Running a Shopify store during peak seasons can feel like a rollercoaster.
On one hand, you’re excited about the potential sales, but on the other, there’s a lot at stake if you don’t have a handle on your inventory.
Without proper forecasting, you could either find yourself drowning in unsold stock that eats up your profits or struggling to fulfill orders because you ran out of bestsellers.
Both scenarios can hurt your revenue and ultimately frustrate your customers.
This article deep dives into Inventory forecasting, how to do it right, its types, best practices, and how Prediko helps you inventory forecasting.
What is Shopify Inventory Forecasting?
Shopify inventory forecasting is the process of estimating early on, how much stock you'll need in the coming weeks or months, to completely avoid both stockouts and excess inventory and still meet future customer demands.
This involves analyzing past sales, market trends, and seasonal patterns so that you can create purchase orders in line with projected demand.
Simply put, Shopify inventory forecasting is like hosting a big feast. You need to prepare just the right amount of food. Too much, and you’re stuck with leftovers; too little, and your guests leave hungry and disappointed.
Similarly, forecasting helps you maintain the perfect stock balance, ensuring you meet customer demand without overstocking or running out.
Why is Stock Forecasting Important for Your Shopify Business?
Inventory forecasting may be a research-intensive route to make an optimal purchase order. However, it is worthwhile and helps your business to:
1. Improve cash flow
Stock forecasting allows Shopify merchants to make precise purchasing decisions and stay away from the cash flow strain of overstocking.
Using forecasts, you can time your purchases to align with expected sales, ensuring that you have stock when needed without holding it for long periods and saving on storage.
You may also use forecast data to allocate the budget more effectively between fast-moving and slow-moving items, preventing cash from being locked in less profitable stock. Moreover, forecasts also help you negotiate better terms with suppliers in terms of unit costs, production times, or payment terms.
2. Reduce warehousing costs
By forecasting customer demand, you maintain optimal inventory levels, preventing extra stock. This means requiring less warehouse space and labor for receiving, storing, and managing inventory. Another added benefit of forecasting inventory is reduced insurance premiums for safeguarding your stock.
3. Maintain accurate inventory levels
Accurate inventory predictions let you reorder products before they run out, ensuring continuous product availability. It also helps you avoid ordering too many unpopular items.
Since forecasting accounts for seasonal fluctuations, you can also stock up for peak periods and reduce inventory during slower times.
When the stock quantities you require are already known, you get the flexibility to set up an auto-replenishment process using a tool like Prediko and keep your store running smoothly.
Prediko’s buying table shows weekly, monthly, or quarterly stockout metrics to know which product or SKU is going out of stock, what you need to buy, when you should buy, and in what quantity. This way, replenishment is just a click away.
4. Inform pricing, marketing, and advertising
The stock forecast data has the potential to inform other decisions of your business as well. Since it gives you a clear picture of overstock, you can offer discounts or cross-sell by bundling products.
The predictions of high-demand items help decide which products to feature in upcoming marketing campaigns. It also lets you allocate the ad budget better, reducing the spend on items expected to be popular and increasing it for potentially low-demand ones.
Historical data and product trends can guide decisions on launching new items. For example, if your clothing brand expects a higher volume of orders from women, you may think about expanding your women’s collection. With Prediko, launching a new product is effortless as it generates a strategic launch plan in a few seconds.
Types of Inventory Forecasting
Let’s look at four common ways to predict the inventory for your Shopify store.
Trend forecasting:
This is a common approach that analyzes historical sales data to identify patterns and trends over time for estimating future demand. For instance, if your clothing store witnessed a constant increase in sales for winter coats over the past few years, trend forecasting helps you prepare for the upcoming winter season by stocking up on similar items.
Graphical forecasting:
This method involves analyzing visual representations of your past sales data using charts and graphs, making it easier to identify trends and patterns. Data visualizations such as line graphs, bar charts, and pie charts offer clear insights into your inventory needs at a glance. For instance, a product-wise bar chart can show which products had the highest sales last quarter, guiding you on which items to stock more heavily.
Qualitative forecasting:
Sometimes you need to rely on expert opinions, market research, and insights to predict future inventory needs. This is known as qualitative forecasting and is ideal when historical data is limited or unavailable. If you’re launching a new product or entering a new line, you may use this method to plan your inventory.
For example, if you're considering adding a new fashion line, market research can reveal which styles or colors are trending, helping you estimate initial inventory levels.
Similarly, after competitor research, if you notice that their eco-friendly water bottles are consistently selling out, you can forecast a similar market demand for your sustainable products.
Quantitative forecasting:
This one uses mathematical models and statistical techniques such as exponential smoothing, and regression analysis to predict future inventory based on numerical data.
Now, each of these forecasting methods has its pros and is often most effective when used in combination. For instance, a merchant who’s launching a new skincare line might use trend forecasting as a baseline and adjust it based on qualitative insights from customer feedback and market research. This makes inventory management more accurate.
Steps to Implement Inventory Forecasting for Your Shopify Store
The following process can be used to manually forecast the inventory for your Shopify store.
Step 1: Determine the forecasting period
First things first, decide on the time frame for which you want to forecast the inventory. This could be monthly, quarterly, or annually, depending on your business’s sales cycle and product turnover rate. For most businesses, a 3 to 6-month forecasting period balances short-term fluctuations with long-term trends.
For instance, if you forecast for just one month in June, it will make you miss the back-to-school rush in August. However, a 3-month forecast helps you prepare by stocking up on popular items like backpacks and notebooks in June. This ensures you’re ready for the seasonal spike and don’t have to place purchase orders now and then.
Step 2: Calculate average sales and monitor trends
Now, analyze the historical sales data and average monthly sales for each SKU over the past year. Identify trends, such as seasonal spikes or growth patterns, and see changes in average sales based on previous peak and off-peak periods.
Use Shopify’s built-in analytics or export your data to Google Sheets. In Google Sheets, use formulas to average your sales and do other calculations. Create charts and graphs to visualize sales, seasonal, and other trends, making it easier to notice fluctuations and set accurate averages for each SKU.
Step 3: Choose an inventory forecasting method
Select a method that suits your product’s sales pattern. This can include:
1. Simple moving average
- It is a method that simply averages sales data over a set period, say 6 months. You can use Google Sheets formulas like AVERAGE(range) to do calculations.
- Best for products with constant sales (almost linear graph)
- For a product like a phone charger that sells steadily throughout the year, calculate the average sales over the past 6-12 months to forecast future demand.
2. Exponential smoothing
- This method involves applying decreasing weights to past data, and more weight to the recent trends.
- Ideal for products with trends or seasonality
- Apply exponential smoothing to recent sales data for seasonal products like summer swimwear. You can do calculations for this as well in Google Sheets, but it can get complicated.
3. Monte Carlo simulation
- This is a statistical technique that uses random sampling and probability distributions to predict a range of possible outcomes and their probabilities.
- Suitable for products with uncertain demand influenced by multiple factors
- For monthly subscription boxes, use Monte Carlo simulations to predict various scenarios based on customer churn rates, seasonal interests, and marketing. You will get a range of possible future demands.
- This is difficult to do with Google Sheets, which is why you need tools like Prediko.
Set your annual revenue goal, and let Prediko’s AI do the heavy lifting. It analyzes past trends and seasonal patterns to generate month-by-month inventory needs and revenue targets. With its 100+ customization filters, you can drill down on your product inventory and plan for demand better.
Step 4: Estimate future sales
Now, once you have chosen your method, it's time to make your projections. Assign the forecasted sales and inventory needed for each month based on your chosen forecasting method. Make adjustments manually to account for factors that could influence these estimates, such as upcoming product launches, marketing campaigns, or shifts in the market.
To automate this manual process, you may consider Shopify apps like Prediko that use AI to forecast sales at SKU, product, category, and company level.
Step 5: Factor in lead time
Your inventory won't arrive right after placing a purchase order. Lead time is the total time it takes from placing an order with a supplier to receiving the inventory. Check your records or contact suppliers to determine lead times for each product. Accommodate the lead time in your sales estimates, know when to place orders for replenishment, and adjust forecasts.
Step 6: Include safety stock
Calculate and add a safety/buffer stock to your predicted inventory to account for unexpected demand spikes or shipment delays. Set safety stock levels based on your sales and lead time. A common formula for calculating safety stock is:
Safety stock = (Maximum daily sales × Maximum lead time) - (Average daily sales × Average lead time)
Retail merchants often keep an extra 10-20% of their average monthly sales as safety stock.
Step 7: Set concrete reorder points
The final step is to establish the inventory levels at which you need to reorder products to avoid stockouts.
These points should be based on your forecasted sales, lead time, and safety stock. You can use Shopify apps to set up automatic reorder alerts and trigger reorders when the stock falls below the target points.
You can manually calculate your reorder point using the formula
Reorder point = Demand during lead time + Safety stock
Common Challenges of Shopify Inventory Forecasting and Ways to Tackle Them
Shopify inventory forecasting isn’t just about dealing with complex calculations, it also involves tackling challenges like
Limited historical data
When starting out or launching new products on Shopify, you may not have sufficient historical data to make accurate inventory forecasts. An inconsistent sales pattern can also make Shopify demand forecasting difficult.
You can use industry benchmarks and market trends to make initial estimates.
As sales data accumulates, gradually refine your forecasts. For inconsistent sales, focus on shorter time forecasts (e.g., weekly or monthly) rather than annual ones. Then, use moving averages to smooth out fluctuations and identify underlying trends.
Prediko’s AI is trained on data from 25 million SKUs helping you create the most accurate forecasts compared to other Shopify apps. Using this tool, you aren’t solely relying on your past sales data but also taking into account seasonal demand in your forecasts.
Manual Google Sheet planning
As your store scales, manually planning inventory on Google Sheets becomes tedious. You have to rely on error-prone manual sales and inventory data entry, there’s a lack of real-time data visibility, and trend tracking across products/stores is difficult.
This is why you must use inventory forecasting tools that pull real-time data directly from your store, leaving no room for manual tasks and mistakes. Prediko’s inventory management tool automatically analyzes historical sales data, identifies seasonality and growth trends, and creates revenue targets for you.
You can also edit and review your plan with 100+ customization filters
Considering return and exchanges
Returns and exchanges can mess up your inventory levels. If not accounted for, these can result in inaccurate forecasts and misjudged reorder points.
Use a Shopify app that automatically adjusts inventory levels based on returns and exchanges. This could involve setting up specific rules or accounting for an average return rate. Keep monitoring returns and exchanges to predict accurate stock levels.
Managing inventory across multiple sales channels
Selling across multiple sales channels, such as online stores, marketplaces, and physical stores, can complicate your forecasts as demand patterns differ with each channel.
You need a tool that centralizes and syncs stock levels across all sales channels in real time.
Prediko is one such app that consolidates all your sales and inventory data in one centralized platform, whether you’re managing multiple stores, warehouses, bundles, or subscriptions.
Forecasting for complex product variations
Products with multiple variations (e.g., sizes, colors) complicate predicting stock levels as each has its own demand patterns.
You must break down forecasting by each product variation to capture specific sales patterns. This is a tedious process manually, so use tools that can automate this.
Prediko’s AI suggests the optimal quantity of each SKU needed for the future by analyzing your historical sales data, taking into account seasonality patterns and growth trends. Based on this, it strategically distributes your revenue targets across the next 12 months.
Best practices for Shopify inventory forecasting
Using inventory forecasting best practices, you can achieve forecasts that are accurate and in sync with actual demand.
Account for seasonality
For a deeper understanding of seasonality, regularly analyze your Shopify sales data over extended periods, ideally 2-3 years if available. Look for recurring patterns in sales volumes that correlate with specific times of the year.
For example, you might notice in your Shopify sales report that sales of sunscreen go up from May to August. This is because people spend more time outdoors during the summer months.
Now, use this data to refine your forecasts by increasing predicted inventory levels for sunscreen during peak seasons, such as summers, and decreasing them for off-seasons like winters. Similarly, adjust forecasts for annual spikes like Black Friday sales, the Thanksgiving period, or product launches based on past seasonal trends.
Prediko’s AI planning feature forecasts revenue (including sales, quantity, and % of total sales) across 12 months by taking into account seasonality and growth trends so that you can skip complex calculations.
Related Read: How to Create an Inventory Plan Ahead of Holiday Season
Segment your inventory
All products don’t behave the same way and expecting the same can lead to forecast mistakes. Segment your inventory based on factors such as sales velocity, product lifecycle, and seasonality.
For products in the decline stage of the product life cycle, such as the previous season's swimwear designs with decreasing sales, need a different forecast strategy.
Reduce order quantities and safety stock levels, and consider using Shopify discount features to create promotions for clearing the remaining stock.
Using the right forecasting methods
Different forecasting methods suit different types of products and situations. For products with consistent sales (minimum fluctuations), simple methods like moving averages are effective.
In contrast, products that are growing (upward graph) or declining (downward graph) are better forecasted using trend-based methods, which can capture and project these changes over time.
The aim here is to match the forecasting method to the behavior of each product or product group. For example, basic t-shirts having year-round sales benefit from a simple moving average, while seasonal holiday decorations require trend-based forecasting to handle demand spikes. Don't be afraid to use multiple methods across your inventory.
Regularly update forecasts
Making PO decisions based on outdated or inaccurate data is risky. Regular updates are important to maintain the accuracy of forecasts. Let’s say, you stocked up heavily on fidget spinners based on their popularity last year. Without updating your forecasts to reflect the decline in interest, you might end up with excess inventory as the trend fades.
During these updates, review your Shopify sales report and reassess your predictions, such as seasonal trends or average sales. Calculate the forecast error which is the difference between the forecasted demand and the actual demand.
For example, if your forecast predicted 1,000 units of a product in July but actual sales were only 800 units, calculate the forecast error as 200 units (1,000 - 800).
Examine these discrepancies to understand why the forecasts were off, whether due to market conditions, changes in customer behavior, or other factors. If there’s a constant forecast error, adjust your predictions accordingly or consider switching methods.
Prediko picks up actual sales figures from your Shopify store so that you can easily compare actual revenue to your forecasted revenue and figure out what’s working and what’s not.
Use Shopify apps to automate forecasting
While manual forecasting can be effective, it can eat up all your time as your product range grows.
Use Shopify apps, like Prediko that can automatically analyze your sales data, account for seasonality and trends, and provide regularly updated forecasts. Consider features like automatic reorder point calculations and purchase order generation that help simplify your Shopify demand forecasting.
Automate your Shopify inventory forecasting with Prediko
Prediko is an inventory management tool that adds an intelligence layer to your Shopify demand forecasting and planning. It centralizes all your sales and inventory data, giving you a unified view of historical sales, and seasonal and growth trends to make projections.
With automated reports and inventory alerts, you can make reordering decisions faster. Prediko's app offers 100+ customization filters to go into the granularity of the inventory plans at the SKU, category, or product level.
Prediko has all the features to let you easily manage everything from raw materials, and purchase orders to product launches in one place. Plus, it extracts sales data in real-time from your Shopify store for you to compare the actual revenue with planned revenue. This helps you identify gaps and keep your forecasts updated.
FAQs
1. What factors affect inventory forecasting accuracy?
Inventory forecasting accuracy is influenced by several factors, including historical sales data, market trends, seasonality, lead times from suppliers, and unexpected changes in demand. External factors like economic conditions and competition can also play a role.
2. How can you evaluate the accuracy of your inventory forecasts?
You can evaluate your inventory forecasts by comparing them to your actual sales. If the numbers are close, your forecasts are on track. Regularly checking for differences between what you expected to sell and what you sold can help make necessary adjustments.
3. How often should you update your inventory forecasts?
Inventory forecasts should be reviewed regularly, typically on a monthly or quarterly basis, depending on the nature of your business. However, it’s important to adjust your forecasts whenever there are major changes in sales patterns, market conditions, or supply chain.
