--- title: Step‑by‑Step Guide to Forecasting Next Season’s Best‑Selling Products for Retail Buyers siteUrl: https://logzly.com/retailinsights author: retailinsights (Retail Buying Insights) date: 2026-06-18T05:00:34.479324 tags: [retailbuying, forecasting, merchandising] url: https://logzly.com/retailinsights/stepbystep-guide-to-forecasting-next-seasons-bestselling-products-for-retail-buyers --- The next season is just a few months away, and every buyer knows the feeling: you’ve got shelves to fill, budgets to stick to, and the constant fear of ending up with a mountain of unsold stock. A solid forecast can turn that fear into confidence, and it’s easier than most think. ## Why Forecasting Matters Right Now Retail is a fast‑moving game. Trends change in weeks, not years, and the cost of a wrong guess shows up fast—in markdowns, in lost shelf space, and in the headache of explaining it to the merch team. A good [forecasting next‑season product trends](/retailinsights/a-stepbystep-guide-to-forecasting-nextseason-product-trends-for-retail-buyers) gives you a roadmap, helps you negotiate better with suppliers, and lets you plan promotions with a clear idea of what will actually sell. ## Step 1: Pull the Right Historical Data ### What to Look For Start with the last two to three years of sales numbers for each category you carry. Focus on: * Units sold per week * Sell‑through rate (how fast items moved off the shelf) * Gross margin per item ### How to Clean It Remove outliers like one‑off promotions or stockouts that forced customers to buy elsewhere. If a product was heavily discounted for a holiday, flag it and treat its numbers separately. ## Step 2: Spot the Seasonal Patterns ### Look for Peaks and Dips Plot the weekly sales for each category. You’ll see clear peaks (back‑to‑school, holiday) and troughs (post‑holiday). Mark those on a simple line chart – you don’t need fancy software, a spreadsheet will do. ### Adjust for Calendar Shifts If a holiday moved a week earlier this year, shift the data accordingly. This keeps the pattern aligned with the actual shopping days. ## Step 3: Add External Signals ### Trend Reports Subscribe to a couple of reliable trend newsletters (like WGSN or Trendwatch). They give you a heads‑up on colors, materials, and product types that are gaining buzz. ### Social Listening A quick scan of Instagram hashtags, TikTok challenges, and Google Trends can reveal what shoppers are talking about right now. Note any spikes that line up with your categories. ### Economic Indicators Keep an eye on consumer confidence indexes and disposable‑income trends. When confidence is high, buyers are more willing to try new, higher‑margin items. ## Step 4: Build a Simple Forecast Model ### Choose a Method For most buyers, a moving‑average model works fine. Take the average sales of the same week over the past three years, then adjust it with the external signals you gathered. ### Add a “Growth Factor” If trend reports show a 10% rise in demand for sustainable fabrics, apply a 10% bump to the relevant product lines. Be realistic – don’t double‑digit everything unless the data truly supports it. ### Test the Model Run the model against the most recent season (the one you just finished). Compare the forecast to actual sales. If you’re off by more than 10%, tweak the growth factor or the weight you give to social signals. ## Step 5: Translate Forecasts into Buying Plans ### Prioritize the Top 20% Identify the 20% of SKUs that will likely drive 80% of sales. Allocate the bulk of your budget to these items. This is the classic Pareto principle at work. ### Build “Safety Nets” For new or risky items, order a small “test” quantity first. If they sell well, you can place a larger follow‑up order quickly. This reduces the chance of a big miss. ### Communicate with Suppliers Share your forecast numbers with your key vendors early. Most suppliers appreciate a clear picture and will work with you on lead times, pricing, and packaging. ### Design a Winning Seasonal Assortment When you’re **[building a seasonal assortment](/retailinsights/how-to-build-a-seasonal-assortment-that-boosts-store-sales-by-15)**, align the top‑performing SKUs with emerging trends and ensure the mix appeals to both core shoppers and early adopters. ## Step 6: Review and Refine Weekly ### Track Real‑Time Sales Once the season starts, compare actual sales to your forecast every week. Small deviations are normal; big gaps mean you need to adjust orders or promotions. ### Be Ready to Pivot If a product is selling faster than expected, move inventory from slower‑moving items to keep shelves full. Conversely, if a trend fizzles, pull back on future orders. ### Document Lessons Learned At the end of the season, write a quick note on what worked and what didn’t. Over time, this becomes a valuable playbook that makes each new forecast sharper. ## A Personal Note When I first started as a buyer, I relied on gut feeling and a few spreadsheets. I remember ordering a huge batch of novelty kitchen gadgets one summer because a friend swore they were “the next big thing.” They sat on the floor for months, and I learned the hard way that hype without data is a risky bet. Since then, I’ve stuck to the steps above, and my markdowns have dropped dramatically. It’s not magic – it’s just a disciplined approach to turning numbers into confidence. ## Quick Checklist * Gather clean sales data for the last 2‑3 years * Plot seasonal peaks and adjust for calendar shifts * Add trend reports, social signals, and economic data * Use a moving‑average model with a realistic growth factor * Focus buying on the top‑performing SKUs and keep a safety net for new items * Review weekly, adjust orders, and record lessons Follow these steps, and you’ll walk into the next buying season with a clear plan, not a guess. Forecasting isn’t about predicting the future perfectly; it’s about giving yourself the best possible odds.