Client: American Eagle Outfitters
How to bring down the gap between online and in-store shopping?
How to help the younger generation discover their personal style?
American Eagle Outfitter, Inc. (AEO) is an American lifestyle clothing and accessories retailer, headquartered in the Southside Works Neighborhood of Pittsburgh, PA. For the MHCI Capstone project, we worked with AEO together to design a seamless omni-channel shopping experience for the younger generation. Currently the project is still under progress, stay tuned in August for our final design!
As for now, we have designed an omni-channel shopping experience concept to help the younger generation to explore and discover their personal style. We design an online inspiration board powered by machine learning for the users to explore and then bring those data to the in-store shopping experience which creates an overall omni-channel personal capsule.
Omni-channel implies integration and orchestration of channels such that the experience of engaging across all the channels someone chooses to use is as, or even more, efficient or pleasant than using single channels in isolation.
For clothes shopping specifically the two channels are online and in-store, how to bring down the gap between them to create a seamless experience for the users?
Generation Z (Gen Z), the demographic cohort after the Millennial born in mid-1990s to mid-2000s, is AEO's target customer. As a generation that grew up with emerging technologies and social media, Gen Z-ers tend to express themselves more, embrace technology and expect convenience & constant connectivity.
Screenshots ended up being forgotten in camera rolls or conversations
People seek inspiration for clothes everywhere either from internet or even on the street. One example is that people take screenshot when running into style they like on social media like Instagram. However, those screenshots will not usually lead to actual purchase, instead, they ended up being forgotten in camera roll or text messages to friends.
Therefore, one of the challenges is that how to transfer those data to actionable purchase behavior, and in what way would user feel more comfortable and natural to do that?
People shop in-store like they have never shopped online before
The way people shop brick and mortar stores has not changed for ages. People still shop in-store like they have never shopped online before, all those data, like and dislikes, wishlist items, sale information from online shopping have all gone silo. When we asked users do they want to see those data in-store, they all said "Yes."
The need of more time to make decision in the store is not supported
From our user research, people expressed the need of more time to make decisions on certain items, either because they are waiting for friends' response, or for paychecks, or just simply want more time to think through.
However, this need is often times neglected. People are having a hard time remembering to buy things they wanted to make purchase decision later in-store because of lacking of technology support.
Style can be the first priority when shopping online
Another finding we had was people's priority changes when channel changes.
Taking style and budget as example, people care more about style other than budget when shopping online. The price is more accessible, and they can spend as much time as they want since this is more of an individual exploration activity, and also of course there are more brands and options online. When shopping in-store, the price is hard to find and also shopping with others makes the experience more social and people are more aware of how much they are spending.
People are willing to spend time on style exploration
Surprisingly, when it comes to style exploration, the younger generation seems to be pretty willing to spend time on it. No matter how many "quiz" or other activity we asked our participants to accomplish online, none of them is "too much effort" for them as long as the result is accurate. For them it is a fun activity and relaxation.
After we explored the Gen Z's shopping behavior, we started to wonder, whether uniqueness of the style the ultimate goal for them? Do they want to be the trend setter and be the first one to discover a style? Or the opposite - they are afraid of being different and judged?
The baseline vs. uniqueness
One big insight we learned from testing and interviewing with Gen Z is that, they want their style to be safe but they also want to add some unique elements that can represent themselves.
The need of being safe and having this baseline is to protect themselves from judgements in order to fit in their circle or social community, and the need of being unique is that they also don't want to look the same as other people and also they want their style to speak for their personal identity. The question became, how can we help the users to add personal touch into their style?
Passive Shopping vs. Active Shopping
Currently, there is a huge part of style exploration that is happening in passive shopping: brand advertisement, life inspiration from images, see someone wearing items that I like etc. These are all data that can help people discover their own style, but how can we bring those data from passive shopping to active shopping and increase the action of purchase?
"I want things to be taken care of"
When talking about shopping, the word "effort" kept popping out. Though it is obvious that people definitely desire things to be less effort, but we did not realize it is this important when it comes procedural steps. This also ties back the key word, "seamless", which means that the final concept we design has to provide a seamless, effortless experience for the user, and also in the same time, personal enough so they would willing to spend time on it.
Creating a personal experience for styling
In order to connect online and in-store experience seamlessly to help user define and discover their style, we decided to create a personal capsule where the user can add personal touch to their style, the algorithm will generate a collection of clothes based on the content that user added and provide personal styling service in the stores.
We designed an online inspiration board where user can add images, music etc. they like, and the system will generate recommended outfit based on the content. User can also request a try-on session either through mailing or in-store. These data will be brought to the in-store shopping experience and help people navigate and make purchase decision.
Testing with Gen Z and iterating on final design
Currently we are starting prototyping and usability testing with our target users: Gen Z. We have already recruited around 25 teenagers and some college students to participate in our testing session and we will then iterate on our design based on the feedback they give us.
Wrapping up in August, STAY TUNED!
This project will be wrapping up in August, by that time we will be presenting our design to the MHCI community and our clients from AEO, STAY TUNED!