Private Client Recommendations Hub
During my time at the Moda Operandi, I have had the chance to learn and understand the full workflow of our internal sales team and their interactions with our VIP clients. One of the big initiatives we took on as a tech team, was to help the sales team give a more tailored experience to their high valued clients by recommending items they will be interested in based on their past purchases.
Role: Design Direction + Execution and Product strategy
Suggestions and recommendations shown on the Moda Operandi E-commerce site for users to find similar products.
Visually Similar Recommendations
What Should I Send?
In their current workflow, Advisors would go on our e-commerce site to curate and find new pieces, or similar items to send to clients.
By leveraging existing data science algorithms on our e-commerce site, like “More Like This” and visually similar recommendations for sold out items, we knew we could help Advisors recommend items to clients quickly.
Design Solution
We landed on an MVP that used our visually similar algorithm to suggest items that look like similar to a reference provided.
Search for products based on our existing inventory.
Adding the ability to take action on an item, that could be coping the URL to quickly text the item to your client or to help them build curated emails.
Pain points we are trying to solve for:
Advisors go to only one tool/place to look for pieces to recommend
Clients sometimes want to find similar items to something that might not be available any longer or items that work better for them
Design Considerations
As a team, we wanted to quickly ship this feature and iterate on it as we saw usage surge. Therefore we wanted to reuse as many patterns as we could. I decided to use the product card we had on our e-commerce site since it was already a familiar pattern for the Advisors. However, some changes were made to meet the needs of the Advisors and meet the goal of the product.
What changed?
Show size availability at a glance without the need to hover over
Instead of optimizing for “Add to Cart”, we made the main interaction a dropdown with options to quickly copy links.
Explorations
V1. When first staring to do explorations, I knew I wanted to leverage established patterns we use on the e-commerce site so it felt familiar to the user and it would also make the implementation a lot more seamless.
V2. We originally had the idea to show recommendations based on a clients’ past purchases and direct affinities to specific designers and products. However, that quickly turned very complex on the back-end side so we decided to scope down the MVP.
V3. Eventually, we decided to make this part of the proprietary internal tool we Advisors use to make it more accessible and aim for faster/larger adoption.
Measuring Success
We put together a set of thresholds and KPIs to make sure we are measuring the success of this product:
Phase 1 - Adoption:
If 50% of Advisors are using this tool to aid their sales and adopting it in their daily workflows, then we’ll know we can continue to develop the tool with more features.
Phase 2 - Conversion
Is what the algorithm showing to stylist helpful? What are they sending and if the items they are sending closing sales?
With the “thumbs up”/“thumbs down” feature we will not only track usage but also make the algorithms smarter.