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Sonia Youmans & Kenwood Youmans
August 08, 2023
Happy Tuesday.✌️ Welcome to the 5th edition of our weekly newsletter!
We’re busy at the Magic Apparel Show in Vegas this week, but it’s business as usual at LA Fashion Insider.
Let’s get into the latest trends, strategies, and insights to help you stay on top. All in a 5-minute weekly read. Sign up here to continue to stay in the know.
In this week’s edition:
🌊 Deep Dive: Fashion Retail Analytics
👗 Fashion delivery in an hour
📱 More Shoppertainment insights
➕ Tips, trends, & tidbits
Quick Hits
Deep Dive 🌊
Fashion Retail Analytics: Using Data to Make Informed Buying Decision.
Introduction
The fashion industry, once ruled by intuition and artistic flair, is now embracing the scientific approach of data analytics. Fashion Retail Analytics is revolutionizing the way fashion businesses operate, allowing them to make informed buying decisions. This article delves into the various aspects of Fashion Retail Analytics, its applications, challenges, and how it's shaping the future of the fashion industry.
What Is Fashion Retail Analytics?
Fashion Retail Analytics involves the use of applications that draw data from various sources about fashion sales, styles, and trends. It helps businesses assess past performance and predict future outcomes, enabling them to make better decisions regarding collections, inventory levels, distribution channels, and promotions.
The Art and Science of Fashion Analytics
Key Components
Data Analytics: Examining datasets to draw conclusions and insights. It often incorporates artificial intelligence to search data without human intervention.
Fashion Analysis: Harnessing data to determine trends, customer preferences, inventory management, and future sales.
Fashion Analytics: Incorporating systems and processes for fashion analysis, including strategies, tactics, and technology. It often involves AI and machine learning.
Key Takeaways
Helps in stocking the right inventory at the right time.
Assists in targeting customers, forecasting trends, managing inventory, planning collections, and personalizing offerings.
Utilizes four principal types: descriptive, diagnostic, predictive, and prescriptive analytics.
Real-World Use Cases
Collection Planning and Design
Fashion analytics offers insights into the latest trends, allowing brands to create collections that appeal to the right shoppers. It guides buying decisions by offering nuanced insights into rising and falling trends in colors, style, fit, and accessories.
Inventory Management
By tracking product performance, businesses can plan their inventory accordingly, avoiding out-of-stock situations with popular items and excessive discounting of unsold goods.
Trend Forecasting
Fashion analytics provides insights into current and forthcoming trends, allowing businesses to create collections that resonate with shoppers' tastes.
Personalization
Fashion analytics enables businesses to personalize their collections and marketing messages, resulting in higher satisfaction and sales.
Challenges and Solutions
Challenges
Bad Data: Outdated or incorrect data can lead to wrong decisions.
Inconsistent Data Management: Different technology vendors may have varying codes, leading to incorrect interpretations.
Incomplete Data: A complete view of a shopper's data is crucial for rich insights.
Solutions
Standardizing Data Sources: Ensuring consistent naming conventions and methods of counting.
Utilizing Descriptive Analytics: Providing a clear picture of past performance.
Leveraging AI and Machine Learning: For predictive and prescriptive analytics.
FAQs
What is the role of a Fashion Analyst? Fashion analysts ensure that merchandisers have access to accurate data about trends and provide counsel on buying, selling, and pricing.
How can Fashion Brands Collect Data? Brands collect data from internal systems like POS, CRM, ERP, online shopping carts, loyalty programs, customer call logs, and online chat logs.
Why is Fashion Analytics Important? It provides tools to increase sales and profit by gaining insights into consumers' desires and behaviors, helping in quick decision-making.
Conclusion
Fashion Retail Analytics is not just a trend; it's a paradigm shift in the fashion industry. By blending art with science, it's enabling businesses to make informed buying decisions, forecast trends, manage inventory, and personalize offerings. The future of fashion is data-driven, and those who embrace this new era will undoubtedly lead the way. So, are you ready to put some science behind the art of fashion?
Additional Resources
[Big Data Analytics: Reshaping and systematizing the fashion industry](https://apparelresources.com/technology-news/retail-tech/big-data
Latest Finds From LA Fashion Insider
AI Fashion Style of the Week 🤖
Each week, our resident AI expert generates a fashion design with the help of artificial intelligence. If enough people like it, we may just make it.
Look for Trench Coats to be all the rage this Fall/Winter
Tip of the Week 😎
Most Popular Hashtags for Women's Fashion Boutiques
In the ever-evolving world of social media, hashtags play a vital role in promoting businesses, especially in the fashion industry. For women's fashion boutiques, utilizing the right hashtags can significantly boost visibility and engagement. Here's a look at some of the most popular hashtags that can be used:
Boutique Hashtags
#boutique: 44%
#fashion: 14%
#style: 6%
#boutiqueshopping: 6%
#shopping: 5%
#ootd: 4%
#shoplocal: 4%
#onlineshopping: 4%
#shopsmall: 3%
#shop: 3%
Women's Fashion Hashtags
#womenfashion: 41%
#fashion: 15%
#onlineshopping: 6%
#style: 6%
#women: 5%
#fashionstyle: 5%
#womenstyle: 5%
#fashionblogger: 4%
#fashionista: 4%
#instafashion: 4%
Boutiques Hashtags
#boutiques: 32%
#fashion: 11%
#boutique: 11%
#boutiqueshopping: 10%
#boutiquefashion: 7%
#boutiquestyle: 6%
#style: 5%
#shopping: 5%
#onlineshopping: 5%
#boutiqueclothing: 5%
Women's Wear Hashtags
#womenswear: 38%
#fashion: 15%
#womensfashion: 9%
#style: 7%
#ootd: 5%
#menswear: 5% (can be used to contrast)
#onlineshopping: 5%
#instafashion: 4%
#fashionblogger: 4%
#womenstyle: 4%
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