I run an ecommerce clothing brand called Concrete Orchids. We reach out regularly to customers asking for honest feedback on our products. In one instance, we've used Judge.me's Shopify integration to gather reviews from customers. We saw customers complain about sizing issues with our "One Tree" Boxy Hoodie, as well as sales data reporting a high return/exchange % on our boxy hoodie. We corrected the sizing issues and saw improvements in our data as the stock moved. A more analytical observation would be on our upsell data. We saw a low conversion % on same-product upsells. For a fashion brand, this is to be expected. Customers want variety and are willing to order more products if they fit the aesthetic they're looking for, for a reasonable price. We launched more product types, such as beanies, sunglasses, tees, thermals, etc. The conversion rate increased as our customers preferred the variety over a discounted same-product upsell.
One example that stands out was a noticeable dip in sales for our seafood dishes during the winter months. A deeper dive into our POS data revealed that while seafood remained popular overall, certain dishes weren't resonating as well during colder months. Specifically, our lighter, chilled seafood appetizers saw a significant decline, while heartier, warming dishes like seafood stew and cioppino remained consistent. This data-driven insight led us to adjust our menu strategy. We introduced a seasonal menu rotation, featuring heartier seafood dishes in the winter months and lighter options in the summer. We also incorporated customer feedback into our menu development, adding new seafood dishes that aligned with their preferences, such as a pan-seared salmon with roasted root vegetables and a creamy seafood chowder. This data-informed approach not only helped us boost seafood sales during the winter months but also demonstrated our commitment to listening to our customers and adapting our offerings to their evolving tastes.