Account for recent sales trends

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The old adage “history repeats itself” is practically a law of science when it comes to demand forecasting. One of the biggest drivers behind accurate product forecasting is a deep understanding of its past sales, and more importantly, what factors influence change.

Analyzing the impact of internal and external events can guide you in predicting future performance. It’s important to not only understand patterns, but also anomalies. For instance, are you seeing an increase in demand due to a change in your marketing efforts, a launch of a new product, or macroeconomic drivers? Understanding the impact of these events and applying the learnings can help mitigate volatility.

Predict new product and category performance

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Adding a new product or category to your business can be challenging to forecast when you don’t have any prior history. There are a few things you can take into account to help form an accurate sales prediction. First consider if you’ve ever launched something similar. New adds typically follow a similar trajectory unless there are major changes in marketing and promoting the product. While the volume may differ due to greater/less favorability among your customers, the sell-through timeline could be similar. To gauge favorability among your customers, consider similar swings across the rest of your business.

Perhaps you haven’t launched a comparative item or category before. In this case, you should look at your customer base and decide how much you expect your current customers to cross-shop into this new product/category and how many you think will be introduced to the brand because of it. Try to find external market data from other retailers with a similar product offering. The key to finessing this forecast is to be able to react quickly on actual selling data and limit your variables to get the most accurate demand.

Consider
the Season

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There’s a reason why some brands target different hemispheres throughout the year. Seasonality and weather trends play a crucial role in most product’s performance. Whether it’s selling pumpkin-flavored everything in the fall or swimwear in the summer, it’s evident when seasonality is playing a role in your sales. Understanding these trends across your product assortment can set you up for success in planning future shifts.

Seasonality also plays a crucial role in product performance when it comes to trends related to specific times of the year. A spike in chocolate and flower sales in February or an overall increase in sales post Thanksgiving are all examples of seasonality at play. To account for these trends appropriately, look back on how your business performed in the past and how others in a similar space perform. Ask yourself if you’re keeping up with the trends, and if not, consider why.

Prepare for new product and
category launches

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The launch of a new product isn't like a normal restock—demand can spike for a limited time after a product first becomes available. Be better prepared for your next product launch by applying the learnings from the last one in a similar category.

Account for
historical events

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Perhaps you had a really successful product launch that cleared out your inventory. Or you ran promotions that may or may not have been anniversaried. In any case, these events and lack of inventory result in sales that may not accurately depict what demand would be later on. You’ll want to account for these anomalies when making future projections. Be sure to also consider internal insights that cause a fluctuation in inventory such as samples being pulled for marketing and PR or backordered quantities that cause an influx of demand once they’re available.

Fuse does it all, on demand

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When it comes to making smarter predictions based on recent sales, category-wide trends, or seasonality, Fuse does it all. Our algorithm does the hard work for you. No more complicated Excel models or locking yourself in a room for hours on end. We'll help you with the analytics and forecasting so that you can focus on growing your business.

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