Inability to filter data by specific dates or export files easily hindered timely decision-making.
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Strategy Gaps: Without accurate data, identifying underperforming bundles and adjusting marketing strategies was challenging.
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.
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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 Impact
Automating data analysis resulted in a dramatic increase in accuracy, reducing manual work by 85%. By utilizing AI to predict bundle sales trends, we achieved an 11% increase in bundle sales year-on-year. Additionally, AI recommendations improved conversion rates by 10% for newly launched bundles. The automated system now allows the marketing team to make quick, informed decisions, leading to more effective strategies and increased profitability.
11
%
Increase bundle sales
year-on-year
10
%
Improve conversion rates
for newly launched bundles
85
%
Reducing manual work
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