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eCommerce Tips & Trends

How to Use Demand Forecasting for eCommerce

Prior planning prevents poor performance.
How to Use Demand Forecasting for eCommerce
Ian Heinig

By Ian Heinig

 

August 23, 2021

Like a sailboat, your eCommerce business is propelled by an outside force: customer demand. Like the wind, demand for your products ebbs and flows throughout the year. With a forecast for demand, though, you can navigate past sales lulls and breeze toward greater sales with speed and confidence.

Demand forecasting is the process of using historical data to predict your customers' future demand for a product or products. The goal is to understand how your customers, capital and inventory interact – and make better business decisions with these insights.

Demand forecasting helps you to answers questions like:

  • What should you sell?
  • What do your customers really want?
  • How much of a certain item should you buy from a supplier?
  • How often do you need to replenish inventory?
  • How much capital do you need for next year?
  • Where will your sales be in a year?

Grab your eCommerce analytics and your thinking cap. Here’s a full guide to demand forecasting for optimal eCommerce growth.

9 Benefits of Demand Forecasting

Demand is the lifeblood of your eCommerce business. It’s the collective expression of your customers’ desire for a product over a given period.

Forecasting is a strategic effort that accounts for many factors in attempts to paint a picture of the future. You rely on data but it’s impossible to be 100% accurate. It’s more of an art than a science.

Forecasting demand allows you to:

  • Prepare your budget: Making smart financial choices takes data awareness. Expect to improve your cash flow, profit margins, operating costs and others when you act on data instead of guesswork.
  • Stay supplied: Running out of stock of popular items during peak period can sink your growth and reputation at once. Demand forecasting is vital to effective inventory control, helping you have neither inadequate nor excessive inventory.
  • Minimize dead stock: Items never sold are known as dead stock and a drag down your bottom line. Figuring out how much of an item to purchase allows you to predict order volumes with greater accuracy for less waste, lower storage costs and higher profits.
  • Ensure customer satisfaction: Customers bounces from sites that can’t deliver the goods. Keeping inventory on hand is vital to your reputation and bottom line, and forecasting helps you ensure items stay stocked and customers stay happy.
  • Identify seasonal trends: Sales fluctuate through the year and a closer inspection can reveal actionable patterns. (T-shirts sell better in summer?) The next level is using this data to keep sales up all year long with data-driven marketing tactics like discounts. figuring out what discounts to offer on which products when to keep sales up all year long.
  • Evaluate best sellers: Delving into your sales data can illuminate why certain products sell better than others. Tweaking order volumes accordingly can help you mitigate loss and optimize sales.
  • Develop a pricing strategy: A sense of demand helps you price items competitively, but also know when to raise or lower prices. For example, discounts on items increase demand temporarily. Raising prices on low-supply but in-demand items allows you to maximize returns.
  • Build resilience: Identifying the ebbs and flows of sales like holiday spikes and the following slowdown helps you to improve lead times for production, mitigate supply issues and set an effective reorder point for when to replenish your stock.
  • Rationalize your cash flow: Matching goods sold to cash flow in a period can reveal the right time to restock, and also identify what investments are most lucrative.

3 Difficulties of Demand Forecasting

If your business is new or unprepared for a data dive, forecasting can be tough. Here are a few common sticking points to watch for:

  • Lack of data: If you lack historical sales data or visibility of your analytics, deriving insights is difficult. Robust inventory management software like  Easyship makes it simple to compile and evaluate data for analysis.
  • Lack of inventory control: Accurate inventory counts are essential to demand planning. If you lack an effective inventory management strategy, you risk making predictions based on discrepancies that can be misleading.
  • Unreliable supply chain: For best accuracy, your forecasts should account for the time it takes for inventory to arrive from vendors, and you should find your optimal reorder point.

Factors That Impact Demand Forecasting

Forecasting demand gets easier when you understand what drives demand. Sure, your customers all have individual preferences for products but larger economic forces are also at work, including:

Seasonality

Seasonality is the fluctuation of order volume during a specific period. For example, it’s no secret that sales spike around the holidays, back to school and Cyber Monday. Nor is it surprisingly that tank tops sell better during warmer months.

The trick is to uncover how consumers relate to your unique products in light of various cyclical conditions – not all of which are driven by temperatures, life events like holidays, or incentives like promotions.

Seasonality may induce you to reduce inventory during slow periods and increase stock during peak seasons.

Geography

Your eCommerce store can ship to customers all over the world. But where your customers live can impact demand. Different nations and cultures have varied needs, wants and expectations which fluctuate. Your least popular item in the US may be your top-seller in Scandinavia. If you’re selling or planning to sell overseas, don’t overlook sales variance by country.

Product Categories

Different product types see different schedules of demand. High-price luxury items see fewer purchases than iPhone cases that are replaced with every new model.

In other words, it can be trickier to forecast demand for some products. And not all products are in equal demand all year long.

Here are a few ways to smooth out demand fluctuations for products:

  • Group high- and low-selling items to sustain revenue
  • Bundle items to drive recurring revenue
  • Group SKUs that sell correlate

Competition

Demand is directly influenced by the competitiveness of your niche. Demand will dwindle if a competitor enters your space, for example. Conversely, you’ll enjoy sustained demand if you’re the only merchant with a certain product.

Demand is susceptible to marketing. If a competitor unleashes an effective marketing campaign, your demand can fall. If you invest in your own campaign, expect demand to rise. Being aware of your competitors' behaviors can help your forecast demand accurately. Tools like social monitoring, sales spend monitoring and others can help you keep tabs on the competition.

How to Forecast Demand

Demand forecasting can be simple or complex. Multinational brands like Coca-Cola use trend forecasting, econometrics and expert analysts to generate a comprehensive forecast for the near, far and far-far term. However, these methodologies are expensive and inaccessible to most small businesses.

For basic demand forecasting, you only need your eCommerce sales data and analytics. Here's how to forecast demand:

1. Set your objectives

What do you want to know? Set out to answer a certain question for a narrow period (month, quarter, year). For example, how will last year’s popular yellow cardigans sell this autumn?

Demand forecasting is most effective when focused on specific answers. Here are some questions you might ask:

  • How quickly are your products selling?
  • Which items are selling fastest? Slowest?
  • Do sales for this SKU impact others?
  • Which SKUs sell best in which areas?
  • How soon will you run out of a certain item?
  • What items are most profitable? Most returned?
  • How do seasons impact your sales?
  • Do shipping options impact your return rates?

You can pick a specific product or product category you want to analyze. Or a certain customer base or subset of customers.

It’s recommended that you forecast for a few individual variables, then combine the results. By narrowing your focus, it’s easier to use historical data accurately.

2. Collect historical data

Gather sales data from all your channels for the product, products or customers in question for the given period. The more data you gather, the more accurate your forecasts.

You can bolster sales data with your own research. Surveying customers is a great way to gather info and flesh out your marketing personas at once.

The analytics in your eCommerce platform CRM or order management software allow you to compile sales data such as:

  • SKUs sold
  • Sales channels
  • Order dates
  • Returns by SKU

Be sure to account for returns by item, as return rates are estimated at 10% of all eCommerce sales. Products with high rates of returns are ripe for dismissal. You can use the shipping and inventory analytics in Easyship to view all returns across all channels data at a glance.

3. Evaluate data

Refer back to your objectives, then examine your data with an eye for patterns. Note any fluctuations in individual SKUs during the year. Do these movements parallel or diverge from your expectations? If so, why? Get granular on certain SKUs, sales channels, and patterns. Use various filters on your analytics to gain a fresh perspective and conduct a thorough analysis.

Demand forecasting is a form of reductive analysis. Meaning, your aim is to draw conclusions from the limited data available to you. Don’t expect total confidence in your predictions, but they are a meaningful data point.

4. Adjust for Success

Now it's time to adjust budgeting and operations to improve your business performance.

Say you found that demand for yellow card is declining. You'll halt ordering until sales pick up. If you’ve set your reorder point correctly, you’ll get notified when stock should be replenished. Or perhaps you notice that sales are seasonal, so you remind yourself to repurchase only at a certain time of year. This way, you have more capital and storage space at your disposal.

This cycle of 'gather, analyze, predict' is done in periods: monthly, quarterly, yearly. The more often you predict and adjust, the more likely you are to be making well-informed decisions.

4 Methods of Demand Forecasting

Demand forecasting models can be wide-angle lenses or microscopes depending on your needs. In other words, your forecasts can be adjusted to suit your needs and timelines. Here are the most common ways to forecast demand.

Macro Forecasting

Zoom out and consider your sales trends in context of the whole economy or your industry. Perhaps those new EU trade regulations are impacting your sales. Or post-pandemic supply chain disruptions forced you to raise unit prices, which, in turn, diminished sales.

Read widely from research and consult with market experts to inform your planning. With an informed sense of the state of eCommerce, you can extrapolate how the larger forces in the market will influence your business and your sales.

Ideally, macro forecasting precedes all large business decisions. For example, before the release of a new product line or an international expansion. Understanding the landscape in terms of competitors, regulations and market conditions helps you predict your position and chart for success.

Micro Forecasting

Micro-forecasting is taking a granular approach to your sales forecasting and planning. You drill down into specific factors that impact your product sales. Often, you’ll make multiple forecasts and compile them into a meaningful analysis.

In micro forecasting, you can look at:

  • Profit margins for unique SKUs
  • Past sales performance of unique SKUs
  • Costs of production for unique SKUs

For product-level forecasting, micro is the way to go.

Short Term Forecasting

What can you expect in the next 3-12 months? You'll predicts sales and plan accordingly for this brief timeline. Often, this forecasting model helps you plan for seasonal changes, or how certain products will perform at different points in the year.

For example: are you likely to sell more red cardigans at Christmas or during back to school? The answer isn’t obvious, and short-term forecasting may have the answer.

Long Term Forecasting

Using your sales data and analytics to plan for the next year, two years, or five. This helps inform your overall business strategy, not just investments in certain products. Consider big-picture factors like your supply chain, sales channels, and partner relationships and how they can be tweaked for greater performance.

To return to the cardigan example. Will that sweater style be in demand in two years? If not, maybe you should switch to a supplier that offers better prices on those up and coming V-necks all the kids are talking about.

With long-term forecasting, you aim to position your business operations and cost centers for success in years to come.

Demand Forecasting for eCommerce

Demand forecasting is a business process that tells you which way this wind is blowing, so you can capitalize on it. The process of ‘gather, analyze, predict’ can be used all year long and multiple forecasts can often yield the best results. Your forecasting can provide both insight and confidence to drive your best business performance.

If you’d like help with your forecasts, our shipping experts are here to help at no charge. Just create your free Easyship account and drop us a line. We’re happy to help you navigate all things eCommerce, shipping and fulfillment.