FMCG: Uncovering Innovation Through Advanced Analytics
Services: Data Engineering & Reporting, AI for Data
Business Functions: Sales & CX
Technology: Power BI, Databricks
The goal was to identify growth drivers for a market player within a specific category and region.
The goal was to identify growth drivers for a market player within a specific category and region. By analyzing granular data, we uncovered market trends and presented the findings in a user-friendly format for actionable insights. A structured „T-Shaped” analytics approach helped navigate across product, time, and competitor dimensions, all within a unified framework.
Our solution provided key market insights, focused on Amazon, and integrated AI-driven analytics for deeper online channel analysis. This enabled the client to monitor innovations more frequently, accelerate trend identification, and improve the success rate in spotting emerging product claims.
Challenge
Growth Driver Identification
The primary objective was to identify the growth drivers for a specific market player within a particular product category and geographic market.
Granular Data Analysis
A drilldown was required to the lowest level of product hierarchy to uncover the root causes of changes in data reflecting the latest market trends.
User-Friendly Data Presentation
It was necessary that the data be presented in a clear format that facilitated ease of analysis allowing stakeholders to identify actionable insights.
Structured Analytics Approach
“T-Shaped” analytics concept was followed enabling structured and detailed examination across various hierarchies and dimensions such as product, time and market players.
Unified Analytical Framework
All insights needed to be consolidated under a single analytical umbrella allowing for seamless navigation across different data prospects.
Growth Driver Identification
The primary objective was to identify the growth drivers for a specific market player within a particular product category and geographic market.
Granular Data Analysis
A drilldown was required to the lowest level of product hierarchy to uncover the root causes of changes in data reflecting the latest market trends.
User-Friendly Data Presentation
It was necessary that the data be presented in a clear format that facilitated ease of analysis allowing stakeholders to identify actionable insights.
Structured Analytics Approach
“T-Shaped” analytics concept was followed enabling structured and detailed examination across various hierarchies and dimensions such as product, time and market players.
Unified Analytical Framework
All insights needed to be consolidated under a single analytical umbrella allowing for seamless navigation across different data prospects.
Solution
Comprehensive Market Insights
Market changes were revealed, the drivers behind these changes were identified, and performance against competitors was benchmarked. All major geographic markets were covered with particular focus on Amazon.
Time-Based Analysis
Flexible time perspectives are offered as well as supporting operational, tactical and strategic reviews, and support in adapting to both short and long term trends.
Advanced Analytics Integration
Combining diverse data sources with an AI engine allows for deeper insights into the online medium, facilitating the analysis of emerging trends.
Comprehensive Market Insights
Market changes were revealed, the drivers behind these changes were identified, and performance against competitors was benchmarked. All major geographic markets were covered with particular focus on Amazon.
Time-Based Analysis
Flexible time perspectives are offered as well as supporting operational, tactical and strategic reviews, and support in adapting to both short and long term trends.
Advanced Analytics Integration
Combining diverse data sources with an AI engine allows for deeper insights into the online medium, facilitating the analysis of emerging trends.
Results
Frequent Innovation Spotting
The ability to monitor innovation and competitor movements more frequently were implemented as well as transitioning from quarterly to weekly insights.
Accelerated Trend Identification
The process of identifying new and waning trends was expedited by shifting from quarterly to monthly updates.
Enhanced Online Channel Analysis
Through the integration of AI and multiple data sources, deeper insights into the online medium were delivered.
Improved Success Rate
Achieved a higher success rate through staying ahead of market shifts by being able to identify trending product assertions and features.
Frequent Innovation Spotting
The ability to monitor innovation and competitor movements more frequently were implemented as well as transitioning from quarterly to weekly insights.
Accelerated Trend Identification
The process of identifying new and waning trends was expedited by shifting from quarterly to monthly updates.
Enhanced Online Channel Analysis
Through the integration of AI and multiple data sources, deeper insights into the online medium were delivered.
Improved Success Rate
Achieved a higher success rate through staying ahead of market shifts by being able to identify trending product assertions and features.
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