How to Analyze Last Year's Sales to Order the Right Wholesale Suits This Year

Quick Take: Most wholesale suit buyers make their annual buying decisions based on intuition, supplier recommendations, and a general sense of what sold well last season. This approach generates inconsistent results — some styles sell out in the first month, others sit on the floor until markdown. A structured analysis of last year's sales data takes less than a day and produces a buying plan that is significantly more accurate than intuition alone. For retail buyers who are placing a wholesale suit order, the analysis framework in this guide is the most valuable tool available for reducing markdown exposure and maximizing full-margin sell-through.

Why Is Last Year's Sales Data the Most Reliable Input for This Year's Suit Buying Decision?

Last year's sales data is the most reliable input for this year's buying decision because it reflects the actual purchasing behavior of your specific customer base in your specific market context — not the purchasing behavior of a hypothetical average customer in a hypothetical average market. Industry trend reports, supplier recommendations, and trade show observations are useful inputs, but they describe what is happening across the market as a whole, not what is happening in your store with your customers.

Your customers' purchasing behavior is shaped by factors that are specific to your store — your location, your price points, your merchandising approach, your customer demographics, and your competitive environment. Last year's sales data captures all of these factors simultaneously and produces a picture of what your specific customers actually bought, in what quantities, at what price points, and at what times of year. No external data source can replicate this specificity.

The practical implication for wholesale suit buyers is straightforward: last year's sales data should be the primary input for this year's buying decision, with industry trends and supplier recommendations used as secondary inputs to identify opportunities that the historical data may not capture — new styles, new colors, and new constructions that were not available last year.

Which Sales Metrics Should Wholesale Suit Buyers Analyze?

A structured sales analysis for wholesale suit buying should cover six core metrics: sell-through rate by style, size distribution, color performance, seasonal velocity, markdown rate, and average transaction value. Each metric answers a different question about last year's performance and informs a different dimension of this year's buying decision.

• Sell-through rate by style — The most important metric in the analysis. Sell-through rate measures the percentage of units received that were sold at full price before the end of the selling season. A style with a sell-through rate above 80% was understocked — you left sales on the table by not having enough inventory. A style with a sell-through rate below 50% was overstocked — you either bought too many units or the style did not resonate with your customer base. The sell-through rate by style is the primary input for this year's quantity decisions: increase depth on high sell-through styles, reduce depth or eliminate low sell-through styles.
• Size distribution — The most frequently mismanaged dimension of suit buying. Most buyers allocate inventory evenly across sizes — the same number of units in S, M, L, XL, and XXL — without analyzing whether their specific customer base reflects this even distribution. In most US menswear markets, the size distribution is not even: M and L typically account for 50 to 60% of suit sales, with S and XXL each accounting for 10 to 15%. If your size distribution data shows a different pattern — a higher proportion of XL sales, for example — your buying plan should reflect your actual customer distribution rather than a generic size curve.
• Color performance — The most visible dimension of suit buying and the one where intuition most frequently diverges from data. Most buyers have strong intuitions about which colors sell — "navy always sells," "grey is reliable," "brown is risky" — but these intuitions are often based on memorable individual sales rather than aggregate performance data. Color performance analysis compares sell-through rates across colors and identifies which colors consistently outperform and which consistently underperform in your specific market. The results often surprise buyers who have been making color decisions based on intuition.
• Seasonal velocity — The timing dimension of suit buying. Seasonal velocity analysis identifies when in the year your suit sales peak and when they slow, which informs the timing of your wholesale orders and the depth of inventory you need to carry through each phase of the selling season. Most US menswear markets have two suit selling peaks — spring (March through May, driven by weddings and graduation) and fall (September through November, driven by back-to-work and holiday occasions) — but the relative size of these peaks varies significantly by market and customer demographic.
• Markdown rate by style — The profitability dimension of suit buying. Markdown rate measures the percentage of units that were sold at a reduced price rather than at full retail. A high markdown rate on a specific style indicates that the style was overstocked, mispriced, or did not resonate with your customer base. Markdown rate analysis identifies which styles are generating margin erosion and should be reduced or eliminated from this year's buying plan.
• Average transaction value by style — The revenue dimension of suit buying. Average transaction value analysis identifies which styles generate the highest revenue per transaction — which is not always the same as the highest-priced styles. A mid-priced suit that consistently generates add-on sales of shirts, ties, and pocket squares may generate a higher average transaction value than a premium suit that is purchased alone. This metric informs which styles to prioritize for floor placement and staff recommendation.

How Should Wholesale Suit Buyers Structure Their Sales Analysis?

A structured sales analysis for wholesale suit buying can be completed in four steps using data that is available in any point-of-sale or inventory management system.

• Step 1: Pull last year's suit sales data by style, color, and size — Export a report from your POS or inventory system that shows units received, units sold at full price, units sold at markdown, and units remaining at the end of the selling season for each suit style, color, and size combination. This is the raw data for the analysis. If your system does not track this level of detail, use your purchase orders and end-of-season inventory counts to reconstruct the data manually.
• Step 2: Calculate sell-through rate and markdown rate for each style — Sell-through rate = units sold at full price ÷ units received. Markdown rate = units sold at markdown ÷ units received. Sort the results by sell-through rate from highest to lowest. The top of the list — styles with sell-through rates above 80% — are your core performers that should be restocked with increased depth. The bottom of the list — styles with sell-through rates below 50% — are your underperformers that should be reduced or eliminated.
• Step 3: Analyze size distribution and color performance for your core performers — For each style in your core performer list, calculate the percentage of sales by size and by color. Compare this distribution to your buying plan from last year to identify where you were over- or under-allocated. Use this analysis to adjust your size curve and color depth for this year's order.
• Step 4: Build this year's buying plan using last year's data as the baseline — Start with your core performers from last year and increase depth by 10 to 20% to account for the understocking that their high sell-through rates indicate. Reduce or eliminate your underperformers. Allocate the freed-up budget to new styles that address gaps in your assortment — styles, colors, or constructions that were not available last year but that your customer base is likely to respond to based on the demographic and occasion data in your sales history.

What Patterns Should Wholesale Suit Buyers Look for in Their Sales Data?

Beyond the core metrics, a structured sales analysis should look for four specific patterns that frequently appear in suit sales data and have direct implications for the buying plan.

• The size cliff — A pattern in which sell-through rates drop sharply at the extremes of the size range — typically S and XXL — while M and L sell out consistently. The size cliff indicates that your buying plan is allocating too many units to extreme sizes relative to your customer base's actual size distribution. The fix is to reduce depth at the extremes and increase depth in M and L, which will improve overall sell-through rates and reduce markdown exposure at the end of the season.
• The color cliff — A pattern in which one or two colors account for a disproportionate share of full-price sales while the remaining colors generate high markdown rates. The color cliff indicates that your buying plan is allocating too many units to colors that your customer base does not respond to. The fix is to concentrate depth in your top two or three colors and reduce or eliminate the underperforming colors from this year's order.
• The seasonal mismatch — A pattern in which your inventory peaks do not align with your sales velocity peaks. If your spring suit inventory peaks in April but your spring suit sales peak in March, you are consistently missing the peak selling window with insufficient inventory and then carrying excess inventory through the slower April and May period. The fix is to advance your wholesale order timing to ensure that inventory arrives before the sales velocity peak rather than during or after it.
• The occasion concentration — A pattern in which a disproportionate share of suit sales are concentrated around specific occasions — weddings, proms, graduations, or holiday events. Occasion concentration indicates that your customer base is primarily occasion-driven rather than wardrobe-driven, which has implications for the styles, colors, and constructions you should prioritize. Occasion-driven customers typically prefer statement styles — checked patterns, double-breasted constructions, vested three-piece suits — over plain-color workwear suits.

How Should Wholesale Suit Buyers Adjust for Market Changes When Using Historical Data?

Historical data is the most reliable input for the buying decision, but it is a backward-looking input that does not capture market changes that occurred after last year's selling season. Wholesale suit buyers should apply three adjustments to their historical data to account for market changes.

• Adjust for trend shifts — If a specific color, pattern, or construction has emerged as a significant trend since last year's selling season — brown suits, double-breasted constructions, or checked patterns, for example — allocate a portion of this year's buying budget to the trend category even if it was not represented in last year's sales data. A reasonable allocation for trend-driven new styles is 10 to 15% of the total buying budget, with the remaining 85 to 90% allocated to proven performers from last year's data.
• Adjust for price point changes — If your retail price points have changed since last year — either through supplier price increases or deliberate repositioning — adjust your sell-through rate expectations accordingly. Higher price points typically generate lower sell-through rates and higher markdown rates, which means the sell-through thresholds you use to classify styles as core performers or underperformers may need to be adjusted.
• Adjust for competitive changes — If a new competitor has entered your market or an existing competitor has changed their suit assortment, adjust your buying plan to differentiate your assortment from theirs. If your primary competitor is stocking plain-color suits, increase your allocation to patterned and checked styles. If your competitor is focused on the occasion wear segment, increase your allocation to the professional and business casual segment.

Top Wholesale Suit Styles for a Data-Driven Buying Plan

Checked Patterned Slim Fit Grey Suit

The core performer benchmark. A checked slim-fit grey — the style that consistently appears at the top of sell-through rate rankings in US menswear retail because it serves the widest range of customer profiles and occasion contexts simultaneously. If this style was in your assortment last year and generated a high sell-through rate, increase depth this year. If it was not in your assortment, it is the right starting point for a data-driven suit buying plan.

Order Wholesale

Checked Patterned Slim Fit Navy Blue Suit

Navy is the most commercially reliable suit color in the US market — and a checked navy slim-fit is the style that most frequently appears as a core performer in sell-through rate analysis across US menswear retail markets. If your color performance data shows navy as your top-performing suit color, this is the style to increase depth on in this year's buying plan.

Order Wholesale

Checked Patterned Vested Light Grey Suit

The occasion wear indicator. If your sales data shows a concentration of suit purchases around weddings, proms, and formal occasions, vested three-piece suits should be a significant component of your buying plan. The vested suit generates higher average transaction values than a two-piece equivalent and appeals to the occasion-driven customer who wants maximum formality and visual impact. Track this style's sell-through rate separately from your two-piece suits to understand the size of your occasion wear segment.

Order Wholesale

Double Breasted Slim Fit Navy Blue Suit

The trend adjustment allocation. If your sales data does not include double-breasted suits from last year — either because you did not stock them or because they underperformed — this is the style to allocate 10 to 15% of your buying budget to as a trend-driven new addition. Double-breasted suits have been one of the strongest growth categories in US menswear retail over the past two seasons and represent a significant opportunity for buyers who have not yet incorporated them into their assortment.

Order Wholesale

Checked Patterned Slim Fit Brown Suit

The color trend allocation. Brown is the breakout suit color of the current menswear cycle — and if your color performance data from last year does not include brown, this is the color to add to this year's buying plan as a trend-driven allocation. Stock conservatively — one or two units per size in M and L — and track sell-through rate closely in the first four weeks of the selling season to determine whether to reorder or hold.

Order Wholesale

Why Wessi Wholesale Is the Right Sourcing Partner for a Data-Driven Suit Buying Plan

A data-driven buying plan is only as good as the supplier's ability to fulfill it. Wessi's wholesale suit catalog provides the style range, color depth, and inventory availability that a data-driven buying plan requires — slim-fit and double-breasted constructions in checked, plain, and vested configurations, across navy, grey, brown, and light blue color ranges, with inventory depth that supports both core performer restocking and trend-driven new additions.

For wholesale buyers who are building a data-driven suit buying plan for the first time, Wessi's catalog provides a practical starting point: a range of proven commercial styles in the colors and constructions that consistently appear as core performers in US menswear retail sell-through data, with the inventory depth to support a buying plan that is sized to your specific market rather than a generic industry average.

Contact the Wessi wholesale team to discuss your sales data analysis, request style recommendations based on your specific market and customer profile, or place a seasonal order that reflects your data-driven buying plan.