0. How to Collect and Utilize Data Without Coding for Fashion MDs, Designers, and Marketers
The fashion industry is rapidly advancing digitalization. With the significant growth of online commerce, various data such as products, prices, and reviews are being generated, providing insights for various roles in the fashion industry.
In this post, we will introduce ways for MDs, designers, and marketers to utilize review data and share how leading company S analyzes and collects review data to lead the domestic fashion industry.
Review data provides essential insights for MDs, designers, and marketers in their practical work. However, the process of collecting and analyzing data requires quite complex and technical knowledge. Especially if you lack knowledge of web scraping or web crawling, it can be a challenging task.
Review data serves as a direct channel for MDs, designers, and marketers to hear customers' stories and is used as foundational material for planning the next season. Let's explore how review data can be utilized for each role specifically.
1. Utilization for MDs
1.1. Product Lineup Decision
Through review data, you can identify which categories or styles of products are popular among customers.
For example, if there are many positive reviews about "sustainable fashion," you can plan a product lineup for the next season emphasizing sustainable materials and production processes.
1.2. Price Setting
By using expressions like "got a good deal at a low price," "price is reasonable," or "good value for money" in reviews, you can determine if the current price is appropriate.
On the other hand, if there are many opinions like "too expensive," adjustments to the price or the need to develop promotional strategies may be necessary.
1.3. Seasonal Trend Analysis
If keywords related to seasons or specific events (e.g., Christmas, summer vacation) frequently appear in reviews, you can plan how to structure products for the next season based on this information.
For example, if there are many positive reviews about "warmth" or "insulation" during the winter season, you may need to prepare more items emphasizing insulation.
2. Utilization for Designers
2.1. Consumer Preference Analysis
You can analyze frequently mentioned colors, patterns, materials, etc., in reviews.
For example, by checking feedback on "pastel tones" or "linen," you can incorporate them into the next collection.
2.2. Design Improvement
By identifying issues such as comfort, durability, materials, length, etc., mentioned in reviews, you can make modifications in actual design or production processes.
2.3. Target Setting for Collections
Extract information from reviews such as "women in their 20s," "college daughter," "office look," "special occasion," to more clearly define the target customer's persona and wearing occasions for the next collection.
3. Utilization for Marketers
3.1. Development of Promotion Strategies
By checking how often keywords related to "discounts" are mentioned in review data, you can adjust seasonal or event-specific discount strategies.
3.2. Product Positioning
Analyze which keywords such as "cuteness," "luxury," "comfort," "practicality" are commonly mentioned in reviews for specific products.
This information can help plan appropriate brand messages or advertising campaigns for those products.
3.3. Monitoring Consumer Responses
After launching new products or marketing campaigns, you can utilize review data to monitor their real-time effects.
You can monitor if the product positioning and marketing messages align with customer responses and how they are reflected in reviews.
4. How Leading Company S Analyzes and Utilizes Reviews to Lead the Domestic Fashion Industry
We have explored how key roles in the fashion industry can utilize review data. Now, let's look at a case study of leading company S, which requested online review data collection and analysis from Hashscraper, to understand what data is being focused on in the fashion industry and how they want it to be analyzed further.
- Collection of Review Data from Own and External Malls
S sells products from various brands on its own and external malls. Therefore, they wanted to collect and analyze review data from both their own and external malls.
Data from their own mall was obtained internally by S, while data from external malls was collected using web scraping methods.
The collected data included review ratings, distribution channels, review dates, review content, etc.
This structured data was used to perform sentiment analysis using AI natural language processing models and extract keywords mentioned by attribute categories.
Sentiment analysis involved breaking down individual reviews into sentences and analyzing the sentiment of each sentence.
Attribute categories such as color, material, fit, size, length, body, style were created for fashion item-related categories, and keyword analysis was conducted by matching keywords in the review content to the attribute categories.
Using these results, S provides MDs, designers, and marketers with various utilization methods mentioned earlier to apply in practice.
We have learned how data can be utilized by different roles in the fashion industry and how leading fashion companies analyze and utilize data.
5. If You Want to Experience It Yourself
In the Hashscraper dashboard, you can collect data from various online commerce sites like Naver Shopping, Musinsa, Coupang, 11th Street without knowing how to code.
Upon registration, you will receive free credits worth 50,000 won. Use these credits to collect the data you need!
If you require custom data solutions or want to inquire like S, feel free to leave a message. Experienced consultants will propose the most efficient solutions to solve your challenges.
Also, check out this article:
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