Product data enrichment or attribution for fashion and apparel retailers is the process of enhancing and expanding the information associated with clothing and accessory items to describe the item in the language of the customer and to show exactly what they are purchasing. Done well, product enrichment will improve the efficiency of marketing budgets, improve the digital shopping experience, and deliver more accurate demand forecasting.
Detailed Product Enrichment
Ultimately, the goal is to create more complete, high-quality, and engaging product data to improve the customer experience and drive sales. With the detailed product attributes, it is important to use customer-centric language, not just the manufacturer or merchandiser terminology. The focus should be on attributes customers actually search for and care about, rather than just the basic facts such as it’s a women’s dress, that is pink and of a certain length. The customer typically cares about more than that, they are typically looking for certain highlight features, occasions as well as how the fabric feels and drapes, for example: “elegant, floaty dress for a wedding that covers my arms” or “Brat summer jeans for a festival”. Complete, consistent data can then fill in the gaps that are most relevant to customers.
Here are key aspects of product data enrichment specifically for apparel retailers:
Physical Attributes
- Style details (neckline, sleeve length, hem style, etc.)
- Fit details (tight, standard, loose)
- Colour, pattern variations
- Details or special features
- Material and fabric composition (with care instructions)
- Size information (measurements, fit guides, model’s details)
On average retailers have 5-8 product features per item (less than 50% of the required physical attribute data) and after an audit of that data it is typically only around 60% accurate.
Contextual Information
- Seasonal relevance (both collection and weather)
- Occasion suitability (casual, formal, workwear, etc.)
- Suitability (modesty, sustainability)
- Trend information (at a locale and brand)
Very rarely added, but enables the customer’s intent to be understood.
Dynamic Seasonal & Zeitgeist Data
- Zeitgeist data to respond to key trending items
- Seasonal data to respond to key calendar events before they start trending
Whether it is #bratsummer #MobWife or #GorpCore these are essential to ensure products are always relevant.
(Title image from Heat Magazine)