Driving Innovation


Rubiscape's Impact in the

E-Commerce Industry

Solutions build with Rubiscape

Implement Rubiscape’s AI-enabled Solutions! Geared for the future!



Foresight Action: Demand Sensing Controls!

Predict the future, optimize inventory, and maximize profits with real-time demand insights.

Goal

  • Implement Demand Sensing: Enhance forecast accuracy for FMCG operations.
  • Optimize Operations: Minimize costs and boost customer satisfaction.
  • Strategic Decision-making: Utilize data-driven insights for resilience and competitive marketing alignment.

Technique

  • Statistical Analysis, Time Series Forecasting, Visualization.

Impact

 

  • To aid the FMCG companies to reduce stockouts and excess inventory with enhanced predictive capabilities.
  • Optimize manufacturing resources by aligning production with real-time demand signals.
  • Quickly adapt to market changes through actionable insights, fostering operational flexibility.
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Unveiling Loyalty: Predict Customer Lifespan

AI models pinpoint high-value customers, driving targeted engagement and long-term growth.

Goal

  • To identify high, medium, and low-value customer segments.
  • To provide personalized offers and experiences to customers.
  • To allocate resources efficiently to businesses for targeting customers with the highest CLV potential and predict customer churn.

Technique

  • Feature Engineering, Segmentation Techniques, RFM Analysis, Clustering and classification modeling, Visualization.

Impact

  • Guided resource allocation, marketing strategies, and customer service efforts.
  • Offering cross-selling and upselling opportunities to customers with CLV potential.
  • CLV helps businesses identify risks associated with over-reliance that encourages diversification and risk management strategies.

Unmasking Moves: Bank Transactions Tells

Analyze spending patterns, predict trends, and optimize services with insightful bank transaction analysis.

Goal

  • To identify spending and investment habits of the customers and segment them corresponding to age groups and locations.
  • Utilise these segments for marketing strategies.
  • To plan cross sell and up sell segment-wise.

Technique

  • Statistical Analysis, Clustering Algorithms, Classification Algorithms, Visualization.

Impact

  • Streamlined marketing efforts: targeting specific customer segments, tailored messaging and promotions
  • Increased efficiency : Automating customer segmentation
  • Improved decision-making: gaining insights into customer behaviour and preferences

Personalized Shopping: The E-commerce Edge

Unlock hidden customer groups, personalize offers, and boost sales with smarter segmentation.

Goal

  • To predict the customer’s lifetime value using RFM and k-means clustering.
  • To predict the review score for the next order or purchase.
  • To provide more accurate and relevant product recommendations to customers.
  • To find best valued customers segment.

Technique

  • Statistical Analysis, K-means Clustering Algorithm, Sentiment Analysis, Visualization.

Impact

  • Improved targeted marketing.
  • Personalised service, sales and marketing as per the needs of specific groups.
  • Informed decision-making and optimize offerings.
  • Enhanced customer experience.
 

Do even more with Rubiscape

AI-driven organisations around the world use Rubiscape to solve their most pressing business problems.



ecom

Drag, Drop, Discover:
Insights Made Simple.

Dive deep into your data, create stunning visuals, and gain actionable insights with ease.

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ecom

Build, Deploy, Manage:
Streamline AI Workflow.

Build robust, Scalable ML/DL models with ease , automated workflows & data empowerment.

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ecom

Wrangle, Blend, Analyze:
Data Orchestration Refined.

Develop data fabric and flow designs with low-code, pro-code and self service platform.

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ecom

Manage, Evaluate, Automate:
Edge Analytics Seamless.

Handle data or device management with integrated ML models and M To M application.

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