The Indian market offers ample opportunities for all businesses regardless of their size. As per ETGovernment.com's latest article, e-commerce in India will grow 4 times to USD 550 bn by 2035. Thus, there is immense growth potential for business in India. However, the success of a business in such a vibrant market is only successful if it is carefully observed and analyzed and appropriate steps are taken.
The aim of this blog is to educate you regarding quantitative forecasting and how you can take necessary steps to increase your profit potential. It does not matter how big your business is and what you have to offer to your consumers. From traditional footwear to expensive electronic goods, you can rely on this method to make huge profits.
Quantitative forecasting is the process of using numerical data and statistical models to predict future logistics-related needs, such as demand, inventory levels, transportation requirements, and warehouse space based on past trends and measurable factors.
In quantitative forecasting, sellers rely on historical data of their sales. They will look at the number of sales of the product they have to offer. They also look for the number of consumers visiting their webpage and how many were converted into potential sales. These numbers donโt lie and allow the seller to take appropriate steps to either stock those products or avoid them.
Thus, sellers will stock up their inventories based on the past performance of the product. For example, during Diwali, sellers will stock up on namkeen of a specific brand more compared to the rest, as this brand outperformed the rest of the brands.
On the other hand, qualitative forecasting relies on market surveys to take appropriate steps while stocking the inventories. However, there are several surveys that are conducted to understand the current market trend. Based on this analysis, sellers choose their products while stocking up the inventories.
As mentioned above, quantitative forecasting depends upon the historical data rather than market surveys. Since numbers do not lie, several sellers with their past experience depend upon historical data while stocking up inventories.
When you, as a seller, rely on quantitative forecasting, you need to understand that there are several methods involved. Thus, you need to know the following:
Naive Forecasting
In this method, sellers will look for past data, regardless of the seasonal or festive changes.
For example, a seller will stock up his inventory with certain candles, as they were of the same specification sold in earlier months. The seller will continue to sell the same candles regardless if there is any festive season, when consumers would like a change and would like some fancy candles.
Moving Average Forecasting
In this method, sellers will take average sales of a particular product over a specific period and then stock up their inventories.
For example, a seller will take an average of three months for a specific namkeen. Based on the average number of namkeens sold, the seller will stock up his inventory.
Exponential Smoothing
In this method, sellers will take recent sales data, and based on it, they will stock up their inventories.
For example, sellers would stock up their inventories with the latest fashion womenโs garments.
Straight-Line Forecasting
In this method, past sales data is considered while predicting future sales. The inventory is stacked up.
For example, a Mumbai-based womenโs footwear predictor said that a certain design was a hit in the last quarter. Based on this data, the seller increases inventory of the same design by 15%.
Seasonal Index Forecasting
In this method, past sales of a product in festive and wedding seasons are predicted, and stocks are maintained likewise.
For example, sellers are most likely to stock more mango pulp between April and July due to huge demand online.
| Basis of Comparison | Quantitative Forecasting | Qualitative Forecasting |
|---|---|---|
| Definition | Uses historical data and past performance to forecast future demand. | Uses expertsโ opinions and consumer preferences to predict future outcomes. |
| Data Source | Relies on numerical data such as sales figures, trends, and historical records. | Relies on subjective insights, expert judgments, and market surveys. |
| Approach Type | Data-driven and based on measurable facts. | Opinion-based and relies on experience or intuition. |
| Best Suited For | Experienced sellers who already have historical data of product performance. | New sellers or businesses without historical data or launching new products. |
| Accuracy | Generally high accuracy if quality data is available. | Less precise, as results depend on human judgment. |
| Advantages | Helps estimate potential sales objectively; avoids guesswork. | Useful for new markets or products where past data doesnโt exist. |
| Disadvantages | Ineffective for new products or unpredictable markets. | Prone to bias and may vary based on expertsโ opinions. |
| Example Scenario | An experienced seller predicts mango pulp demand from AprilโJuly using past sales data. | A new seller seeks guidance on which womenโs garments to stock for the festive season. |
For experienced sellers, quantitative forecasting helps predict the right inventory while avoiding unnecessary pileup of inventory that is of low demand or hardly moves.
Experienced sellers can allocate the right capital for the right inventory. Thus, they avoid unnecessary spending on those products that are not in demand.
From experience these sellers know what their consumers may desire and stock up with those products that would ensure sales. Thus, these sellers are customer-centric, thus boosting consumer trust. As a result, these consumers are bound to come back to the same e-shop.
When a festive season is on the horizon, they know that consumers will come flocking to their site; thus, these sellers will adequately stock up their inventories.
Godamwale is one of the few third-party logistic companies that is seller- and trader-centric. From experience, Godamwale has identified the challenges faced by sellers and traders in logistics and warehouses across India. With more than 16,000 warehouses spread across 138 cities, the company promises last-mile delivery in the most remote areas of the country.
With the help of in-house software INCIFLO, a seller can track their inventory in the warehouse and also when the products are out on delivery. This software provides a real-time status of the product that has been dispatched from the warehouse.
With the help of digital warehouse solutions and in-house software INCIFLO, you as a seller can track each of your products stacked in the warehouse, allowing you to avoid unnecessary delays and losing out on a potential sale when the inventory is low.
Godamwale also promises last-mile delivery to the remote areas of the country. Thus, you, as a seller, can concentrate on replenishing your inventories and focus on sales rather than handling warehouse and logistic challenges.
Thus, you as a seller do not have to own a warehouse and divert your precious capital to the maintenance and security of it. You do not even have to be bothered by the logistic challenges. You can outsource these challenges to Godamwale, a professional third-party logistic company with scalable, flexible, and on-demand warehousing Pan-India.
How does quantitative forecasting help sellers using Godamwaleโs warehouses?
Quantitative forecasting uses historical sales data to predict future demand. By combining this with Godamwaleโs 3PL warehouse services in Guwahati, sellers can stock the right amount of inventory, avoid overstocking or stock-outs, and ensure products are ready for peak sales periods like festivals.
Can Godamwale support inventory planning for festive seasons?
Yes. Using data from quantitative forecasting, Godamwale helps sellers plan inventory for seasonal and festive demand. For example, popular products during Diwali or wedding seasons can be stocked in advance, and last-mile delivery in Guwahati ensures timely delivery to customers.
How does Godamwale help new sellers with forecasting challenges?
New sellers may not have past sales data for forecasting. Godamwaleโs expertise and e-commerce fulfillment in Guwahati allow them to combine industry insights with warehouse data, helping estimate demand, stock products efficiently, and avoid unnecessary inventory costs.
Does Godamwaleโs software integrate with forecasting methods?
Yes. Godamwaleโs INCIFLO software tracks inventory in real-time and integrates with forecasting methods like moving averages or seasonal index forecasting. Sellers can make informed decisions on stock replenishment and optimize warehouse operations for maximum efficiency.
Why is combining quantitative forecasting with Godamwaleโs services beneficial for e-commerce growth?
By using quantitative forecasting alongside Godamwaleโs 3PL warehouse services, last-mile delivery, and e-commerce fulfillment, sellers can reduce costs, prevent stock-outs, speed up deliveries, and scale efficiently. This combination ensures higher sales, better customer satisfaction, and long-term growth in the Indian e-commerce market.
