AI Based Demand Forecasting

AI-Based Demand Forecasting

Demand Forecasting refers to the process of predicting future demand for the firm’s product. In other words, demand forecasting consists of a series of steps that involves the anticipation of demand for a product in the future under both controllable and uncontrollable factors.

The goal of demand forecasting and demand planning is to predict customer demand as accurately as possible to minimize the loss of business and poor customer experience. Retail demand forecasting models are grouped into two categories: qualitative and quantitative. Quantitative methods rely on data, while qualitative methods rely on industry expert insights and feedback.

Critical Industry Challenges

Is your business struggling with revenue growth?

The inability to understand and predict consumer needs leads to manifold losses in direct sales and it increases overall inventory and supply chain cost. If only local stores would be equipped with data-driven demand forecasting then they would have immediately multiplied their revenues by many folds while never disappointing their customers by returning them empty-handed due to their frequent out of stock alerts.

Does your Inventory run out of stock?

The industrial survey indicates that over 20% of Amazon’s retail revenue comes from consumers that first tried to buy their product at the local stores and since they were out of stock, they had to order from Amazon. Running out of stock is a pinching problem for any retailer because for every out of stock alert they not only lose the current business but also risk their customers for the future.

Do you end up with unhappy and unsatisfied customers?

Customers spend so much time and effort to look for their preferred product or service but when they find that it's not available in your inventory, it leaves a bad taste for any customer while pushing them immediately to the competitor's site. Adding to the pain is when in the absence of sufficient inventory, retailers end up increasing the price of the product which typically is perceived by clients as if they are being cheated. In most cases, businesses end up losing such customers against the competitors.

Are you always struggling to forecast customer demands & preferences?

More than 30% of the top global retailers have reported poor forecasting accuracy. With a growing customer base along with their mammoth amount of product and product-related data transactions, demand forecasting grows more and more complex and inaccurate.

Benefits with AI-Based Demand Forecasting Engine

01.

Accurate Demand Prediction to Increase Revenues

Synctactic.AI engines specialize in equipping the business with Accurate Demand Prediction Models, these advance forecasting models provide discrete and variable outputs in terms of various values that need to be forecasted creating a reliable system which constantly supports the supply chain management & sales team to keep up with the inventory and demand. This ensures that business can meet every customer's demand which means minimal loss of business and hence a direct increase in revenue.

02.

Enhanced Actionable Insights

Synctactic.AI, working in Artificial Intelligence has expertise in bringing the time tested Machine learning-based tools that enable an organization's ability to enhance its Quantitative and Qualitative forecasting models.

03.

Real-Time Data Analytics

Synctactic.AI Quantitative and Qualitative forecasting models are used to automate and enhance the retailers' ability to forecast future data as a function of past data and on-going transactional data.

04.

Reduced time of Implementation by leveraging Transactional & Stored Data

Synctactic.AI engine is specialized in pruning through existing millions of GBs of data to learn the direct and indirect business drivers, seasonal & daily events, data patterns, etc.

How Synctactic AI supports Demand Forecasting?

SyntacticAI thrives in enforcing accurate demand forecasting by taking a data-centric and model-driven approach such as qualitative forecasting, Time series analysis, Causal model using their existing patent-pending data automation tools like Sync discover, Sync learn, Sync data, Sync analyze and bring the true power of AI in client’s systems using their internal and external data. SyntacticAI is a leader in providing a trusted AI-based demand forecasting implementation.

Internal & External Business Data-driven models

Syntactic.AI ensures Internal data including historical sales numbers, advertising expenditures vs performance, online/offline traffic, time spent by customers, etc is considered during the implementation of reliable demand forecasting engine. The various external data which SyntacticAI data scientist team considers for their client’s AI engine is based on business trends, industry and consumer trends, seasonal variations and changes, competitors data, etc.

Machine Learning based Self Improving Models

Synctactic.AI continuous machine learning models are designed to constantly align themselves to achieve predetermined business goals & KPI.

Profit & Revenue focussed Demand Predictions

Synctactic.AI goal-seeking models algorithmically vary the future values of the “inputs” to determine the values that achieve a certain goal (profit, revenue, or cost goal) based on the forecasts.

Seasonal Demand Forecasting

Warning Alerts

The AI engine further improves seasonal demand forecasting which leads to greater operational efficiency, reduced expenses and increased profits. Self-Improving AI models increase the reliability of AI-based demand forecasting engines which can persistently feed on the new data and processes which results in quarter to quarter revenue growth for Synctactic.AI clients and an increase in client’s market capitalization.

To immediately leverage this power of AI on your existing data and system please connect with one of the data scientist members of the Syntactic.AI team.

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