How Shopper Body Data Can Improve Product Design, Planning and Sales – Footwear News
As retailers diversify their revenue streams and allocate inventory, merchandise planning becomes more complex – and more critical to getting the right results. It is common practice to look at historical purchasing data and use that to predict modeling. However, AI Fit technology company 3DLook believes that the best solution comes from actual data on the customer’s body.
“Poor fit is the number one reason clothing is returning,” said Whitney Cathcart, co-founder and chief strategy officer, 3DLook. “If you understand what your customers look like and can break this down into planning and sales, you would not only lower your ROI, but also sell products to places that are closest to your customers.”
Many clothing and footwear companies offer sizing guidelines online. However, these can be inaccurate or rely on buyers to know their exact measurements. Individual styles can also differ within the same brand, making it difficult to make consistent and trustworthy recommendations.
Then there is the challenge of individual differences between customers. Existing purchase data provides insights into the most popular sizes in a given retail location, but these may not be suitable for every consumer. Unless a business is exactly the right size for their customers, it can be prone to losing future purchases when the buyer finds a retailer that offers a better match.
“With a proper understanding of how customer bases differ from region to region, you can distribute clothing of different sizes accordingly and realign patterns and scoring rules to better match your actual customers’ body measurements and shapes,” said Cathcart. “For example, there are more people in Texas who are tall and curvy and customers in Florida who are more short and curvy.”
The 3DLook app requires two photos of the user to show their body for recommendations.
LOAN: 3D look
To identify these nuances of a customer base, technology can be a useful and easy to use tool. 3DLook guides customers through a quick scan process that takes two photos of their bodies from each smartphone against each background. These photos will be permanently deleted from the 3DLook platform once they have been processed in order to preserve the landmarks on the user’s body and create their unique 3D model.
By collecting these models, which are then compared with certain product data, 3DLook can generate individual recommendations for each buyer. These are based not only on the size of the consumer, but also on their specific shape and dimensions. In this way, it mimics the recommendations of a business partner.
“When you go into a store, the salesman comes up to you and sees that you are trying to buy something,” said Cathcart. “She knows the range, she can see your body type and ask what style you’re looking for. She has the knowledge of what customers with similar preferences have bought and she can actually help you find something that fits. Now that offline shopping is banned, people are expecting the same online experience. “
It is important to understand where the product needs to go in the distribution chain to minimize inventory waste and inter-store shipping. By using customization data and incorporating it early into the decision-making process in the product development phase, brands can improve customer satisfaction, build loyalty, and maximize inventory.