Demand Forecasting for Ecommerce: How to Buy the Right Stock at the Right Time

Every ecommerce business has faced the same question.

“How much stock should I order?”

Order too much and you’ll tie up cash in products that sit on the shelf.

Order too little and you’ll miss sales, disappoint customers and potentially lose them to competitors.

Finding the right balance isn’t about guesswork. It’s about understanding customer demand and using that information to make better purchasing decisions.

That’s exactly what demand forecasting helps you do.

While no forecast is ever perfect, having a structured forecasting process allows you to reduce stockouts, improve cash flow and better prepare your warehouse and fulfilment operation for future demand.

In this guide, we’ll explain what demand forecasting is, why it matters and how ecommerce businesses can build a forecasting process that supports long term growth.

Table of contents

• Why demand forecasting matters
• Start with your data, not your software
• Don’t let stockouts distort your decisions
• What information creates a better forecast?
• Choosing the right forecasting method
• Common forecasting mistakes
• How do you know if your forecast is working?
• When should you invest in forecasting software?
• Forecasting supports your entire operation
• Working with your fulfilment partner
• Fulfilpackers: supporting your inventory planning
• Frequently asked questions
• Key takeaways

Why demand forecasting matters

Demand forecasting influences far more than purchasing.

It affects almost every operational decision you make.

A good forecast helps answer questions like:

• When should I reorder inventory?
• How much stock should I buy?
• Will I have enough products for an upcoming promotion?
• How much warehouse space will I need?
• Can my fulfilment operation handle seasonal demand?

Without a forecast, many businesses rely on instinct or react only after inventory begins running low.

This often leads to:

• Expensive last minute freight
• Excess inventory
• Stockouts
• Missed sales
• Poor customer experience

Forecasting helps shift your business from reacting to planning.

And the upside is real. McKinsey reports that applying AI-driven forecasting to supply chain management can reduce forecast errors by 20% to 50% and translate into reductions in lost sales and product unavailability of up to 65%. These are potential outcomes rather than guaranteed results, and they depend heavily on the quality of the data, model and implementation. That is exactly where every forecasting process should start.

Start with your data, not your software

One of the biggest misconceptions about demand forecasting is that it starts with buying forecasting software.

It doesn’t.

It starts with clean, reliable data.

No forecasting tool, spreadsheet or AI model can produce accurate results if the underlying information is incomplete or inconsistent.

Before thinking about technology, make sure you have access to:

• Historical sales
• Current inventory
• Purchase orders
• Supplier lead times
• Promotions
• Product launches
• Seasonal events

One of the highest-value things you can do before choosing a forecasting model is build a clean, unified demand signal: one dataset bringing together sales, inventory positions, purchasing information and promotional history.

That first data-cleaning stage should include:

• Pulling order history, inventory positions and purchase-order timing into one dataset using consistent timestamps
• Identifying stockout periods and estimating lost demand rather than automatically treating zero sales as zero customer demand
• Tagging promotions and major events separately from baseline sales so temporary spikes aren’t interpreted as permanent organic growth
• Establishing a regular forecast review cadence so your process doesn’t quietly become less useful as demand changes

The better your data, the better your forecast.

Don’t let stockouts distort your decisions

Here’s a simple example.

Imagine one of your best selling products normally sells 20 units every day.

On Friday afternoon, you sell out.

Saturday’s sales report shows zero sales.

Did customer demand disappear overnight?

Probably not.

Customers simply couldn’t purchase the product because it wasn’t available.

This is one of the biggest mistakes businesses make when forecasting demand.

If those zero sales are treated as genuine customer demand, future forecasts can underestimate how much stock you’ll actually need. Research published in the International Journal of Forecasting confirms that sales during stockouts underestimate underlying demand and can bias forecasts downwards, which can then contribute to lower inventory levels and poorer service levels.

Before relying on any forecasting model, it’s worth identifying periods where products were unavailable so those gaps don’t distort future purchasing decisions.

What information creates a better forecast?

Forecasting isn’t based on sales history alone.

The more information you can bring together, the easier it becomes to identify genuine buying patterns.

Some of the most valuable inputs include:

Sales history

Historical sales provide the foundation for understanding demand over time.

Inventory history

Knowing when products were unavailable helps explain why sales increased or decreased.

Supplier lead times

Your purchasing decisions should always consider how long suppliers need to manufacture and deliver inventory.

Promotions

Sales events can significantly increase demand for a short period.

Rather than treating these spikes as normal demand, they should be considered separately.

Product information

Categories, suppliers, brands and product attributes often help explain broader purchasing trends across your catalogue.

Choosing the right forecasting method

There isn’t one forecasting method that’s right for every business.

The best approach depends on your product range, sales history and the complexity of your operation.

Spreadsheets

For businesses with a relatively small catalogue and consistent sales, spreadsheets can still provide an effective starting point.

Simple forecasting methods are often enough while demand remains stable.

Statistical forecasting

As businesses grow, many move to forecasting methods that automatically account for trends and seasonality.

These approaches generally produce more consistent results than manual calculations.

Machine learning

Businesses managing large product catalogues and multiple demand drivers may benefit from machine learning.

These models can consider factors such as:

• Pricing
• Promotions
• Marketing campaigns
• Customer behaviour
• Seasonality
• Product attributes

While powerful, they also require higher quality data and regular monitoring.

More technology doesn’t automatically mean a better forecast.

In many cases, a well maintained spreadsheet will outperform a sophisticated AI model built on poor quality data.

Common forecasting mistakes

Even businesses with years of sales data can end up with poor forecasts if the underlying process isn’t reviewed regularly.

Here are some of the most common mistakes.

Relying only on historical sales

Past sales are an important starting point, but they don’t tell the whole story.

Promotions, supplier delays, new competitors and seasonal events can all influence future demand.

Looking beyond historical sales helps create a more realistic forecast.

Treating every product the same

Not every SKU behaves the same way.

Some products sell consistently throughout the year, while others experience seasonal peaks or only sell occasionally.

Grouping products with similar buying patterns allows you to forecast more accurately and make better purchasing decisions.

Ignoring supplier lead times

Knowing you’ll need more stock is only useful if you can receive it in time.

Long manufacturing or shipping lead times should always be factored into your purchasing decisions to reduce the risk of running out of stock.

Forgetting about promotions

Promotions can significantly increase demand over a short period.

If these sales spikes aren’t identified, future forecasts may assume they’re part of normal demand, resulting in unnecessary inventory after the promotion ends.

Not reviewing forecasts

Customer behaviour changes.

New products launch.

Marketing campaigns perform differently.

A forecast should be reviewed regularly rather than treated as a one off exercise.

How do you know if your forecast is working?

A forecast isn’t successful simply because it looks accurate on a dashboard.

The real measure of success is whether it helps your business make better decisions.

Some simple questions to ask include:

• Are we running out of stock less often?
• Are we carrying less excess inventory?
• Has emergency purchasing reduced?
• Are we planning promotions more effectively?
• Is cash flow improving because we’re buying more efficiently?

If the answer to these questions is yes, your forecasting process is creating value.

When should you invest in forecasting software?

Many ecommerce businesses assume they need advanced forecasting software as soon as sales begin growing.

In reality, that’s rarely the first step.

If your product range is relatively small and demand is predictable, a well maintained spreadsheet may be all you need.

As your business grows, however, forecasting becomes more complex.

You may be managing:

• Hundreds of products
• Multiple suppliers
• Seasonal demand
• Promotional activity
• Several sales channels
• Different lead times

At that point, dedicated forecasting software or more advanced planning tools may become worthwhile.

The important thing is to solve today’s challenges rather than buying software for tomorrow’s.

Forecasting supports your entire operation

Demand forecasting isn’t only about deciding what to buy.

It also helps prepare the rest of your business.

A reliable forecast allows you to plan for:

• Supplier purchases
• Incoming inventory
• Warehouse storage
• Staffing requirements
• Packaging supplies
• Carrier capacity
• Seasonal demand

If you know a busy sales period is approaching, your warehouse and fulfilment partner can prepare well before orders begin arriving.

That’s where forecasting becomes more than an inventory exercise. It becomes part of your operational planning.

Working with your fulfilment partner

Forecasting becomes even more valuable when it’s shared with your fulfilment provider.

If your warehouse knows a major promotion, product launch or seasonal sales period is approaching, they can prepare additional storage, labour and operational resources ahead of time.

While your 3PL isn’t responsible for creating your demand forecast, they can use that information to help plan warehouse operations and maintain service levels during periods of increased demand.

Good communication between your business and your fulfilment partner helps ensure everyone is working towards the same outcome.

Fulfilpackers: supporting your inventory planning

At Fulfilpackers, we work with growing ecommerce businesses to help turn inventory planning into efficient warehouse operations.

Our services include:

• Inventory management
• Warehousing
• Receiving
• Pick and pack
• Shipping
• Returns management

Through Mintsoft, our Warehouse Management System, you’ll have real time visibility of inventory, stock movements and order activity, making it easier to plan future purchasing decisions.

If you’re expecting a product launch, seasonal increase or major promotion, our team can work with you to prepare warehouse space, receiving schedules and fulfilment capacity ahead of time.

Our current operational performance includes:

• 98% on time dispatch
• 99.9% order accuracy

Combined with a dedicated Customer Success Manager, you’ll have ongoing support as your business continues to grow.

Frequently asked questions

What is demand forecasting?

Demand forecasting is the process of estimating future customer demand so you can make better purchasing and inventory decisions.

Is demand forecasting only for large businesses?

No.

Even smaller ecommerce businesses can benefit from forecasting by using historical sales data to plan purchasing and reduce stockouts.

How often should I review my forecast?

This depends on your business, but reviewing forecasts regularly helps ensure they continue to reflect changing customer behaviour and upcoming promotions.

Do I need forecasting software?

Not necessarily.

Many businesses begin with spreadsheets before moving to dedicated forecasting tools as their product range and operational complexity increase.

Can a 3PL create my forecast?

A 3PL can help you execute your inventory plan, but forecasting customer demand remains the responsibility of your business.

Sharing your forecasts with your fulfilment partner allows them to better prepare for future demand.

Key takeaways

Demand forecasting isn’t about predicting the future perfectly.

It’s about making better decisions with the information you have today.

As your business grows, improving the way you plan inventory can reduce stockouts, improve cash flow and create a more efficient fulfilment operation.

Recommended

• 3PL Inventory Management Explained: Why It Matters for Your Business
• How to Achieve Efficient Inventory Management: Best Practices and Tips
• Inventory Management & Warehousing
• Signs You Need a 3PL Partner: An Australian Guide