Normalizing Size and Color in Fashion Using AI to Power Competitive Price Intelligence
6th Nov, 2024
By Joe Bunner
Fashion is as dynamic a market as any—and more competitive than most others. Consumer trends and customer needs are always evolving, making it challenging for fashion and apparel brands to keep up.
Despite the inherent difficulties fashion and apparel sellers face, this industry is one of the largest grossing markets in the world, estimated at $1.79 trillion in 2024. Global revenue for apparel is expected to grow at an annual rate of about 3.3% over the next four years. That means companies in this space stand to make significant revenue if they can competitively price their products, keep up with the competition, and win customer loyalty with consistent product availability.
There are three main categories in fashion and apparel. These include:
- Apparel and clothing (i.e., shirts, pants, dresses, and other apparel)
- Footwear (i.e., sneakers, sandals, heels, and other products)
- Accessories (i.e., bags, belts, watches, and so on)
If you look at all of these product types across all sorts of retailers, there is a massive amount of overlapping data based on product attributes like style and size that are difficult to normalize.
Fashion Attributes
Style, color, and size are the main attribute categories in fashion and apparel. Style attributes include things like design, look, and overall aesthetics of the product. They’re very dependent on the actual product category of fashion as well. A shirt might have a slim fit attribute associated with it, whereas a belt might have a length. All these different attributes are usually labeled within a product listing and affect the consumer’s decision-making process:
- Color (red, blue, sea green, etc.)
- Pattern (solid, striped, checked, floral, etc.)
- Material (cotton, polyester, leather, denim, silk, etc.)
- Fit (regular, slim, relaxed, oversized, tailored, etc.)
- Type (casual, formal, sporty, vintage, streetwear)
Color Complexity in Fashion
Color is perhaps the most visually distinctive attribute in fashion, yet it presents unique challenges for retailers. This is because color naming can vary across retailers and marketplaces. There are several major differences in color convention:
- A single color can be labeled differently across brands (e.g., “navy,” “midnight blue,” “deep blue”)
- Seasonal color names (e.g., “summer sage” vs. “forest green”)
- Marketing-driven names (e.g., “sunset coral” vs. “pale orange”)
Size: The Other Critical Dimension
Size in fashion refers to the dimensions or measurements that determine how fashion products fit. Depending on whether the product is a clothing item, shoes, or a hat, there will be different sizing options. Types of sizes include:
- Standard sizes (XS, S, M, L, XL, XXL, XXL)
- Custom sizes (based on brand, retailer, country, etc.)
A single type of product may have different sizing labels. For instance, one pants listing may use traditional S, M, L, XL sizing, while another pants listing may use 24, 25, or 26, to refer to the waist measurement.
Size is a dynamic attribute that changes based on current trends. For example, there has recently been a significant shift towards inclusive sizing. Size inclusivity refers to the practice of selling apparel in a wide range of sizes to accommodate people of all body types. Consumers are more aware of this trend and are demanding a broader range of sizing offerings from the brands they shop from.
In the US market, in particular, some 67% of American women wear a size 14 or above and may be interested in purchasing plus-size clothing. There is a growing demand in the plus-size market for more options and a wider selection. Many brands are considering expanding their sizes to accommodate more shoppers and tap into this growing revenue channel.
Pricing Based on Size and Color
Many fashion products are priced differently based on size and color. Let’s take a look at an example of what this can look like.
A popular beauty brand (see image) is known for its viral lip tint. While most of the color variants are priced at $9.90 on Amazon, a specific colorway option, featuring less pigmented options, is priced at $9.57. This price differential is driven by both material costs and market demand.
Different colorways (any of a range of combinations of colors in which a style or design is available) of the same product often command different prices also. This is based on:
- Dye costs (some colors require more expensive processes)
- Seasonal demand (traditional colors vs. trend colors)
- Exclusivity (limited edition colors)
An example of price variations by size is a women’s shirt that is being sold on Amazon as shown below. For this product, there are no style attributes to choose from. The only parameter the shopper has to select is the size they’d like to purchase. They can choose from S to XL. On the top, we can see that the product in size S is ₹389. Below, the size XL version of this same shirt is ₹399. This price increase is correlated to the change in size.
So why are these same products priced differently? In an analysis of One Six, a plus-size clothing brand, several reasons for this difference in plus-size clothing were determined.
- Extra material is needed, hence an increase in production costs
- Extra stitching costs, hence an increase in production costs
- Production of plus-size clothing often means acquiring specialized machinery
- Smaller scale production runs for plus-size clothing means these initiatives often don’t benefit from cost savings
Some sizes are sold more than others, meaning that in-demand sizes for certain apparel can affect pricing as well. Brands want to be able to charge as much as possible for their listing without risking losing a sale to a competitor.
The Competitive Pricing Challenge: Normalizing Product Attributes Across Competitors in Apparel and Fashion
There are hundreds of possible attribute permutations for every single apparel product. Some retailers may only sell core sizes and basic colors; some may sell a mix of sizes for multiple style types. Most retailers also sell multiple color variants for all styles they have on catalog. Other retailers may only sell a single, in-demand size of the product. Also, when other retailers are selling the product, it’s unlikely that their naming conventions, color options, style options, and sizing match yours one-for-one.
In one analysis, it was found that there were 800+ unique values for heel sizes and 1000+ unique values for shirts and tops at a single retailer! If you’re looking to compare prices, the effort involved in setting up and managing lookup tables to identify discrepancies when one retailer uses European sizes and another uses USA sizes, for example, is simply too onerous to contemplate doing. Colors only add to the complexity – as similar colors may have new names in different regions and locations as well!
Even if you managed to find all the discrepancies between product attributes, you would still need to update them any time a competitor changed a convention.
Still, monitoring your competitors and strategically pricing your listings is essential to maintain and grow market share. So what do you do? You can’t simply eyeball your competitor’s website to check their pricing and naming conventions. Instead, you need advanced algorithms to scan the entire marketplace, identify individual products being sold, and normalize their data and attributes for analysis.
Getting Color and Size Level Pricing Intelligence
With DataWeave, size and color are just two of several dimensions of a product instead of an impossible big data problem for teams. Our product matching engine can easily handle color and sizing complexity via our AI-driven approach combined with human verification.
This works by using AI built on more than 10 years of product catalog data across thousands of retail websites. It matches common identifiers, like UPC, SKU code, and other attributes for harmonization before employing a large language model (LLM) prompts to normalize color variations and sizing to a single standard.
For example, if a competitor has the smallest size listed as Sm but has your smallest listing identified as S, DataWeave can match those two attributes using AI. Similar classification can be performed on color as well.
Complex LLM prompts are pre-established so that this process is fast and efficient, taking minutes rather than weeks of manual effort.
Harmonizing products along with their color and sizing data across different retailers for further analysis has several benefits. Most importantly, product matching helps teams conduct better competitive analysis, allowing them to stay informed about market trends, competitors’ offerings, and how those competitors are pricing various permutations of the same product. It helps ensure that you’re offering the most competitive assortment of sizing in several colors to win more market share as well. Overall, it’s easier for teams to gain insights and exploit their findings when all the data is clean and available at their fingertips.
Product Matching Size and Color in Apparel and Fashion
Color and size are crucial attributes for retailers and brands in the apparel and fashion industry. It adds a level of complexity that can’t be overstated. While it’s a necessity to win consumers (more colors and sizes will mean a wider potential reach), the more permutations you add to your listing, the more complicated it will be to track it against your competition. However, This challenge is worth undertaking as long as you have the right solutions at your disposal.
With a strategy backed by advanced technology to discover identical and similar products across the competitive landscape and normalize their color and sizing attributes, you can ensure that you are competitively pricing your products and offering the best assortment possible. Employing DataWeave’s AI technology to find competitor listings, match products across variants, and track pricing regularly is the way to go.
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