This article will discuss the various types of demand forecasting and how they can be used to predict business demand.
Different types of demand forecasting
You have many options for demand forecasting. You can use any combination of these strategies, or just one. They all provide valuable insights that will allow you to manage your store more effectively.
Qualitative forecasting uses descriptive data, such as customer testimonials, expert opinions, focus groups and competitive analysis to forecast demand. It is not based on numerical or quantitative sources.
When should you use qualitative forecasting?When possible, it is a good idea for qualitative input. It is most likely that you will use it in order to validate quantitative findings. You can also use it to validate quantitative findings.Started a retail businessThis is the best way to see what market demand might be if you are opening a new location or launching a product.
Action:My boutique would send out surveys through our Instagram page to collect information. We also looked at historical numbers and economic trends before purchasing trips. We would receive insights from our loyal customers about their color preferences, favorite trends, and how they shop. This combination of qualitative insights and numbers allowed us to make better purchasing decisions and better understand our customers.
Trend analysis or the trend projection method uses historical data to identify trends in demand. Trend analysis can help you identify cycles in demand as well as seasonal and time-based trends that increase/ decrease demand. These findings can be used to predict future demand by using historical ebbs or flows.
Trend analysis when to use:If you have data for at least two years, trend analysis forecasting can be very useful. This allows you to see two years of data and can identify areas where there are spikes or demand cycles each year.
Action:Based on seasonal trends analysis, my store knew that there was always an increase in sales and traffic around the holidays. Then, we knew to stockpile cold-weather items, gift options, as well as hot summer clothing.
Trend analysis looks at historical data in order to predict seasonal trends in demand.
(Source: Small Biz Trends)
Life Cycle Model
A type of retail forecasting called life cycle modeling looks at the typical product’s “lifecycle” and predicts demand based upon how often customers repurchase. Each product type’s life cycle is different and their end dates will vary.
Face cream and flowers, for example, both have an expiration date. However, their lifespans are very different. Creams last months while flowers last days. Fast fashion also has a limited life span. Although trendy, inexpensive clothing items don’t technically expire but they will need to be replaced based on seasonal trends.
When to use life-cycle modelingRetailers who sell items that are either out of season, need to be maintained or renewed, or that require replacement, can use life cycle modeling.
Action:Small Engine Masters, for example, knows that most people only need to change their mower blades once a year. This knowledge allows it to better predict how many mower blades will be needed each year.
Mower blades are a great product to run life cycle analysis on because they have a very set life span.
(Source: Small Engine Masters)
Forecasting for the Short-Term
To make demand predictions, short-term forecasting focuses on a very short time period, usually between three and twelve months. This forecasting strategy allows for you to concentrate on seasonal trends and short term fluctuations in order to better plan and understand them.
When should you use short-term prediction?Short-term forecasting is useful for retailers who have seasonal business that are subject to unpredictable fluctuations in demand. Short-term forecasting is also useful during the holiday selling season. This strategy can be used even if you don’t have enough data.
Action:Breeze Ski Rental understands that most of its traffic comes in September to April. Breeze Ski Rental knows that the demand for goods is low between May and August so it doesn’t make sense to use data for forecasting winter season demand. It instead uses short-term data for winter season trends to understand business’s seasonal cycles.
Long-term forecasting considers trends over a time period of one to four year in order to predict demand. Long-term forecasting is not a way to look at details but rather at the whole picture. This allows you to make strategic long-term decisions.
When should you use long-term prediction?For larger businesses, long-term forecasting can be very useful. If you are considering expanding online or opening a new storefront, for example. It’s similar to trend analysis in that it helps identify cycles and patterns which repeat over and over again.
In action:Recalling my boutique experience, over the years we opened another store and expanded our brand. This store offered a different selection of products and was more appealing to an older demographic who had grown tired of my boutique. Based on long-term trends and shopper profiles, we knew about this group and their loyalty to our brand.
Three Steps to Forecast Demand
Now that you have all the necessary demand forecasting strategies, it is time to start to do demand forecasting in your business. We will be discussing the three steps involved in forecasting customer demand. Then we’ll show you how to use your demand forecast to make the most of your forecast and help you make the right business decisions.
1. Choose a Forecasting Strategy
To help you forecast your demand, you need to choose one or more of the forecasting methods we have covered. Before you begin to crunch numbers and gather research, take a moment to reflect on which approach is best for your business goals.
If you are trying to plan for the holiday season, you may consider using both short-term and qualitative forecasting. If you are trying to decide where to open your second shop, however, long-term forecasting might be more appropriate.
Identify the business’s needs and set forecasting goals to meet them.
2. 2. Collect Data
Once you have a forecasting strategy in place, you can start collecting data. Lightspeed has an integrated POS system that makes it easy to keep track of and file data manually.
Lightspeed allows you to pull reports and see how your business is performing in an array of different categories.
Lightspeed integrates your POS, online store, accounting, employee scheduling, and other software into one central location. Lightspeed integrations allow you to easily access historical sales data, pull reports on seasonal trends, and gain many other valuable and accurate insights into the business. Your data will enable you to make better demand forecasting decisions and lead your business to success.
Pay extra attention when collecting data for demand forecasting purposes.
- Average order value
- Total sales
- Time and data of sales
- Employees make sales
- SKUs sold
- Channel sales
- Product category
- Rate of Return
All the information we have discussed above is internal data. However, there are also external factors. To help you predict customer demand, there are four important external factors you should consider:
3. Analyze Results
Once you have all your data, it is time to start to analyze it to identify buying patterns and trends that can help you predict future demand. You will need to analyze your customer and general shopper trends in order to better predict your future demand.
- What is the average amount they spend in one trip?
- Which factors (weather, sales, promotions) drive them to spend?
- Which factors discourage them from shopping, namely competition, seasons, and economy?
- What is the average number of units they buy?
- What are your most typical shopper profiles?
Next, you’ll want to validate other inputs or hypotheses using the numbers. To help you analyze your data, you can use the questions and hypotheses you have formulated during the demand forecasting process.
Let’s say, for example, that you believe you have sold 50% more during the holiday season than you did in November. You would like to back up your hypothesis by looking at the numbers when you analyze your data.
Use Demand Forecast to Enhance Your Business
Forecasting your demand is only useful if it’s used to make smarter business decisions. Forecasting data is important when you plan how to improve customer service, manage your inventory, budget your cash flow, and set purchasing and spending budgets.
Improve Customer Experience
A good demand forecasting system will help you ensure that there are enough products on hand and sufficient staff to offer a great customer experience. Let’s say, for example, you didn’t do demand forecasting so you didn’t know that there was a seasonal increase in traffic during summer months.
This means that you won’t be able to order enough merchandise and staff enough people during peak season. Many of the items shoppers want to buy are out of stock and there is not enough staff to run the registers and help them on the floor. This not only creates a singular bad experience, but for the modern shopper, it might erode their loyalty completely and make them inventory management in retail are vast. You will not only save money on storage and management, but your customers will be happier because you always have what they need in stock. Good inventory management makes it easier to work in your shop, which will result in happier and more productive employees. Also, you won’t need to sell stock to clear it. This will help improve your margins.
Do you keep track of your stock levels?Start by reading our guide if you don’t have an inventory management system.How to organize your inventoryDownload our Inventory Management Workbook. It will be easier to predict future demand once you have a good record of your stock levels.
To maintain profitability, set budgets
Good demand forecasting will also help you to set and stick to a budget. Forecasting your demand will help you predict how much revenue you can expect over the next period. It can also help you forecast your cash flow. It will allow you to determine your revenue and set sales goals to reach your expenses and make a profit.
A good demand forecasting strategy is one that incorporates data and analysis. It can help you achieve your business’s goals and needs. Understanding the different demand forecasting strategies available and how to use them effectively can help you reduce costs, increase customer satisfaction and improve inventory management. The guide below will help you get started in demand forecasting.