Forecasting & Predictive Analytics

With machine learning to the rescue, Forecasting the user behavior and needs has never been easier.

Integrate Forecasting into your web and mobile applications.

Forecasting & Predictive Analytics

Benefits of using forecasting and predictive analytics

Over 50% accuracy in forecasting

Over 50% accuracy in forecasting

Time series data and other variable product features and locations of stores can affect one another. With our machine learning algorithms and advanced analytic architectures, we are about to achieve that 50% faster, which can help us better understand how such complex relationships can affect user behavior. The models we integrate are custom built for your data, which means the predictions are custom-built for your business.

Huge reduction in forecasting time

Huge reduction in forecasting time

Forecasting often takes months of engineering and data analytics. With the feature to quickly import time-series data and go ahead directly from there. Our deeply integrated machine learning model quickly automatically loads data, inspects it, and figures out the key attributes needed for forecasting. One done, it trains and optimizes the custom model, which you can host into a highly available environment that can be used to build better models.

Virtually any time-series forecasting possible

Virtually any time-series forecasting possible

Different types of time-series forecasting models are required based on your business requirement, which can range from cash-flow to product demand to resource planning. With our integrated machine learning models, you can forecast for almost every industry, including finance, logistics, retail and more. You can work with any historical data and use a large library of built-in algorithms to best fit your mobile and web applications.

Highly secure business data

Highly secure business data

We have highly invested in security and encryption to keep your data safe and secure. Any content we process for you is encrypted with keys personalized to you, so that you and only you will have access to the forecast data, and not even we are allowed to check the results. We have partnered with Amazon Web Services to help you with identity and access management permissions policy, ensuring the confidentiality of your information.

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How Forecasting & Predictive Analytics Works

Use Cases for Personalized Recommendations

  • Product Demand and Planning

    Once you provide information like historical sales, pricing, promotions, location and catalog data from your retail management system (like Orderhive and Trackhive), we integrate advanced analytics and combine it with website traffic, weather, shipping and more to create a model that accurately forecasts customer demand for products at an individual level. You will also be able to export your forecasts at batch in CSV format and import them into your retail management system which can help you plan your product demand planning.
  • Financial Planning and Budgeting

    Accuracy in forecasting the sales and revenue numbers are essential for every business. With our advanced integrated machine learning models, you can accurately predict financial metrics like expenses, cash-flow, revenue, and various other monetary units across multiple periods of time. After producing a model, we can provide enough information to be able to accurately forecast data and production.
  • Resource Planning and Estimation

    Planning can help you maintain the right level of resources. Staffing, inventory, raw materials, and many other such important resources matrices can find help with the help of advanced machine learning algorithms that can be used to forecast using historical data. For example, a company running a broadcasting business might want to optimize the advertisement inventory at a regional level. Historical data can be imported across programs and categories like geographic regions, content metadata, regional demographics and more.

Features of ML-based Forecasting integration

  • Works with any type of historically accumulated data

    You can use any type of historical data from your mobile or web applications to create forecasts for your business. Enterprises use their retail scenario, and use our machine learning integrations to process their time series data which combines with time-series data to determine complex relationships.
  • Machine learning is automated

    Machine learning is a completely automated process. You simply have to bring in your data, which we keep safe and secure, and use our advanced algorithms to analyze. Once your data is loaded, you can inspect it, select the right algorithms, and train model, provide accuracy and generate forecasts.
  • Based on the same technology as

    We use personalization models that have been learning for over 20 years and used by large organizations like Amazon and Microsoft to understand user behavior and recommend the right type of products. We use algorithms that are best suited for your users.
  • Easy evaluation of accuracy in forecasting

    With machine learning integrated into your mobile and web applications, you can have performance checks for models and compare them to previous models, that have looked at a different set of variables, which use a different period of time for the historical data.
  • Visualization of forecasts

    Every forecast from our machine learning model is visualized as easy-to-understand graphs. Once our forecasts are generated, we navigate to the relevant forecast by picking it from the available list of things. Visualization deepens your understanding of the data.
  • Can be easily integrated with your existing tools

    You can easily integrate your existing tools to accurately measure and forecast. Supply chain applications like SAP and Oracle can import our learning model services easily, with little or no change into the approach and behavior of machine learning models.