When the weather gets hot in the summer, Best Buy is a top destination customers go to when looking to buy an air conditioner for their home. However, buying an air conditioner optimal for the space you live in can be a complicated process. I led the strategy and design of the web category to enhance the experience for customers shopping for an air conditioner. Through understanding the pains and goals of our users, my team and I were able to make it easier for customers to make an informed purchase online.

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.

My Role

I lead the research and strategy for the category experience and collaborated with designers and a copywriter for the visual design and copy for the final experience.

The Opportunity

During the summer season, there is a significant spike in traffic to the Best Buy website from customers looking to buy an air conditioner. We saw an opportunity to help customers understand the information that they need to know quickly so they can find the right product for their home with confidence.

  • Help customers get to the products that meet their needs

  • Make it quick and easy for customers to make an informed purchase decision online

Key Performance Indicators
  • Increase % to a product description page

  • Decrease exit rate on product listing page

  • Increase direct to home revenue


Research & Discover

During the research phase, I conducted stakeholder interviews with our buyers to gain insight into the assortment and inventory plan, as well as to gather information about air conditioner buying considerations. I worked with the team to develop a customer journey map and conducted a competitive analysis against other sites and tech blogs to identify opportunities for our website.

Stakeholder Interviews

I interviewed our buyers who oversee the air conditioning category to understand how much inventory was allocated towards the different products that we carry, and also information about store performance and their goals for the season. Being subject matter experts in the category, they were able to highlight some top considerations about air conditioners that would impact a customer's purchase decision and competitors in the market.

Customer Journey Map

The team and I visualized the path of a customer purchasing an air conditioner on a journey map to better understand the goals and pain points of their experience.

We approached the research in two ways. First, we conducted desk research by reading buying guides such as Consumer Reports, to get a better understanding of the common scenarios and features people were likely to look for when purchasing an air conditioner.


We also talked to customers by interviewing participants to ask them questions about their experience with Best Buy under a few different conditions. 

  1. Recently bought an air conditioner at the Best Buy Store (3 participants)

  2. Recently ordered an air conditioner online from Best Buy (3 participants)

  3. Thinking about buying an air conditioner this summer (3 participants)


For groups 2 and 3, we had participants do a cognitive walk-through of the website. Our goal was to understand any usability issues or pain points in being able to add the right product to their cart and check-out. 


Through an affinity diagram, I was able to consolidate their experiences and map them to the customer journey and extract the key insights.

1. Customers who are interested in buying an air conditioner can have varying levels of knowledge and experience.

2. Best Buy could be the first destination that a customer comes to look for an air conditioner.

3. The website lacked any educational content to help customers understand the information they need.

4. The most important feature considerations for an air conditioner are cooling capacity, noise level, and energy efficiency.

5. The facets we have to help customers narrow down their choices were sparse and used unfamiliar terminology.

Competitive Analysis

Next, I evaluated the current experience of our website for air conditioners by completing an audit on informational content, facets, and navigation. After establishing a baseline, I was able to conduct a competitive analysis to compare our experience to other multi-retailer websites. These websites included Home Depot, Canadian Tire, Cool Blue, Lowes, and Walmart.

Opportunity areas were we lacked, that competitors we stronger in:

1. Product Specific Facets & Filters

2. Educational on Page Navigation

3. Educational Blog Content

Define & Ideate

Taking a look at our findings from the research phase, I defined the major problems and strategized tangible ways of how we can solve them in collaboration with my team.

Taking the Guesswork Out of Cooling Capacity

A critical part of buying an air conditioner is knowing how much space it has the ability to cool, determine by British Thermal Units. Our existing website did an ineffective job of allowing customers to understand what cooling capacity is or how it needs to be calculated, relying mainly on customers to do their own research away from our site. We want to be in service to our customers by taking the guesswork out of how to properly cool their space, just like how our Blue Shirts do in the stores. In our research, we came across buying guides that used infographics to help explain how cooling capacity works. This idea of using a visual guide to help customers picture the rooms of their home easily, along with including descriptive copy inspired the Shop by Room Size navigation. Through the use of an infographic, were able to apply the usability heuristic recognition over recall and with the descriptive labeling we applied a match between system and the real world by speaking the customer's language.

To build these navigational elements, I started by determining what the optimal ranges would be for our customers to shop by room size through an article online explaining how to properly size an air conditioner. From this, I calculated how many BTUs were needed to cool per square footage of space, plus 600 BTUs for each additional person in the room. Therefore, larger rooms such as living rooms that may hold more people, would need to account for a larger cooling capacity. Then, I converted BTUs to square feet by using the official EnergySTAR conversion chart. Finally, I validated that the established ranges fell within Architecture Canada’s guideline for standard room sizes for each room type to create to the concept of Shop by Room Size.

Guerrilla Testing

To validate and finalize the descriptive labeling for the Shop by Room Size experience, I conducted a moderated, balanced preference test on 6 participants planning to buy an air conditioner this summer. The goal of this test was the understand what type of descriptive labeling was most useful to users and make them feel the most confident that their choice would lead them to the right products.

1. Not all users knew the square footage of their space.

2. Users who knew their square footage felt less confident in navigating using room names due to its subjectivity.

3. A combined option (room then square footage) was the most useful for all users.

Communicating Noise Level in a More Relatable Way

Another major problem customers have during the hot summer is sleeping. That’s why it’s not uncommon for customers to be looking for a quiet air conditioner. Looking at insights from our competitive analysis, most competitor sites mention noise level as a way to filter search results, however, none of them effectively explain how loud the air conditioner actually will be. For example, Home Depot uses ambiguous terms like “quiet” and “standard” but don't have a baseline for customers to compare or relate to. 


To avoid falling into the same hole, I looked at different ways in which decibels were explained, through online resources, government websites, discussion forums and more. I noticed that many of these resources used scales and compared decibels to sounds one might hear in real life, however, they forced users to recall noises through memory.

I worked with a copywriter to explore options, for example, “light rain”, “a babbling brook” and “a running river“, but it could be hard to imagine or remember what these specific noises sounded like. Then we came up with an idea as we were having a conversation with each other. We noticed how the volume of our voices would change depending on the environment we were working in. We could prompt customers to replicate the noise level of the air conditioner with additional copy describing the volume of their own voice by using "a whisper", "a hushed tone" and "a conversation". Again, we applied the usability heuristic match between system and the real world by using familiar terms instead of decibels. Furthermore, we applied the usability heuristic of recognition over recall by prompting customers to leverage their own voice to understand the volume of how loud an air conditioner can be.

Design & Develop

After defining the core problems and ideating on solutions, I worked with a visual designer to design and implement the finalized core experiences.

Shop by Room Navigation

A visual guide to help customers choose an air conditioner with the right cooling capacity.

Visually, we were constrained around designing an image to fit within certain parameters. Because of this, any intricate details used to define each room would be lost, therefore, we came up with a simple iconography highlighting the coverage area with a shade of light blue. We also considered listing more than one room name, for example, “a bedroom, office or den”, however, the readability of the labels became difficult, especially on the mobile view.

Noise Level Facet

Descriptive labeling to make the noise level of an air conditioner more relatable.

To improve the readability of the filters, we moved the measurement (dB) to the facet title, instead of having it repeated throughout the options. We also paid close attention to the length of words to ensure that they did not flow over and impact the consistency established line by line. 


 In our post-analysis, we used Adobe Analytics to check how the category was performing. Overall, the improvements we made to the experience successfully helped our customers get to the products that they wanted. We saw a significant increase from % to PDP for customers who interacted with the Shop by Room navigation, and % exit rate also decreased by a significant amount.

1. 1 out of 3 users who landed on the page engaged with the Shop by Room feature. 

2. % to PDP increased by 17% for users who used the Shop by Room feature.

3. % Exit Rate decreased by 15% for users who used the Shop by Room feature.

Overall, these results support that we have successfully reached our KPIs to increase % to PDP and decrease the exit rate on these category pages. Although traffic was lower than the year prior due to the cooler weather, total online revenue was still strong, likely because, with the improved experience, customers can find products easier. The results for the Noise Level facet, unfortunately, are not showing up in Adobe Analytics to provide results, however, I will provide an update once the issue has been fixed.

Next Case Study

Improving the findability and discoverability of products by understanding the customer's mental model.

© 2019 Jackie Huang