AEO Service Innovation

AEO Trend Tagger — Digital/Physical Service Innovation


user research
data analysis
ui/ux design
service blueprint

Nathalie Rayter
Se Eun Park
Sujay Desai
Wenjie Li

Trend Tagger is a bundling service based that rewards users for providing outfit ideas and offers style recommendation for less confident shoppers. This service aims to increase confidence and wallet share between the customers and AEO.

I worked closely to develop the details of our service and adapt it based on insights we received from our stakeholders and user tests.




Julia Costa and Matthew Nichelson of the AEO Technology Innovation team kicked off the project with a short presentation on the current state of AEO and where they had been focusing on innovation. They recommended looking into the areas of associate enablement, returns & exchanges, in-store personalization, and omni-channel fulfillment as a starting point.

We began the process by brainstorming innovations that would fit into each category.


Through discussion, we noticed that while some categories, such as returns and exchanges, generated a lot of ideas, they were less revolutionary than others. There also seemed to be some overlap in certain areas, such as in-store personalization and associate enablement. In the end, we decided that we wanted to pursue the issue of in-store personalization (or lack of).




For the survey, we chose to gather information about people’s general in-store shopping habits that were not AEO specific. We wanted to measure perceptions of shopping, as well as identify pain points in the in-person shopping experience.

We collected around 100 responses from folks within our networks by sharing the survey via email and social media. We received responses from people from 15 to 41+ and people living in both suburban and urban areas.

Key Insights:

  • many people are uninterested in speaking with associates and often find them to be annoying

  • a lot of responses indicated the need for style advice or inspiration.




We developed a stakeholder map and concept map focusing on the in-store experience of AEO. This helped us to identify the different actors and pain points of the customer’s journey which gave us more insights to the connections between the customers and the business itself.




For our competitive analysis, we researched nine of American Eagle’s top competitors. When looking for information, we narrowed our search down to understanding target demographics, top sellers, store layouts, use of website and app, methods of in-store personalization, fitting room environment, average product prices, and overall gross profits. We thought that these parameters were important to understand how competitors appeal to their target customers through their physical stores. These pieces of information also helped us to understand the differences between AEO’s and competitors’ methods of personalizing through technology and store layout.


AEO has multiple competitors in the retail industry, almost all of whom are trying to enhance in-store personalization. This is occurring through technology as well as through methods to bond and create a relationship with the target demographic.

Every competitor has their own website and app, which they’re trying to use to extract consumer data and use it to match their store experience to what customers want. Every competitor is on social media and uses influencers to promote their brand but those methods cannot target individual customers’ desires. 




For our service blueprint, we laid our focus on in-store customer experience. The blueprint begins from how customers gain motivation of going to an AEO brick-and-mortar store and ends when they leave the store. From the blueprint, we’re able to see how physical evidence and employee interactions affect customer experience at each phase of the service. An interesting finding is that customer’s in-store journey is split into multiple branches. For example, they may leave the store at any point. The reason that drives customer’s prompt decision is an interesting point to concentrate in our future research.




From our research, we began storyboarding different ideas to “speed date” with. We created around five storyboards based on the categories of preparing associates, displaying more style options, increasing associates’ style credibility, socially supported shopping, and utilizing customer meta-data in store. We gauged audience reaction and feedback and used that to refine and narrow down our potential solution.




After creating storyboards, we ran through each one with around twelve of our peers as well as each other to gauge initial feedback. Through this process, we ended up with a few takeaways which are listed below:

  • Customers are outfit-motivated and want versatility from their purchases.

  • Personalized recommendations are good, but easily verge on being creepy and inefficient!

  • Bundled deals are appealing, but it depends on what is in the bundle.

  • “I feel like there are some items that look really cute, but I have no idea what I would wear it with and I would be more inclined to buy if I knew.”

  • Hard-to-style items become more desirable when customers know how to wear them

Rather than come up with completely new ideas, we decided to combine the successful parts of each storyboard to create a modified innovation approach and visualized it through preferred future storyboards.




We decided to stage a user enactment of our idea that would allow us to gauge interest and effectiveness of our idea. To accurately do this, we began working on wireframes for the application, highlighting all of the key points of the customer journey. This was meant to showcase the process of suggesting outfits to be matched in store.




We decided to simulate a shopping experience using the initial prototypes as a way to introduce our concept. We had three groups of participants enter the space and peruse the clothing on the hangers as if it were in a real store with minimal instruction.


Shoppers will walk into a “store” where they will encounter a clothing display. The clothing will be tagged with regular American Eagle tags as well as a Trend Tagger tag that indicates that the item can be bought at a discount when purchased in tandem with another item. The display also carries signage about AE Trend Tagger, a profile of the customer “stylist,” and a URL with more information about the program.

Shoppers will approach the display and go shopping. Researchers playing the role of shopping associates will be available to greet shoppers and answer questions. When they’re ready to check out, they’ll approach a mock-register with their merchandise.

Research Questions

  • How interested will shoppers be in this concept?

  • How might shoppers share their styles with their social networks to garner votes?

  • What recognition might shoppers want if their styles win?




We presented this concept to representatives from our client, American Eagle, on November 12. We received largely positive feedback, as well as direction to think about streamlining implementation.




From here, we recognized that we needed to further define aspects of our service. We decided to discuss how the service would be implemented and work together given the multiple touch points and experiences, while also editing our application and physical tags based on feedback from our user enactment sessions.

We started working on the design of the physical tags. Participants of our user enactments expressed concerns with the name and handle of the winning stylists displayed on the tags, so we decided to forego them. Additionally, we decided to increase emphasis on the name of the Trend Tagger program as well as the bundle discount.




For the final client presentation, I created more simplified storyboards for the future we were proposing, given the time constraints of the presentation period. We wanted to focus on the most basic aspects and functions of the service, so as to introduce it seamlessly.




Trend Tagger involves AE customers in the co-creation of value by inviting them to style upcoming trends, incorporating social voting and rewards, and bundling merchandise in-store.

The Trend Tagger program invites AEO customers to style upcoming, on-trend items with other American Eagle merchandise through the website and the mobile app. Customer stylists receive points in AE’s existing loyalty program by submitting their outfits for community voting, and the three customers who receive the most votes win the styled merchandise and 10,000 AEO Connected points as a reward.

In-store, the items in the winning Trend Tagger style are displayed together with recognition of the customer stylist. The display is accompanied by signage explaining the Trend Tagger program, and individual items are marked with “match” tags that indicate they will be discounted if purchased in a bundle.

Trend Tagger yields greater in-store wallet-share for American Eagle by incentivizing customers to purchase different items; rich customer data for AE from both new AEO Connected sign-ups and co-created styles; and greater confidence for customers from socially-affirmed styling. It also lays a strong foundation of future, sustainable digital-physical shopping experiences.




Through this project, I gained valuable experience in experimenting with different research methods.