Diminishing Differentiation



Shelves and aisles in retail stores are increasingly being stocked with competing products that marginally vary in price and quality. At the same time, shoppers are more informed than ever before, and have higher expectations of both the products they buy and the companies who manufacture them, including product sustainability and “clean” supply chains. The combination of this diminishing product differentiation and increase in consumer awareness is making it more difficult to predict demand.

Parallel to these new challenges are the ongoing obstacles you continue to address: your existing legacy systems are poorly integrated to one another, with some even sunsetting; your data repository is not unified, preventing true, data-driven decision making; and your planning processes are still highly manual, complex and time-consuming. As chances for missed sales increase, will your business be able to stay competitive?

 
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New SKU Demand Prediction

Harness the power of ML to accurately predict the demand for new SKUs

ML-ENABLED FORESIGHT


New Product Introduction accounts for a significant portion of your business, with successful launches highly dependent on collaboration with demand planning and S&OP functions. Predicting demand and performance of new products can be contentious, with poor forecasts impacting your bottom line. Rubikloud’s ML models use product embedding, through Natural Language Processing, to better categorize new items across a greater depth of attributes and dimensions. This improved categorization results in forecasts that are validated by data and accurately align to consumer demand.

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NEW SKU FORECAST ACCURACY IMPROVEMENT

Clients typically see a 26% improvement in forecast accuracy for new products

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Improve Forecast Accuracy

Leverage the power of AI to generate consumption-based forecasts

AI-POWERED ACCURACY


In an ongoing effort to improve forecasting accuracy, manufacturers are trying to leverage data more effectively - but their traditional, legacy systems cannot extrapolate for missing sources of information. Rubikloud’s AI Engine analyzes data from all your sources, compensating for any missing information, to accurately predict actual consumption. This improved forecast accuracy allows for better control of your inventory and management of product lifecycles, translating into direct financial impact.

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OVERALL FORECAST BIAS IMPROVEMENT

Clients typically see a 36% reduction in forecast bias compared to existing legacy systems

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Strategic Promotion Planning

Build trade promotions that maximize sales and minimize spend

DATA-DRIVEN PROMOTIONS


Trade promotions are critical to reaching your sales targets, but do not always drive the best results. The inefficiency of planning leads to repeated programs without understanding the impact to the overall business. Rubikloud’s AI Engine simulates what-if scenarios in real-time, enabling teams to identify and create the most effective promotions based on business constraints and objectives. These automated, optimized plans improve planning efficiency and consistency, maximize sales, and minimize trade spend.

RETURN ON INVESTMENT


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OVERALL BIAS IMPROVEMENT

Clients typically see a 36% reduction in conscious and unconscious forecast bias

Why Choose Rubikloud?

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UNIFIED DATA

Our expandable solutions ingest data from all your raw sources and quickly converts it into a clean, usable data model. This removes the onus from internal resources and allows for seamless integration back into your legacy systems.

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REAL PRODUCT. REAL RESULTS.

Our proven solutions are deployment ready, no need for costly custom builds or lengthy sessions that never lead to anything tangible. This approach delivers the fastest time to value on the market while optimizing total cost of ownership.

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WORLD LEADING CPG-SPECIFIC ML

Using our best-in-class, industry specific Machine Learning expertise, we tackle the most complex and nuanced business challenges uniquely impacting retailers.

Stop Speculating. Start Predicting.

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