• Pricing For Profit, Competitor & Price Discovery, Demand Forecasting.

    Enabled By AI & Machine Learning

    Delivered a sales uplift of 14% for an American brand of casual apparel due to better pricing…
  • Pricing For Profit, Competitor & Price Discovery, Demand Forecasting.

    Enabled By AI & Machine Learning

    Caused a sales lift of 4% in the face of 11% degrowth for an online European retailer…
  • Pricing For Profit, Competitor & Price Discovery, Demand Forecasting.

    Enabled By AI & Machine Learning

    Better demand forecasting enables better utilization of capital at a leading Middle East Retailer…
  • Pricing For Profit, Competitor & Price Discovery, Demand Forecasting.

    Enabled By AI & Machine Learning

    Intelligent competitor price monitoring enabled better responsiveness to competition at a Middle East Retailer
  • Pricing For Profit, Competitor & Price Discovery, Demand Forecasting.

    Enabled By AI & Machine Learning

    Discovered lost sales opportunity of 11% on the shirts category of an Indian men’s apparel brand across its network of 100+ stores..

    NextOrbit Platform

    We help you predict and respond to demand peaks and troughs with our advanced forecasting algorithms and predictors
    We alert you to take action before you lose customer demand
    NextOrbit helps you to price up or markdown to maximize profits

    Features

    Intelligent Demand Planning

    Intelligent Demand Forecasting

    Machine learning and human judgement - We help combine best of both worlds. We incorporate the impact of local events, holidays, back-to-school, school closing, local carnival and games, social signals and macro-economic variables

    • Demand Forecasting
    • Store Ordering
    • Purchase Order Recommendations
    • Shelf Space Allocation & Optimisation
    • Continious Monitoring And Improvement
    Intelligent Demand Planning

    Intelligent Pricing

    Better price realization to improve Sales & Margin.

    • Determine price elasticity by product, location and day; hence determine the extent of mark-up or markdown
    • Differential Pricing Strategies
    • Avoid a race to the bottom
    • A/B testing to demonstrate effectiveness of recommendations
    • Continuous monitoring and improvement
    Intelligent Demand Planning

    PriceEye – Competitor Price Discovery & Monitoring

    Uses Machine Learning with atleast a dozen product attributes to identify similar or substitutable items, and retrieves their pricing and in-stock status multiple times in a day.

    • Identify Substitutable / Similar Products With a “Similarity” Score
    • Analyze /slide & dice historical competitor pricing
    • Get Real-time competition pricing insight
    • Competitor price trend alerts
    • Discover new competitors

    Benefits

    Intelligent Demand Planning
    Higher Inventory Turns
    Intelligent Demand Planning
    Higher Profits
    Intelligent Demand Planning
    Working capital optimization
    Intelligent Demand Planning
    Better Full Price sell through
    Intelligent Demand Planning
    Higher On Shelf Availability
    Intelligent Demand Planning
    Higher Basket Sizes
    Intelligent Demand Planning
    Higher Customer Loyalty & Repeat Visits
    Intelligent Demand Planning
    More Effective Planning
    Get Started

    How It Works

    Intelligent Demand Planning
    Request Demo

    The Questions We Help Answer

    Price Optimization

    • How should we price for profit, as opposed to price for sales?
    • Are we pricing right? What’s the price elasticity (ability to pay) by product, by location and day?
    • How can we make changes, at speed? How do we not leave money on the table?
    • Can we conduct “price experiments”, and get a quick read on results?
    • What customer attributes are significant that drive price acceptance?
    • What are frequently occurring baskets and who are the “key basket holders”? How do we minimize discounting?
    • How should we adapt to competitor pricing, while still avoiding a “race to the bottom?”

    Demand Forecasting

    • How do we automate the demand forecasting process, and make it more intelligent and self-learning?

    • How we do reduce manual involvement, and yet get the benefit of human judgement?
    • How do we incorporate factors that impact demand?(e.g. local events, macro-economic factors, holidays and so on)
    • How can we determine latent demand? Answer the question – What COULD we sell?
    • How do I ensure the delicate balance between over-stock and out of stock?
    • How should I distribute stock across my stores and on-line?
    • How should I anticipate demand, and stock up, so as to not lose demand?

    Pricing

    Onboarding Fee
    No Contracts
    Monthly Subscription Fee
    Flexible

    Transparency & Flexibility

    A transparent cost effective monthly subscription model based on the number of stores and categories. No contracts or lockin period for the business.

    Fees based on your number of transactions, number of products, and for brick and mortar Retailer - number of stores.

     

    NextOrbit Mission

    Enable mid-market Retail, CPG Brands and e-commerce enterprises to achieve and sustain credible competitive differentiation and operational effectiveness by the power of the AI, Machine Learning & Cloud

    Our Team

    Kishore Rajgopal
    Kishore Rajgopal
    Founder and CEO
    Srinivasan M.
    Srinivasan M.
    Director
    Data Science Platforms and Solutions
    Vishnukiran KV
    Vishnukiran KV
    Principal Engineer
    Tarooqh Ahmed
    Tarooqh Ahmed
    Data Scientist
    Anand Kumar Chandran
    Anand Kumar Chandran
    Member of Technical Staff
    Sudarson M.
    Sudarson M.
    Principal Data Scientist
    Achilles Saxby
    Achilles Saxby
    Principal Data Scientist
    Manikandan TV
    Manikandan TV
    Lead Data Engineer
    Rajath Rao
    Rajath Rao
    Software Engineer
    Anam Iqba
    Anam Iqbal
    Data Analyst
    Sharadhi N
    Sharadhi N
    Data Engineer
    Udith VB
    Udith VB
    Software Engineer
    Bernard Anderson
    Bernard Anderson
    Principal Consultant

    Our Advisors

    Win Weber
    Win Weber
    Strategic Alliance Partner
    Bill Homa
    Bill Homa
    Advisor – Retail

    Get Started

    Pain Problems to Solve

    Select 3 problems
    Over Stock
    Product Expiration
    Out of Stock
    Innefficiant planning for growth opportunities
    Leaving money on the table Due to Improper Markdown
    Cant Figure out latent Demand
    What more merchandise could sell
    Food Wastage
    Not Responding Speedily to fashion Trends
    Over Exposure to Competitor Pricing

    Benefit Expected

    Select Top one or two
    Better Full Price sell through (Less Discounting)
    Higher OSA (on shelf Availability)
    Higher Inventory Turns
    Lower Store or DC inventory
    Higher Basket Sizes
    Higher Customer Loyality (More Repeat visits)
    More Effective Planning