The feed problem
For merchants selling online, omni-channel is crucial to the success of their e-commerce presence. Staying competitive means meeting their current market where they are, and expanding to new markets to scale their business.
BigCommerce is an e-commerce platform built on flexibility. There are many native capabilities enabling merchants to manage storefronts, products, customers and orders, but also plenty of partner integrations to fill the gaps. As such, there are a range of native and partner solutions to support a merchant’s growth depending on the stage of their omni-channel strategy. However, it comes with several complexities.
Products won’t list correctly if they are not optimized to a channel’s taxonomy - the shopper will never find them organically. BigCommerce did not have a native solution.
Managing omni-channel data is a full-time commitment. A merchant’s categorization of products is NEVER the same as a channel’s and product attributes are not 1:1. That means the merchant must modify their feed for every SKU for every channel - which could result in 1000’s of product modifications.
Take the adidas example above: for Google ads and Amazon, the merchant needs to find the corresponding product category AND modify the title with product attributes so the shopper has appropriate context.
To ensure merchant’s omni-channel success, BigCommerce was in need of a feed management solution for small medium businesses (SMBs) to save them countless hours optimizing product data.
Current experience
To start this initiative, I led multiple service blueprinting workshops to map the merchant experience and technical limitations of the BigCommerce platform. These consisted of front-end & backend engineers, product managers, designers and UX researchers and helped all stakeholders understand the architecture.
The channels domain had been built with partners in mind: BigCommerce created sample app SDKs to predefine the experience and UI patterns (something I helped refine and publish later), then partners develop a “connector app” to communicate with the channel.
While channels are connected via apps, managing listings happens at a platform level. There were gaps in the experience because the catalog was missing key functionality like per-product listing, bulk edits & errors.
After a channel was authenticated, the merchant had a one-way connection to list their entire catalog, but little in the way of optimizing the listing.
I worked with our UX research team concurrently to understand where our merchants struggled the most. Here’s some of the highlights:
"I have to figure out how to get information from Shopkeep to BigCommerce to Facebook. [If there’s a way to see] these are all the fields I’ve imported, these are the fields BigCommerce mapped them to and these are the fields Facebook is looks for and what’s missing."
A partnership solution
In July 2021 (one month before I joined), BigCommerce acquired the feed management platform Feedonomics. Feedonomics provides a managed service in which trained professionals optimize product data for enterprise businesses using a SQL-based UI.
An initiative was started at BigCommerce shortly thereafter to leverage the power of Feedonomics for all existing BigCommerce merchants. My team was tasked with creating a down-market solution for optimizing channel product data, utilizing Feedonomics APIs.
Feedonomics had the APIs to solve our merchant’s feed issues, but their platform is extremely complex and part of a managed service. Our goal was to make a subset of features native and stupid-simple.
In collaboration with product and engineering from both companies, we derived a hypothesis for the ideal merchant experience.
We wanted to focus on 3 essential features for the product MVP for 3 channels we had close partnerships with. Because of the complexity of using Feedonomics APIs, the interface would be built on an app using BigCommerce design system, allowing for shorter feedback loops and less infrastructure setbacks.
MVP experience
Over the course of several months, we crafted designed a UI according to the desired user experience, product needs, API capabilities and existing platform workflows.
In partnering with our UX research team, we tested with 7 merchants based on the channels they currently sell on and their catalog complexity. We learned quickly that merchants needed a high level of flexibility to correctly categorize products and match their corresponding attributes.
Through testing with our merchants and partners, we found an intuitive, repeatable pattern for creating listing rules to optimize channel listings in bulk.
Our solution allowed merchants to use any existing product data in their catalog to create groupings applied to the channel category or required attributes.
With final validation from users, I worked closely with our front-end engineers to implement the UI and test on sandbox stores.
Preparing for beta and beyond
While the core experience was in development, we started discovery on how to integrate the service with the BigCommerce platform and identify additional dependencies.
This included crucial items such as discovery and billing of the optimized listings service, which required cross-collaboration and iteration with multiple other teams across BigCommerce.
Using the Scrum@Scale framework, we were able to create the UX patterns needed to integrate our solution with the core platform, as well as establish new standards for UX company-wide.
For instance, we didn't have a pattern for upgrades (how we ultimately framed the service) so we needed to create a new experience and set the standard for new initiatives.
.png)
This project contains many complexities and problems that could not be summed up in a short article. If you'd like to learn more reach out and we can chat.