TWEED Reimagined

RETAIL

So, what shops?

The Goal: FIND WHICH SHOPS WILL WORK!

The Masterplan

1. Go to Tweed Airport and Conduct a Survey

2. Set up a Timelapse Camera at the Exit

3. Record for 30 minutes + Sensor Faces

4. Manually capture still images of each person

5. Reverse Image Search (AI) outfits to find clothing brands

6. Populate brands into a spreadsheet

7. Use a python-based Data Analysis program to find the most common brands

8. Propose Top 3 Brands as Retail Stores

YUCG Tweed Fashion Data Spreadsheet

Negative sentiments reconfirmed regarding Retail/Food!

⬅️ Verbal Survey with employees/travelers. Preferred to go in person and talk to workers vs corporate because workers are there EVERYday.

YUCG TWEED AIRPORT FASHION DATA

⬅️ Slide Deck of ~80 people of Tweed Airport with the brands of each item of clothing

Process: Stills taken from 30 minute video of each person

⬅️ Demonstration of how brands were found for each outfit

Google AI Reverse Image Search Used to manually find each item

YUCG Tweed Fashion Data Spreadsheet

⬅️ Brand Data from slidedeck populated into a spreadsheet used for Data Analysis

Brand Categories Represented:

Athletic/Sportswear: Nike, Lululemon, Adidas, Columbia, Gymshark, Reebok

Fast Fashion: H&M, Zara, Shein, ASOS

Department Stores: Walmart, Target, Nordstrom

Mid-range: GAP, Banana Republic, Calvin Klein

Specialty: Aritzia, Pacsun, Urban Outfitters

Python Machine Learning Model used to find most common brands in the dataset!

Nike, Lululemon, and ASOS are the most popular brands!

Conclusion Made from the following Statistics:

20+% of clothing is from Nike

12% of clothing is from Lululemon and ASOS

Fun Finding: Hats are the second most popular accessory after jewelry

Final Recommendation:

Fund Retail Stores that contain the above brands and perhaps a hat/jewelry mini stall

30 minute video of airport exit not included because of safety reasons. Stills of people from the video are censored and included in the slide deck.

Google Sites

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