Size recommendation: helping every customer choose right.
Size recommendation means telling each customer, product by product, which size fits them, by crossing their body data with the garment's real measurements. It is the direct answer to the question every fashion shopper asks in front of the size selector: “which size should I take?”
Done well, it turns a moment of hesitation into a moment of decision.
Why size is THE friction point
The same customer is not the same size everywhere: M at one brand, L at another, sometimes both at the same brand depending on the cut. Sizes are not a standard, they are conventions that vary across brands, lines and fabrics.
Customers know this from experience. That is why a plain “M” on a selector doesn't reassure them: they have been let down by an M before.
What a good recommendation requires
A reliable recommendation crosses two things: what you know about the customer (height, weight, body type, measurements if they provide them) and what you know about the garment (its real measurements, fabric and cut).
The second part makes the difference. Many tools reason in “usual size”; the most reliable ones reason from each product's real data, provided by the brand.
Product by product, not in general
A concrete example: a customer hesitates between M and L for a slim-fit half-zip. On an oversized sweater from the same store, the question would not arise the same way. The right answer depends on the product: a useful recommendation is therefore computed product by product, with a fit description: where the garment will hug, where it will fall straight.
That description is what settles the “between two sizes” case: the customer knows whether the M will be close to the body or the L will fall looser, and picks what they prefer to wear.
Recommendation alone, or with try-on?
They reinforce each other. The recommended size answers “which size should I order”; virtual try-on answers “what does it look like on me”. Together they close both exits of doubt, and they run on the same integration, with no extra work.
How OptiDress addresses this
OptiSize is the native size recommendation inside OptiDress: it crosses the body data the visitor provided, without uploading any photo, with each garment's real measurements, and states the size to order product by product, with a fit description. The same profile drives the try-on on their 3D digital twin, and the avatar is kept for 30 days on the store.
The whole joins your product pages in under 24 hours, with no redesign, on all major e-commerce platforms, with a subscription based on the number of monthly visitors, no commitment.
Frequently asked questions.
What happens when a customer is between two sizes?
The recommendation comes with a fit description: the customer knows the smaller size will sit closer to the body and the larger one will fall looser, and decides based on preference.
Does the recommendation apply to every product?
Yes, that is the point: it is computed product by product, from each garment's real measurements, fabric and cut, not from a general rule.
Do we have to change our product pages?
No. OptiSize integrates into your existing store in under 24 hours, with no redesign: your product pages stay identical, the recommendation is added to them.