E-COMMERCE PRODUCT TAXONOMY FOR APPLIANCES
Best Buy appliances have been a pillar growth area in a competitive market for the last couple of years. I drove the information architecture redesign for their online kitchen appliance categories with the goal of helping users find and discover products by aligning the taxonomy and navigation to their mental model through research and user testing methods. Not only did this helped build consistency between the website's navigational elements, but it also improved the discoverability of Best Buy's wide assortment of products, decreased the time customers spent looking for a product and ultimately resulted in improved findability and usability for customer wayfinding.
In this case study, I will take you through my design process starting with how I understood the situation, conducted research, discovered opportunities and defined the major problems to solve. I will also explain how I collaborated with team members to ideate, design and implement the solutions, and finally evaluate the performance post production to determine if we successfully met our goals and KPIs.
I lead the research, testing, and delivery of sitemaps and navigational requirements for the information architecture of Best Buy's online retail appliance categories. I collaborated with a business analyst, digital merchandiser and SEO specialist on the analytics, execution and labeling strategy.
To make a purchase, customers need to be able to easily find the products that they are looking for. As the online assortment continues to grow with more and more products every moth, a major goal among stakeholders was to bring visibility to the wide assortment of small kitchen appliances that Best Buy carries online and to help customers reach a purchasable product page.
Improve the discoverability of our wide assortment of products
Make it quick and easy for a customer to get to the product that they are interested in
Key Performance Indicators
Increase traffic to select category pages
Increase % to a product description page
Decrease time to navigate to a category page
Decrease bounce rate on product listing page
Decrease volume of search queries on product listing pages
Research & Discovery
During the research phase, I conducted stakeholder interviews with our buyers and e-commerce executives to better understand the goals and to align on the problems we were trying to solve. I worked with the team to develop proto-personas as a quick way to build empathy with our customers and conducted a competitive analysis and a series of user tests to understand customer mental models and navigation behaviors.
I interviewed our buyers to understand their budget forecasts for the quarter and considered their goals for the assortment of products Best Buy will carry online. The beverage appliance categories seemed to be underperforming and as the assortment was continuing to expand, they wanted help to increase awareness, discoverability and drive traffic to all products.
I also met with a digital retail manager to gain insight into the red flags appearing in category performance reports. The main concern was that % to a product description page was lower for small kitchen appliance categories, compared to other similar online retail categories. This could be due to a variety of factors, such as price, the audience visiting the website, etc, but the digital merchandising team needed help to define a wayfinding strategy to potentially bring more interest and qualified traffic to those categories.
I worked with a business analyst to create a baseline of important metrics to monitor performance through using Adobe Analytics. Listed below are my considerations when evaluating each metric as well as a search log analysis.
Traffic to Categories
How is traffic compared with other similar categories?
Are there other factors that explain traffic disparities? (other navigational elements)
The expectation of traffic based on the importance of the category
Is the category strategically significant even if it has low usage?
Does the page drive traffic to other important pages?
Is content part of a longer user journey, which requires multiple visits before conversion?
Bounce Rate on Product Listing Pages
These pages are meant for customers to narrow down their selection to a product
Does the label name describe the category accurately?
Do on-page elements prevent people from understanding the content?
Based on internal and external factors, is the entrance rate lower than expected?
Does the category have a high conversion rate despite a low entrance rate?
Search Volume & Queries
Is the search query already represented by a category?
Are customers noticing facets on the page to help narrow their search?
What are customers searching for?
From the search log analysis, we discovered that:
1. Customer search queries were heavily brand specific.
2. Some customers searching for specific products were being redirected to a broader parent page.
3. The queries for brand-specific searches resulted in higher exit rates.
I audited the current product taxonomy with a system focusing on organizational schema and principles. Heuristically, I noticed opportunities for recategorization as well as parent-child relationships in the hierarchy based on product saturation and Hick's and Miller's psychological principles of memory and decision making. Then, I conducted a competitive analysis by looking at how our competitors were organizing their product hierarchy and paid attention to the similarities and differences. These websites included Canadain Tire, The Bay, Walmart, and Costco. Because customers spend most of their time on other competitor sites when away from Best Buy, it's important to consider following any industry-standard trends to foster a sense of familiarity when navigating our own website.
Next, my team and I got together with our buyers to brainstorm customer pain points and needs through the use of building proto-personas. For this first slice, we wanted to follow lean UX principles and leveraged the resources we had available on customer demographics and purchasing behaviors from consumer insights reports, while also gathering the right people into the workshop to contribute educated guesses. Any more validation and adjustments to our target audience could be done through future iterations. We developed two major proto personas:
Now that we had some valuable insight into our target audience, we used these personas to build screeners for the user tests that followed. Our goals were to understand the customers mental model for the grouping of these categories, and to validate whether our proposed hierarchy would perform better against the current state.
We recruited 20 participants using Card Sort from Optimal Workshop with the goals of:
Understanding how customers naturally group products in their minds.
Identifying intuitive category and subcategory names.
Here are some results that came out of the card sort with the affinity between products highlighted in yellow:
Knowing the affinity between categories, as well as common groupings and labels that customers used to group like products together, I worked with an SEO specialist to create a new product taxonomy that matched the user mental model and labels that satisfied both user understanding and search volume opportunities.
Because these changes would require a significant amount of time and effort in reorganizing the products, we wanted to validate if the proposed hierarchy would perform better than the current state by looking at 3 major metrics. Time taken, success rate, and directness. Tree testing is the fastest, most effective way to spot problems with a site’s information architecture. I worked with our UX designer to ask representative users to find products or information using a simple, clickable “tree” of the site’s navigation; and we record each click. The resulting data shows which category structures and labels are intuitive to customers (and search engines), and which ones likely cause confusion, abandonment and lost sales.
Here's the approach we used for our tests:
We used Treejack from Optimal Workshop to run the tests and UserTesting.com to recruit participants.
We recruited 15 users for the tree tests.
We ran a balanced preference test, by randomly assigning users to navigate hierarchies A and B to track performance.
We focused on the categories that were affected by the redesign.
Here's what we learned from the results:
1. Time taken decreased for products under the coffee & espresso categories in the proposed taxonomy.
2. Directness collectively improved for all categories in the proposed taxonomy.
3. Success rate improved for sous vides machines in the proposed taxonomy.
Define & Ideate
New On-Page Navigation
With insight from the data gathered above, I developed a wireframe for the small appliances category page, featuring new ways for customers to navigate to products.
1. Shop by category as the primary navigation, as customer's information-seeking behavior, is heavily product based. This will align with the global flyout menu and side navigation categories highlighted in red to build consistency and reinforce customer's familiarity with our product taxonomy.
2. Search query data shows that customers are interested in small kitchen appliance brands. Secondary navigation will be a shop by brand, featuring the top searched brands. This will take customers to a collection page, where they can filter down by category.
3. Our target audience may be looking for new ways to cook for the family or seek more guidance to what kitchen appliances can best suit their needs. This curated section will feature descriptive copy highlighting the customer goals, educating them about possible appliances that can fit their needs.
Design & Develop
I worked with a visual designer, copywriter, and digital merchandiser to design and implement the finalized core experiences of the new taxonomy as well as the on-page navigational elements.
Shop by Category
Shop by Brand
In our post-analysis, we used Adobe Analytics to check how the category was performing. We compared the categories that were affected by the redesign to the same time frame from the year before prior to the changes. Overall, we saw significant changes in a number of categories where the traffic to the category and % to product description page both increased, and average search volume declined, suggesting that the improvements we made to the experience successfully helped our customers get to the products that they wanted.
That being said, we noticed that engagement on the curated collections over 60 days was lower than expected compared to the other navigational elements on the page. This could be due to the placement in the information hierarchy of the page is low, or that the target demographic is seeking less guidance on what to shop for. There is an opportunity to explore this behavior as the assortment continues to expand, to potentially split up the primary navigation into sections based on the function of the kitchen appliances.