What Is Demand Forecasting?

Running a business is hard. You never really know how it will all turn out, yet you need to be able to answer questions like these:

What amount of inventory do you need to possess in order for all SKUs to be fully stocked?

How often do you project to replenish inventory?

How will those projections change over time?

What do you anticipate your situation to be like in one year?

Perhaps you only have a slight grasp of the demand for your products. That’s fine! It is very difficult to accurately predict what will happen in the future.

Once you’ve been practicing for a little while and are beginning to get the idea of it, your goals will switch again.

No matter if your company is seeing slow sales increases or growing rapidly, we’ll provide you with guidance on how to better estimate demand.

Using previous data to determine what amount of a product or service customers will want in the future is called demand forecasting. This is achieved through the application of predictive analytics. Demand prediction aids the company in making wiser supply decisions that estimate the total sales and profits for a future time frame.

Predicting future sales through demand forecasting enables businesses to effectively manage their stockpile. By examining past sales information, demand supervisors can make intelligent business choices about matters varying from inventory control and warehousing requirements to conducting flash sales and satisfying customer anticipations.

Types of Demand Forecasting

Making an estimate of what the future demand for a product or service is based on past sales trends is generally referred to as demand forecasting. You can categorize forecasting models, though, by different factors. They include time scale, scope, and more. As such, the following are four common varieties of demand forecasting:

Macro-level.

Macro-level demand planning looks at forecasting from the largest possible perspective. This is a technique for anticipating market requirements which evaluate the environment in which an online store operates. That implies it requires an analysis of the target market and is best suitable for companies with specific objectives.

That could be businesses attempting to release fresh goods or trying to tap into a different demographic. For example, if Skull Candy, the audio company, desired to expand into the clothing industry. They’d need to perform macro-level demand forecasting. That is the way that they would accurately handle their stock organization and management of the supply chain.

Micro-level.

Micro-level ecommerce demand forecasting involves forecasting the demand for products on a very small scale. It is the opposite of macro-level ecommerce demand forecasting, which looks at the overall demand for goods on a larger scale. A company takes a look into its own functioning for prediction and preparation of sales.

An ecommerce business has a number of options to consider. They include:

Past sales performance of product categories and individual lines (by SKU).
Profit margins achieved on different items.
Cost of production and cash flow considerations that may impact inventory planning.

Short-term.

Forecasting demand is always about looking to the future. To what extent will depend on the company’s forecasting. Anticipations of purchasing movements are most commonly restricted to the time span of the following 3 to 12 months when planning for near-term demand. Making an estimate of future demand based on this method usually involves finding out the regular fluctuations throughout the year. That’s how product demand changes by time of year.

The National Baseball Hall of Fame’s online shop might likely experience an increase in business during the baseball season. Would purchases spike more, though, during the World Series? What is the optimum time to begin the regular season? This is the type of inquiry that short-term demand prediction can address.

Long-term.

Long-term ecommerce demand forecasting is the most comprehensive variety. It uses data analysis to recognize patterns of need for the next one to four years. This far-reaching demand planning feeds into broader business strategy.

Analysis of sales figures could show possibilities for utilizing fresh sales strategies. It can indicate that a brand must significantly alter its supply chain. Trends could be an indicator of a significant increase in customer need for a certain item. Therefore, the current providers may not be able to furnish the necessary stock number.

Importance of demand forecasting for ecommerce

Without demand, there is no business. Without having complete knowledge of consumer demand, companies are unable to make the necessary choices about their marketing plan, output, staff, and so forth.

It is impossible to predict an exact demand forecast, however, there are techniques to enhance lead times during production, raise operational effectiveness, cut costs, launch novel products and provide clients an improved experience.

Preparing your budget

Prediction of demand enables one to lower dangers and make fine monetary choices that influence net margins, cash flow, allotment of resources, chances for growth, stocking numbering, running costs, recruitment, and total consumption. Strategy and operational plans are created based on predicted demand.

Demand planning and scheduling production

Demand prediction enables you to give the items your purchasers need when they need them. Before launching a product or service, it is necessary to ensure that your order fulfillment is in alignment with your marketing goals in order to accurately forecast the demand.

Having your product sold out for extended periods can quickly damage both your progress and your reputation. Accurate prediction of demand and management of inventory can help guarantee that a business does not purchase too little or too much stock.

Storing inventory

Demand predicting can assist in cutting expenses in relation to both stock buying and storing, as having excessive amounts of inventory will cost more to store. Proper stock control means having an adequate supply of the item, but not overstocking.

Keeping an accurate record of stock numbers will make it simple to get new items and estimate future inventory levels.

We are able to keep track of the number of products in stock at each of our fulfillment centers using ShipBob’s real-time inventory management feature. This assists us with not only maintaining and keeping our stock levels even but also with taxation procedures during the yearly tax season.

Matt Dryfhout, Founder & CEO of BAKblade

Developing a pricing strategy

Demand prediction isn’t simply about refining a business’s manufacturing plan to fulfill demand, but also it should guide the pricing of items based on the demand. By having an understanding of the industry and potential chances to capitalize, businesses can foster expansion, devise cost-effective prices, utilize the correct e-commerce advertising techniques, and set aside funds for maturation.

If you decide to reduce the cost of something or give a discount on an item, there may be a temporary boost in demand for that product. It is possible that you would not have seen an increase in business had the sale not taken place.

If there is not an abundance of an in-demand item, you could apply the scarcity technique to raise its cost in order to make it a select deal. You must pay close attention to any new competitors, as it may cause an increase in supply.

Factors influencing the customer demand life cycle

Demand prediction is when the management of the supply chain combines with sales and marketing. Both sides must be in sync to succeed. Learn how different forces affect demand forecasting.

Seasonality

Changes in the number of orders over a certain amount of time are known as seasonality. A brand that experiences a big difference in customer demand depending on the time of year may center itself around a certain time period, event, or season, with large interest observed right before it (think shoppers wanting grilling equipment prior to the summer or 4th of July).

A company may need to decrease its stock during the off-season and relieve its production and staff when it is in the peak season. A lot of businesses that operate in a cyclical fashion choose to employ a third-party logistics supplier to manage their retail fulfillment, including storing inventory, selecting items, packing boxes, and delivering orders.

Competition

Demand is affected by competing companies as there are additional choices for customers to select from and more firms trying to capture their notice.

When two or more solutions enter the market and customers have to select from them, competition will cause the demand to shift. You may not expect it, so a nimble demand-predicting system can help you answer swiftly.

Types of goods

The level of demand forecasting necessary to anticipate customer needs will vary significantly depending on the product or service being offered; ranging from quickly decomposing items to regularly scheduled subscription boxes.

It is significant to be aware of the overall money spent by customers throughout their relationship with you (what they buy from you across different markets for a long time period), the average spending per transaction (how much money they commit each time), and the products that are regularly ordered together to refine the prediction of demand.

By using this set of information, it is feasible to determine how to unify or organize goods, acquire more repeated profits, and ascertain how a singular SKU influence or causes a need for another (such as razor and razor blade refill sales).

Geography

The area where your clients live and your production and mailing location can have a major effect on your predicting of stock and the rate at which you can finish customer orders.

The placement of your retail supplier network can be a very calculated decision. It is advantageous to utilize fulfillment centers close to your clients so that it is possible to rapidly satisfy consumer expectations in a cost-efficient manner. This means it will be sent from the distribution center closest to them.

This allows you to keep an eye on where your clients live and to keep particular items in the areas where they are most requested, so you don’t have to send them to remote places.

How Does Demand Forecasting Work?

Anticipating changes in customer demand and sales potential is part of demand forecasting. By having knowledge of past sales, a company is able to gain a competitive edge over its competitors. They can, for example, increase the amount of a product they have on hand to prevent running out.

We will go over the advantages of ecommerce forecasting for controlling inventory further on. For now, let’s consider precisely how it works. In summary, it is possible to predict future outcomes through either subjective interpretation or numerical analysis.

This type of approach examines the wider economic climate in order to make predictions. You may consider any of the following:

Market research – target audience surveys, etc.
Industry expert’s opinions
National or global economic circumstances – recession, etc.

Quantitative forecasting leans more on hard data. This kind of planning follows a pattern and makes predictions based on past data. Examining sales statistics or website analytics and noting correlations is usually part of the process. Can you infer that sales will significantly increase based on the sales of one specific item? Do you need to alter your stock control system due to this?

Steps for Demand Forecasting in Ecommerce

The evidence presented ought to have reinforced the significance of anticipating consumer demand. It is just as paramount for ecommerce businesses to have a marketing plan as it is for companies in the SaaS sector. How, though, can you start forecasting demand more accurately? Below are a handful of easy steps for you to begin with.

Identify goals.

The initial step to achieving remarkable demand forecasting is to make a plan. This is the same for numerous operational activities. Before undertaking any data gathering or analysis, you must be aware of the goals you wish to accomplish. Specify time limits for your prediction and come up with the queries you wish to answer. Examples may include:

What volume of particular products will we sell?
Will demand certain lines fluctuate over time?
What events or external factors could influence the demand?
Might changing consumer expectations affect sales?
If demand shifts significantly, will our commercial infrastructure cope?

Once you have established your objectives, make sure everyone involved is in agreement. Make sure that your sales representatives, social media advertisers, and decision-makers are in complete accord and that all scenarios have been taken into consideration. Then, you can start forecasting demand in earnest.

Collect and record data.

It has been established that augmenting information will bring forth more precise predictions. No matter which approaches you choose to predict consumer demand, it is necessary to acquire a great deal of data. There are numerous methods to obtain data and facts.

Bear in mind that both internal and external forces affect the requirement for the product. You will need to collect past sales data and information from other sources as well.

It should be relatively simple to acquire the latter from your customer relationship management or order fulfillment system. For the latter option, you may choose to do your own market analysis or look at current reports and questionnaires.

Measure data.

Once you have your data, it is important to analyze it to make determinations. Examining your outcomes to spot patterns and tendencies. This task can be achieved without automated means, however, this is only efficient for smaller companies.

When you have an abundance of different kinds of data, it is prudent to make use of an AI-powered data analytics platform. By using machine learning methods, these solutions are able to rapidly obtain knowledge from your data. Remember not to rely wholly on tech, however. Put your experience to work and utilize your cleverness to make sense of the knowledge you acquire.

Make adjustments.

You’ve collected your data and found illuminating patterns. So, what’s next? That is the stage of the process that gives your business the advantage. This is the place where you modify your business activities in accordance with your predictions.

You could predict that there will be a decrease in customer demand for a certain item. You could then alter future orders for those products so that there are fewer of them in inventory. You might find that a product has a period of high activity during a particular season. You could choose to only supply the item during certain seasons. The stock does not fill your storage facility when it is not required.

Conclusion

Determining the future of ecommerce is essentially predicting consumer demand. Accurately obtaining the necessary information will allow you to modify your procedures to fulfill customer requirements precisely. It’s the kind of service that modern consumers demand.