top of page

You're in! This is going to be epic! 🥳


Stay ahead of the curve and sign-up for monthly updates on fashion trends, industry news + retail tips

  • Writer's pictureCharlotte Mackenzie

Post-season analysis: How to maximise your brand's retail profit margin

So, you want to stay ahead of the competition and optimise your product offering for more retail profit, a higher conversion rate and a more seamless customer experience? Of course, you do. This should be your raison d'être with every decision you make. But you won't get there with just a wave of some magic wand, this all relies on post-season analyses of sales, margins, competitors and growth. Here’s how to not miss a $3million unicorn (true story).

Now, we know there are plenty of ways to increase profitability, from improving size availability to setting retail budgets, but there's another piece that you should start getting acquainted with pronto. It's the post-season analysis, sometimes referred to as a post-season review or retail SWOT analysis.

As tempting as it is to pretend the past season never existed, or ride off its coattails blindly into the future, your brand must acknowledge the elephant in the room (and we’re not talking about that sale rack, yet). Indeed, it's the all-important post-seasonal analysis.

In this article, we're going deep on the very definition of a post-season analysis, why it's important, how best to use it, and we'll even guide you on what to look for so you can get started on building your retail strategy, today.

What is a post-season analysis?

A post-season analysis provides your whole team with insights on the performance of a previous season, capsule collection, or marketing activation related to product performance (do you have a new core style on your hands?), trends (is low-rise really on the rise?) and buyer behaviors (did Insta-shopping accelerate your online store performance?).

The findings are then used to form the basis for planning and forecasting upcoming seasons, as you nut out exactly what your growth opportunities and risks are. In other words, you can create your blueprint for success. It’s imperative to perform a post-season analysis quarterly to stay on top of changes in customer demand.

A post season analysis is the first step in merchandise planning and buying cycle.

circular infographic depicting the fashion merchandise buying and planning cycle
Merchandise planning and buying cycle

These findings are then analysed to improve buying decisions with the intent to have a ripple effect on customer conversions going into the following season.

The most common mistake? More is not more. Don’t make the assumption you need to always buy more inventory to get better results and grow your business. It’s important to understand your business so you can identify the levers to pull to affect change.

What can you do instead?

  1. Start looking at what's driving the retail profit and shift the inventory investment for the following season accordingly. To do this, take a look at which categories, brands and products drove the most retail profit.

  2. Opportunities = More Sales - learn how different colours performed, what sizes were selling out, and which prices hit your customer's sweet spot.

  3. Weigh in on how much total inventory sold at full price vs how much you bought to begin with.

Yes, a post-season analysis can get very detailed - but the more stats, the merrier. It pays to dig deep when figuring out which products drove sales and profit, and how this will influence the future buying cycle.

Why is a post-season analysis important?

It provides you with the foundations for the next season. It’s your marathon warm down so you don’t get injured. It’s your make-up removal routine so you don’t wake up with spots. On average, a retailer that performs a post-season analysis will achieve better results than one that doesn't.

In fact, retailers can see +146% growth in profitability in one category alone after completing a post-season analysis. If that's not reason enough, we've got a few others up our sleeve:

  • Assists cash flow

  • Increases sell-through rate

  • Provides confidence to increase sales budgets

How do I complete a post-season analysis?

Good question. Firstly, before kicking off analysis, brands must create a data set for the period of time you wish to look at.

Creating your data set: You'll need the below metrics for every product in the range you are analysing before you can get started:

  • Sales $ ex GST

  • Sales Units

  • RRPs

  • Cost prices to calculate retail profit margin (see glossary)

  • Buy units (see glossary)

Select a time frame you want to analyse (e.g Q1 Jan-Mar) and then spend a good couple of hours compiling your data from all your various systems in a format like below.

post seasonal analysis example data set table
Bold column heading indicates calculated field

Or if you have Style Arcade, pull the below information together in less time than it takes to make a coffee using the Rollups tab. Watch the video below to see how.

There are a few fields that need to be calculated manually using retail math formulas. If you're new to the retail game, I'm sure you're asking yourself:

  1. How do I calculate retail profit?

  2. What is the retail markdown formula?

  3. How do I calculate sell through rate?

Here's a list of formulas we prepared earlier to populate the items above, consider this your cheat sheet to save, to pin, to print, to love:

Once you have your data set, you can slice it in multiple ways to analyse categories, brands, silhouettes, prices or colours considering the following:

  • Category contribution %

  • Brand contributions %

  • Pricing hierarchy

  • Sizing

  • Colour

  • Silhouette

  • Width and depth

  • Markdowns

Below is an example of what you can achieve purely from one of the above. 6x in one category?! Imagine that across your whole range! 😍

Case Study: Category growth

The opportunities in getting it right

As a merchandise planning consultant, I used the above logic to uncover a 6X year on year growth opportunity in just one category.

What we uncovered was there was hidden customer demand in a specific category. Empowered with this knowledge from the post-season analysis, the brand gave the customer what they wanted and in turn drove significant additional revenue.

How do I analyse the post-season data ?

Here are some of the key metrics to focus on and what they are telling you:

1. Category Sales mix % vs Buy mix % - Compare the sales mix % to the buy mix % to know whether you should buy more or less of the same category/colour next season.

In the example provided below, Tops made up 36% sales mix even though it only made up 26% of the buy. An over-indexed sales mix to buy mix is a success, and an opportunity. This indicates if you had bought more of this product or category you could have achieved more sales.

Graph of sales mix versus buy mix by category
10% higher in sales vs buy is a clear opportunity to invest more in this category to see sales growth.

Conversely, look out for the examples where you were overstocked; these are categories where the buy mix % is higher than the sales mix % and you will need to reduce your investment in these next season.

Using Style Arcade, Blue Bungalow were able to identify an opportunity in cardigans, which resulted in +261% growth in one quarter.

2. Profit % vs markdown % - Your profit % is one of/if not the most important metric to track to know if you want to increase or decrease investment in a category/brand next season.

If a product or category didn’t work for you, eg. you lost profit you could have made by spending markdown dollars to sell it in a clearance sale, then you would steer clear of similar products the following season or reduce the investment to ensure a high sell through %.

Your intake margin, markdown and profit are all interlinked. It all starts with the intake margin (initial margin before discounting), then the product is marked down (markdown %) which leads to the final profit %. For those playing at home, the calculation is:

profit % = 1-(1-intake margin %) / (1-markdown %)

Fashion Industry Benchmarks

It's always good to know how your numbers stack up to everyone else. We've found that based on the above formula, the benchmarks for a fashion apparel brand is:

Benchmark figures
Note: Each business operates differently so it’s always important to check the benchmarks internally and adjust accordingly.

3. Sell-through rate (ST%) indicates the percentage of stock you sold vs how much you bought.

Sell through rate (ST%) = sold units/purchased units x 100

Say you purchased 100 black long sleeve tops and sold 82 of them your sell through on this item would be 82%.

An industry benchmark sell-through rate for a fashion retailer is around 70-75%. You ideally want to sell 70-75% of the inventory you bought in any one season.

This will leave you with 25-30% to sell on markdown going into the following season. If a product category achieving higher than a 75% sell-through rate has over-performed, you might want to look into buying more of this next season.

Anything lower than 60% would be considered a slow performer and future investment may need to be reviewed and adjusted.

It’s important to consider your ST% by full price sales and mark down sales as the total can sometimes be deceiving.

For example, you purchased 100 units of a top, and sold 40 units at full price and 30 on mark down, your total ST% would indicate 70% which would appear to be a good performance.

However the true ST% at full price would only be 40%. You would hate to mistakenly over-invest in a similar product the following season because you thought you had sold 70 units when in fact you should be reducing the investment.

When working for a large retailer or brand that stocks a large volume of SKUs, it's really easy to miss the detail. Particularly if you are working off excel spreadsheets. This is where images of products alongside your numbers is so key and can help jog your memory. 🤔 Oh yes that's right, we put that floral item on markdown...

But without a system to automatically tell you the number of units that sold while on markdown it means you will be required to dig into data by date range to manually calculate this metric ☠️ (If you've ever had to do this, you'll realise how painful this exercise is).

Style Arcade automatically tracks full price ST% for you, making it easy to react in season. By being able to see this so easily, means you can keep on top of it and ensure strong ST% result come post season analysis time.

screen grab of Style Arcade products showing sell through percentage and product suggestions