What is Demand Forecasting? Importance and Benefits of Forecasting Customer Demand
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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:
- How many units of inventory do you need to have on hand to be at full stock for each SKU?
- How often do you project to replenish inventory?
- How will those projections change over time?
- Where do you expect to be a year from now?
Maybe you only have a slight understanding of demand for your products. That’s fine! Forecasting projections is one of the toughest things to get right.
And just when you’ve been doing it for a while and start to get the hang of it, your projections shift again.
Whether your brand is experiencing gradual sales or is in high-growth mode, we’ll walk you through some tips to improve your ability to forecast demand.
What is demand forecasting?
Demand forecasting is the process of using predictive analysis of historical data to estimate and predict customers’ future demand for a product or service. Demand forecasting helps the business make better-informed supply decisions that estimate the total sales and revenue for a future period of time.
Demand forecasting allows businesses to optimise inventory by predicting future sales. By analising historical sales data, demand managers can make informed business decisions about everything from inventory planning and warehousing needs to running flash sales and meeting customer expectations.
Importance of demand forecasting for ecommerce
Without demand, there is no business. And without a thorough understanding of demand, businesses aren’t capable of making the right decisions about marketing spend, production, staffing, and more.
Demand forecast accuracy will never be 100%, but there are steps you can take to improve production lead times, increase operational efficiencies, save money, launch new products, and provide a better customer experience.
Preparing your budget
Demand forecasting helps reduce risks and make efficient financial decisions that impact profit margins, cash flow, allocation of resources, opportunities for expansion, inventory accounting, operating costs, staffing, and overall spend. All strategic and operational plans are formulated around forecasting demand.
Demand planning and scheduling production
Demand forecasting lets you provide the products your customers want when they want them. Forecasting demand requires that order fulfilment is synced up with your marketing prior to launching.
Nothing kills progress (or your reputation) faster than being sold out for weeks on end. Proper demand forecasting and inventory control can help ensure a business doesn’t buy insufficient or excessive inventory.
Demand forecasting can help you spend less money on both inventory purchase orders and warehousing, as the more inventory you carry, the more expensive it is to store. Good inventory management involves having enough product on hand but not too much.
“With ShipBob, we have access to live inventory management, knowing exactly how many units we have in each fulfilment centre. This not only helps with our overall process in managing and making sure our inventory levels are balanced but also for tax purposes at the end of the year.”
Matt Dryfhout, Founder & CEO of BAKblade
Developing a pricing strategy
Demand forecasting isn’t just about perfecting a business’s production schedule to supply demand, but it should also help price products based on the demand. By understanding the market and potential opportunities, businesses can grow, formulate competitive pricing, employ the right ecommerce marketing strategies, and invest in their growth.
If you choose to slash prices or put an item on promotion, demand may temporarily increase for that product. Without that sale, you may not have experienced the boost.
If there is a limited supply of a high-demand product, you can use the scarcity principle to increase the price as an exclusive offer. You must keep an eye on new entrants though, as supply may increase.
Examples of demand forecasting methods
A small business may be on a conservative growth plan, while another company may be scaling or diversifying with aggressive growth plans. The demand forecasting examples below walk through a couple of different scenarios.
A grocery store looks at sales trends from last year’s Thanksgiving week to prepare adequate inventory levels for the upcoming season. They look at sales leading into that week last year for seasonal products like turkeys, cranberries, and mashed potatoes.
It was a great holiday sale for them. But eight months ago, a competing grocery store opened four blocks away, so they’re unsure how Thanksgiving demand will be affected and if local customers will buy ingredients from their competitor.
At the same time, a lot of families continue to move into the neighborhood, and they’ve still grown an average of 1% month-over-month since the competing chain opened.
They plan to launch a few more ads than last year through channels that have proven a good ROI for them in the past and also offer some new deals to position themselves as the go-to Thanksgiving destination. Their calculations project a 5% increase in sales from last year.
An up-and-coming direct-to-consumer cosmetics brand is growing quickly. Currently, they are selling 10,000 orders per month. Based on their past sales data, upcoming ad campaigns, and general market conditions in the industry, they plan to be above 30,000 orders per month at this time next year.
Right now, they’re stocking a total of 75,000 units at varying levels across their 5 SKUs. Their order volume fluctuates quite a bit based on their replenishment cycle, and they restock inventory by SKU level at a rate of about every 90 days.
The average units they store will grow quickly while the cadence will remain the same. The last run of their main SKU was 30,000 units. They’re about to ship in another 50,000 units, and their next run will be 75,000 units.
They plan to continue to grow at that pace, so they are looking into whether they should purchase land, lease a warehouse, or outsource fulfilment to keep up with demand.
Types of demand forecasting techniques
There are various ways businesses can forecast demand. All demand forecasting models leverage data and analytics over specific periods of time.
Macro-level demand forecasting looks at general economic conditions, external forces, and other broad things disrupting commerce. These factors keep a business in the know around portfolio expansion opportunities, market research intel, and other shifts in the market.
Demand forecasting at the micro-level can be specific to a particular industry, business, or customer segment (e.g., examining demand for a natural deodorant for millennial customers in Chicago, IL).
Short-term demand forecasting is usually done for a time period of less than 12 months. It looks at demand for under a year of sales to inform the day-to-day (e.g., planning production needs for a Black Friday/Cyber Monday promotion).
Long-term demand forecasting is done for greater than a year. This helps identify and plan for seasonality, annual patterns, production capacity, and expansion over a longer period of time. This drives long-term business strategy (e.g., plans to launch a facility or store internationally and expand into new markets).
Factors influencing the customer demand life cycle
Demand forecasting is where the supply chain management side of business meets sales and marketing. Both sides must be in sync to succeed. Learn how different forces affect demand forecasting.
Seasonality refers to changes in order volume throughout a specific period of time. A highly seasonal brand may serve a specific time period, event, or season, causing varying demand levels throughout the year, including large spikes during their peak season (e.g., shoppers looking for grilling equipment right before the summer or 4th of July).
The chart below shows a ShipBob customer that runs an extremely seasonal business.
Seasonal demand often requires a business to reduce inventory on hand during the quiet months and then ramp up production and their operations workforce during peak season. That’s why many cyclical businesses outsource retail fulfilment to a third-party (3PL) logistics company, who can store inventory, pick items, pack boxes, and ship orders for them.
Competition affects demand as there are more options for your customers to choose from and more companies vying for their attention.
When a competitive force comes into play — whether it’s a direct competitor or a new kind of solution that forces your customer to choose between you or them — demand will be skewed. This can take you by surprise, so an agile demand forecasting model can help you respond quickly.
Types of goods
Demand forecasting will be very different for different products and services — from perishable goods that expire quickly to subscription boxes that come at the same time each month.
It’s important to know the lifetime value of your customers (the total purchases they buy from you across channels over time), your average order value (how much they’re spending each time), and the combinations of products ordered to improve demand forecasting.
Using this data, you can understand how to group or bundle items, drive more recurring revenue, and see how one SKU affects or drives demand for another (e.g., razor and blade cartridge refill sales).
The geography of where your customers reside and where you manufacture and ship orders from can greatly impact inventory forecasting and the speed at which you can fulfil customer orders.
The geographic locations of your retail supply chain can be very strategic. Using fulfilment centres in locations near your customers can help you fulfil customer demand quickly and more affordably, so it ships from the warehouse closest to the customer.
This helps you monitor where your customers reside and store certain products in the regions where they are ordered most, so you don’t have to ship to far away destinations.
“We love that ShipBob actually operates its fulfilment centres — they know their operations and they are very clear about it. ShipBob having multiple locations was also huge for us. Keeping our inventory in Chicago and Los Angeles has brought cost savings since we ship from the locations that are closest to the customer.”
Courtney Lee, founder of Prymal
How to forecast demand in 4 steps [Infographic]
Forecasting demand is an extremely challenging task. You want to be flexible enough to handle sporadic influxes but also take a long-term approach. Here are some tips for your business.
1. Set objectives
Demand forecasting should have a clear purpose. At its core, it predicts what, how much, and when customers will purchase. Choose your time period, the specific product or general category you’re looking at, and whether you’re forecasting demand for everyone or a specific subset of people.
Make sure it satisfies your financial planners, product marketing, logistics, and operations teams in a non-biased way.
You need to understand what your goals are for the right demand capacity planning, which will allow you to use decision-making forecasting processes to understand online consumer behaviour better.
2. Collect and record data
Integrating all of the data from your sales channels can provide a cohesive view of actual product demand and insight into sales forecasts.
In addition to recording the time and date of all orders, the SKU(s) included in each order, and the sales channel it originated from, there are other important forecasting metrics to track, such as:
- SKU Velocity: how frequently a SKU is picked over a certain period of time
- Inventory Turnover Rate: how many times your entire inventory has been sold and then replaced within a given timeframe
- Average Order Value (or AOV): the average dollar amount a customer spends each time they place an order
- Return rate: the frequency with which each SKU is returned
- Stockout rate: how often your business sells out of a particular SKU, depleting available units of the SKU to 0
By tracking these inventory metrics over time, your business can forecast growth and trend projection on a more granular level and look back to see how your forecasts matched up to reality.
In addition to your historical sales data, you may also need to pull in other pieces of data, like market conditions. Make sure any data you use is properly prepared to achieve the most reliable and accurate forecasts possible.
“We have a Shopify store but do not use Shopify to track inventory. In terms of tracking inventory, we use ShipBob for everything — to be able to track each bottle of perfume, what we have left, and what we’ve shipped, while getting a lot more information on each order.
The analytics are super helpful. We download Excel files from the ShipBob dashboard all the time and use them to analyse everything from cancelations, to examining order weights, to checking on whether ShipBob is shipping orders on time.”
Ines Guien, Vice President of Operations at Dossier
3. Measure and analyse data
Whether done manually or using automation and predictive analytics, you’ll need a repeatable data analysis process. This requires comparing what you predicted to actual sales to help you adapt your next forecast.
The chart below shows four different ShipBob customers on the same timeline that have all shipped 60,000 total orders in the same year. Measuring this helps track demand for different products at different times. While they each ship an average of 5,000 orders per month, some months are much lighter than others.
If the brands under-forecasted this volume, they wouldn’t have had enough inventory to ship orders out, and there wouldn’t be enough staff to fulfil them all in a timely manner. If they over-forecasted the volume, they would have spent a lot of money on inventory that is just sitting and taking much longer than anticipated to generate revenue.
As you grow, you may find you need to start tracking additional pieces of information such as obsolete stock, frequency of stockouts, and other order details you may need to improve.
4. Budget accordingly
Once you have a feedback loop, you can set your next forecast (hopefully more accurately) and update your budget to allocate funds where they should go based on growth goals. Demand forecasting helps you reduce inventory carrying costs, plan marketing spend, future headcount, production and inventory needs, and even new products.
How ShipBob makes demand forecasting easier
ShipBob’s proprietary software and merchant-facing dashboard provides ecommerce businesses with real-time visibility into their inventory.
With metrics like daily order status and performance, units on-hand, and days of inventory left, you can monitor today’s inventory activity before looking ahead.
When you’re ready to forecast demand for the future, you can look back at your inventory history. ShipBob automatically tracks data over time — including average units sold per day, order destinations, and SKU velocity — which you can use to optimise your forecasts for accuracy.
You’ll also have access to information on average storage, fulfilment, and shipping costs, as well as a suggested ideal distribution of inventory across locations to reduce these costs while optimising for speed.
Here are just a few stories from ecommerce brands that have used ShipBob to improve their demand forecasting.
The esports and apparel brand leverages the “drop” model to create spikes in demand. With ShipBob’s intuitive analytics and dashboard, they can manage their inventory levels even on the busiest days — and get orders out the door on time.
“Quadrant operates using a drop model, meaning we offer a select number of units each release and they sell out really fast. We run on the idea of “if you’re quick enough, you can get a piece.” Our last drop sold out in 18 minutes – it was amazing!
The key to this model is ensuring we are able to fulfil a massive spike in demand within a reasonable timeframe. With ShipBob, we are able to trust that orders will get out in a timely manner.
ShipBob has given us increased visibility thanks to the dashboard that allows us to easily manage stock and orders. That wasn’t possible for us before. Our relationship with ShipBob has been a game-changer for Quadrant, and it’s made my life so much easier. ShipBob is incredibly easy to use – that’s my favourite part about it.”
Will Kerr, Apparel Lead at Quadrant
Slime by Nichole Jacklyne
Youtuber-turned-business-owner Nichole Jacklyne was blown away by the comprehensive visibility into inventory metrics that ShipBob provided. Having data and insights at her fingertips equips her to grow her business, and continue meeting demand across channels.
“When I found ShipBob, I was so taken back by how thorough everything was. I’m obsessed with the dashboard – everything I need to know is there. If I want to know shipping analytics or shipping prices, it’s all right there and so transparent.
I love ShipBob’s analytics tool. I like being able to look at the last seven days of shipping costs. It’s so nice to see exactly what the average shipping cost is and make sure the number that my Shopify store has customers paying matches what’s in the ShipBob dashboard. Having those kinds of metrics on hand at any point is incredible.
As I grow my business, I’ve realised how important little details like analytics and insights are. If I can’t go in and see that information like I can in ShipBob, it’s going to hinder my ability to grow the business. Ultimately, we left our old small fulfilment centre because everything ShipBob offered blew them out of the water.”
Nichole Jacklyne, Founder of Slime by Nichole Jacklyne
This digital health brand uses ShipBob’s inventory analytics tools to make sure they always have enough inventory to fulfil demand. Using automatic reorder notifications, MDacne can reorder inventory to avoid stockouts if demand forecast is ever off.
“ShipBob’s analytics tool is also really cool. It helps us a lot with planning inventory reorders, seeing when SKUs are going to run out, and we can even set up email notifications so that we’re alerted when a SKU has less than a certain quantity left. There is a lot of value in their technology.”
Oded Harth, CEO & Co-Founder of MDacne
Demand forecasting helps businesses make informed decisions that affect everything from inventory planning to supply chain optimisation. With customer expectations changing faster than ever, businesses need a method to forecast demand accurately.
If you’re looking for an ecommerce fulfilment solution to help you improve demand forecasting, learn more about how ShipBob helps you replenish stock and deliver the experience that customers want. Request a pricing quote of our fulfilment services below.
Demand forecasting FAQs
For ecommerce brands, forecasting projections is one of the toughest things to get right. Here are answers to some common questions about demand forecasting.
What is demand forecasting?
Demand forecasting is the process of predicting future sales by using historical sales data to make informed business decisions about everything from inventory planning to running flash sales.
Why is demand forecasting important?
Without a thorough understanding of demand, businesses aren’t capable of making the right decisions about marketing spend, production, staffing, and more. Through it will never be 100% accurate, forecasting demand can help you improve production lead times, increase operational efficiencies, save money, launch new products, and provide a better customer experience overall.
How is demand forecasting done?
There are various ways businesses can forecast demand. All forecasting models leverage data and analytics over specific periods of time. For instance, you can forecast demand on the macro-level (e.g., economic conditions, external forces, and other broad things disrupting commerce) or micro-level (e.g., particular industry, business, or customer segment). Or, you can determine future demand by short-term or long-term, depending on how you’ll use the data.
How do I build a demand forecasting model?
Forecasting demand is an extremely challenging task. You want to be flexible enough to handle sporadic influxes but also take a long-term approach. The first step is to set clear objectives, and make sure your objective satisfies your financial planners, product marketing, logistics, and operations teams in a non-biased way. You’ll also need a technology and systems in place to collect historical order accurately from your sales channels, so you can easily measure and analyse the data.
Forecasting demand can be a time-consuming task. By partnering with a logistics platform like ShipBob, you can access advanced analytics and distribution metrics to make the process much easier.