Best Buy's AI-Assisted Self-Diagnosis is a fully responsive, concept-to-release microsite embedded in BestBuy.com to help customers self-assess hardware and software issues with the power of Geek Squad's twenty-five years of call transcripts and troubleshooting models.
The application leverages three facets of artificial intelligence:The conversational system, puts customers in control, results in greater issue resolution and satisfaction—but the primary goal was to reduce Best Buy Customer Service's Average Handle Time.
The MVP was only targeted laptops, but the initial decision tree, UI and conversational elements paved the way for all hardware and software products to be triaged through the application.
All participants in the unmoderated study quickly identified the rationale behind the application; reduce call volume (top answer—surprisingly), to save customers' time, and encourage self-service. Most participants were not aware that Best Buy did computer repair (which surprised us all on the Services team, both marketing and tech).
The reactions among test users were largely positive. The length of the interaction was considered appropriate, had logically sequenced stages and was easy to complete. However, some participants found the outcomes predictable or "surface level”, and expected more in the way of pricing and timing options. Overall, the majority found it useful, and gave them a base understanding of their issue without setting foot in a store.
About 80% of users who tested it said they would use the feature in real-life—a win win for Best Buy and the customer experience.
Participants were screened for having a computer or device issue in the past six months, so we could leverage a "true to life" scenario within our test.
At the time, the product managers on this product had limited vision about what this self-diagnosis could do and understand. They were very MVP-focused and if it reduced any call volume it'd have been considered a win for them. Anything outside of that was seen as scope creep. It was early in my UX experience, but found the lack of "big picture" as well as the disinterest in details from the product managers very frustrating.
Unfortunately, it's a very nuanced process to understanding the variety and complexity of users' personal taxonomy and goals. Even more complex, but highly valuable to the customer experience— we missed the opportunity to help the customer with their decision to repair or replace (for example, give the customer their current device's value, Best Buy's trade-in value and show them pricing on new devices.) Attempting to discuss ideas like these with the product managers were immediately stifled and met with hostility.
However, this was precursor to the Best Buy intelligent chat, and this triage application didn't not have the flexibility nor logistics to use natural language processing. It did eventually, with a newly-formed CX team's guidance, roll into a triage model currently used for all Best Buy-supported products.
The Best Buy Partner Portal is a web-based application that allows vendor partners (like distributors, resellers service providers and other strategic partners) access to product registration, marketing resources, pricing and sales tools.
While we found Sears and Best Buy very closely rated in ease of use, and Best Buy had a slight edge in user confidence within the scheduling component. Both Sears and Best Buy services were very difficult to find, whereas no test subjects were able to find Amazon's services component.
As expected, the HelloTech experience was superior, given their only task for users was to estimate and schedule. We also found hesitation across all platforms when it came to taxonomy, as well frustration when there was a need to create an account to get an estimate or schedule a repair.