Decrease return rates
and increase conversion
Remove the guesswork from choosing sizes and allow customers to find their best fit at the click of a button. meepl's Size Recommendation uses state-of-the-art machine learning techniques to combine clothing data with body measurements, derived from your customer's meepl profile. Our technology takes into account that every garment has an individual fit
and size recommendation, which should not be generalized for a whole collection. What means our Size Recommendation is based on individual garment measurements and based on the customer specific body, using either the full meepl profile, which requires a body scan, or the meepl quick size function.
meepl Quick Size function
Alternatively to the full meepl profile, which requires a body scan, meepl provides the possibility to receive a customer’s quick size by typing in only 4 body values; gender, age, height and weight. This makes meepl accessible everywhere, no matter where your customers enjoy online shopping.
It only takes a few seconds for your customer to provide the 4 values. As soon as the customer's quick size is calculated the specific sizes for each article are automatically displayed.
This means that every recommendation is personalized and allows your customer advanced filtering based on their actual physical properties. Creating an integrated system of recommendations enables automized customer support and intelligent shopping assistance, lowers the need for returns of products and increases the confidence a customer has in a purchase. The improved shopping experience enhances customer satisfaction and loyalty. This leads to higher conversion, that promotes both cross-selling and up-selling.
Connection to our Virtual Dressing Room
The combination of both, the meepl profile and the results generated by our Size Recommendation, feeds into our Virtual Dressing Room. This solution empowers you to offer customers a completely new, personalized, 3D online shopping experience. Learn more about our Virtual Dressing Room here.
Manually captured body data often suffers from incompleteness, errors from manual data entry and inconsistencies due to varying measurement taking approaches.
With meepl and our size recommendation engine the acquisition of body data is inherently complete and consistent. In this way, we enable our corporate clients to receive size recommenations in the most effective way. In addition, the digitization of supply chains becomes possible, what permits comprehensive process optimization and makes our services particularly interesting for workwear providers.
Curious to see how established workwear providers integrate our solution into their existing processes? Download our case study with Würtenberg Design below.
Würtenberg D. Case Study
Download Würtenberg Design Case Study
Decrease returns for greater sustainability
Promote cross- and up-selling
Digitalized and automated measurement processes