"41% shoppers have abandoned a transaction at a virtual check-out in 2018, compared to 24% who have walked away from a purchase in-store."
Online shopping vs. in-store shopping statistics indicate that the inclination to window-shop is much higher in the case of online shoppers than it is for brick-and-mortar store shoppers. Unfortunately, this same study also found that many vendors have little insight on the reasons behind such high abandonment rates, making it difficult to tackle this online conversion challenge.
E-commerce sites require a special amount of detail and an exceptional amount of user-friendliness in order to be successful. A big part of the UX (user experience) of e-commerce sites lies in properly categorizing your products.If you can master the science of product categories, you’re well on your way to a great UX… and more sales!
When done right, filters enable users to narrow down a website’s selection of thousands of products to only those few items that match their particular needs and interests.Yet, despite it being a central aspect of the user’s e-commerce product browsing, 84% of websites offer a lacklustre filtering experience.
In fact, the top research institute reveals -
42% of major e-commerce websites lack category-specific filtering types for several of their core product verticals.
Let's dive in,
In this article,we’ll outline our research findings on why category-specific sorting is so important to the user’s product finding abilities, and how it can be implemented.
Table of Contents
- What are category-specific filters
- Types of category-specific [‘Soft ’Boundary Sorting and ‘Hard’ Boundary Filtering]
- Why Users Often Prefer “Soft” Boundaries
- How does sorting boost your website?
- Key Takeaway
The users are interested in filtering a product list across category-specific attributes, and not just the website-wide attributes (such as brand, price, user ratings, etc.)
In the below example of Myntra, category - filters for jumpsuits are listed as[ bundles, closure, number of pockets, sizes, type ].
Similarly ,category - filters for dungarees are listed as[ bundles,size and wash care ].
[‘Soft ’Boundary Sorting and ‘Hard’ Boundary Filtering]
Filters set the criteria for whether a given product is in- or excluded from the product list (i.e. what is displayed) whereas Sorting determines the sequence of those products (i.e. how it is displayed).
Filters – Sets a “hard” boundary. Any product that doesn’t strictly fall within the selected value(s) will be cut off. It is a great way for users to exclude any products that don’t match specific criteria.
Sorting – Applies a “soft” boundary. The products are ordered by the chosen sort type (in the case of category-specific sort types that typically means a product attribute)
Fear of missing out –
The user may not want to set a hard boundary in fear of missing out on relevant products that fall just outside their defined range, hence many users prefer the soft boundaries of sorting.
Lacks domain knowledge –
The user may not know or feel like they have sufficient knowledge about the product domain (the natural spec jumps within the vertical, the implications of different product attributes, etc) to set appropriate cut-off criteria.
Unclear about own preferences –
The user may not be entirely clear on their own preferences and restrictions (budgetary limitations, compatibility requirements, usage conditions, etc). Oftentimes users purchasing for themselves are willing to flex their criteria significantly once they start seeing what’s available and begin to understand the product domain better.
Prevents Accidental Product Elimination -
When the user can only filter and not sort by category-specific attributes they are limited to setting “hard” boundaries only. This leaves the user with two less-than-ideal options: either
i) apply the preferred range as filters and run the risk of accidental product elimination, or
ii) loosen the preferred range to be more inclusive to avoid this elimination at the cost of ending up with a much poorer signal-to-noise ratio (due to numerous less relevant items suddenly being included).
The more specific are the filters, the more is the product discovery. In the above two examples, it is pretty much obvious about user preferences.
2. Increase Domain and site insight-
This is obviously very helpful to novice users because their lack of domain knowledge means they don’t instinctively know the natural “spec jumps” in the product vertical and might therefore inadvertently eliminate large clusters of perfectly relevant products
Category-specific sort types are ultimately about empowering users with the tools they need to reach the product selection they want and have it presented in a way that suits their unique interests. It’s an obvious opportunity to increase the return on existing product data investments, empower your users and get ahead of the competition.
Sources- Barclaycard, Baymard, Myntra, Ajio