What demand forecasting tools mean for modern eCommerce

Have you ever been awake at night wondering if you’ve ordered enough inventory for next month’s campaign? Or worse, you’re staring at a warehouse full of products that simply aren’t moving while your best-sellers continue to fly out of the door.

If you’re processing hundreds of orders a month, you’ve likely lived one of these scenarios before. Because let’s face it: anticipating customer demand can be a minefield. The good news? There’s a smarter way to run your business. Yep, it’s time to ditch the crystal balls and educated guesses, and say hello to demand forecasting. 

The problem of scaling: When gut instinct starts to go wrong 

Let’s be honest, when your business starts to ship hundreds of monthly orders, intuition only gets you so far. What worked when you were a smaller operation can be your Achilles’ heel as you scale, and the consequences of getting demand wrong can really hurt you financially. 

Consider this sobering statistic: McKinsey estimates that global out-of-stock losses hit around $1.2 trillion annually, while overstocking costs businesses about $562 billion. That’s not pocket change – that’s more than the GDP of most countries.  

Even at a singular business level, small forecasting errors can translate into financial impact, increasing the need for more accurate ways to anticipate demand. The moment you’ve all been waiting for... 

What is demand forecasting? (and why your business needed it yesterday) 

Demand forecasting is the process of predicting future customer demand for your products using historical data, market trends and advanced analytics. For eCommerce businesses, it’s essentially the crystal ball we referenced earlier – just without the mysticism. 

eCommerce demand forecasting goes far beyond simple sales predictions; it’s about understanding the complex web of factors that influence your customers' purchasing behaviours. Not only this, but it considers seasonal patterns, promotional impacts and external market forces to predict how demand will change over time. 

Modern forecasting systems use behavioural algorithms to analyse your customers’ purchasing data, order information and inventory levels, giving you a much clearer view of how demand is expected to fluctuate. 

The hidden costs of flying blind 

Before we dive a little deeper into the solutions behind demand forecasting, let’s talk about what poor forecasting might be costing your business. 

The classic inventory nightmare

Companies using traditional forecasting methods typically tie up 20-30% more capital in inventory than necessary. And, when you start to process more orders, that’s a big chunk of money sitting in warehouses instead of fuelling your business. 

One major retailer discovered it could save 15% on inventory costs simply by switching to a machine-learning demand forecasting solution. 

The impact of stockouts

Here’s a stat that can make every eCommerce manager wince: up to 43% of shoppers will go to another store to buy the same item if it’s out of stock, translating to a 4% hit in overall sales for a typical retailer. 

When your business continues to scale and ship more orders, that 4% starts to leave a much bigger hole in your bottom line. 

The efficiency drain

Manual forecasting costs you more than money – it eats away at precious time. Your team can spend countless hours crunching numbers and cross-referencing seasonal spreadsheets, and still arrive at an answer that isn’t as accurate as a demand forecasting solution. 

How modern forecasting solutions can seriously transform your business (with an added boost from AI) 

The good thing about demand forecasting tools is that they keep getting better and better. And, thanks to AI, that improvement has been accelerated massively. 

Slashing your inventory costs

Businesses using AI-driven demand forecasting typically see inventory levels drop by 20-30% while maintaining or improving stock availability.  

When you quantify this, a 25% reduction frees up £125,000 in working capital from £500,000 of inventory. That’s money you can reinvest into your growth, rather than it collecting dust in your warehouses. 

Stopping your stockouts

Advanced forecasting can reduce stockouts by 30% in practice. Think about the ripple effect of 30% fewer stockouts: happier customers, higher conversion rates, and improved customer lifetime value. 

Even what may seem a modest 2% improvement in shelf availability can boost sales by up to 1% – and when you’re processing high volumes of orders, this can make a big difference. 

Boosting your revenue

Companies using AI forecasting report revenue increases of 3-7% per year, with another study finding that properly stocked product assortments can lift sales by around 9%. 

Gartner’s analysis suggests that AI planning can yield 5-10% sales increases while cutting inventory costs by 10-20%. 

Why modern eCommerce businesses need tools like demand forecasting more than ever 

Cross-border eCommerce is exploding, and it’s vital that your forecasting solution can keep pace with the times.

Borderless commerce means a Black Friday sale in the US can trigger unexpected demand spikes in the UK, or a viral TikTok trend in Germany can clean out your inventory across Europe. One thing for sure is that many traditional forecasting methods can’t read these interconnected demand patterns.

Advanced forecasting platforms take your international data and seasonal patterns all into account, helping you anticipate these cross-border demand spikes.  

So, how does it all actually work? 

Today’s forecasting tools are more sophisticated than ever. With the amount of customer data available, and how quickly these tools can process it, modern demand forecasting solutions can present trends that could take humans hours to discover. 

The process involves: 

• Data integration: Information is pulled from multiple channels, payment platforms, warehouse management systems, and any other external data sources 

• Pattern recognition: Seasonal trends are identified, along with promotional impacts, channel-specific behaviours and emerging market signals 

• Predictive modelling: Machine learning algorithms are used to predict future demand with high accuracy 

• Real-time adjustment: Predictions are continuously updated based on new data, ensuring forecasts remain accurate despite changes in market conditions 

Modern platforms also offer API access to forecasting data, creating a seamless bridge between existing systems and real-time decision-making capabilities. 

The impact of demand forecasting – for you and your customers 

Accurate demand forecasting does more than protect your bottom line – it directly impacts your customer satisfaction levels. 

Think about it from a customer’s perspective: you’ve found the perfect product, added it to your cart, and you’re ready to purchase... but it’s out of stock. Nothing kills conversion faster than stockouts, and there’s no guarantee that customer will return when you restock your warehouse. 

Not only this, but retail is evolving rapidly. Consumer behaviours flip faster than ever, new channels emerge all the time, and global supply chains become more complex by the day. As all of this change happens, traditional forecasting methods become more and more obsolete. 

Thanks to good old AI, modern forecasting can adapt to these changes quickly, learning from new data patterns as they emerge and adjusting predictions accordingly.  

Getting started: Your next steps

If you decide to implement demand forecasting, it doesn’t need to be overwhelming. The key is starting with a platform that understands eCommerce complexities and can scale with your business. 

Keep an eye out for solutions that offer: 

• Multi-channel integrations 

• Real-time data processing 

• API access for system integration 

• Proven accuracy rates 

• Scalable architecture 

Businesses thriving in eCommerce today aren’t necessarily the ones with the biggest budgets – they’re the ones making the smartest decisions. And smart decisions start with accurate forecasting. 

The bottom line

Demand forecasting has changed from a nice-to-have to an eCommerce necessity for scaling businesses. It can be the difference between thriving and surviving, as businesses using forecasting tools often see lower inventory costs, fewer stockouts, higher revenue, and improved customer satisfaction. 

Backed by good technology, your business can make smarter decisions and significantly improve its cash flow.  

Plus, forecasting tools are continuously improving. Thanks to predictive analytics and AI, these tools are more powerful than ever, and there’s more around the corner in terms of improvements. 

But just how good can these tools actually get? We take a look at the future of demand forecasting in our ‘What’s Next for Demand Forecasting’ eBook, which you can download by clicking below.