Data Insights - General Knowledge Flashcards

1
Q

The Fashion Cycle (4 steps)

A
  1. Introduction
    - New styles enter the market
    - Innovators here
  2. Growth
    - Trend gains popularity as they are adopted by more consumers and influencers
  3. Maturity
    - The style reaches peak acceptance
  4. Decline
    - Fashion begins to wane in popularity as newer trends emerge
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2
Q

Sociocultural influences on fashion trends

A
  • Art and music
  • Economic factors
  • Technological advancements
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3
Q

Global fashion: An interconnected phenomenon

A
  • Street style influencers
  • Digital Design tools
  • Global Trade Shows
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4
Q

The Rise of Fast Fashion - 4 aspects that have allowed this to occur

A
  1. Trend Identification
    - Rapid analysis of emerging styles from runways show, street fashion and social media
  2. Quick design
    - Streamlined design process to create trend aligned pieces in record time.
  3. Efficient Production
    - Flexible manufacturing systems that can quickly produce new cycles
  4. Global distribution
    - Advanced logistics to deliver products to stores worldwide within weeks
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5
Q

Forecasting Methodologies:
 (Quantitative Techniques):

List 3:

A
  • Historical sales data
  • Consumer behavior patterns
  • Market indicators
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6
Q

Time series analysis

A

examining historical sales data = predicts seasonal trends

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7
Q

Regression analysis

A

identifying relationships between variables = forecasts demands based on economic factors

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8
Q

Machine Learning

A

Using AI to analyze large data sets = identifies emerging microtrends from social media

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9
Q

 Qualitative Techniques: list 4

A
  1. Expert Panels – gathering insights from the industry.
  2. Scenario Planning – developing future scenarios based on social, technological, and economic trends to anticipate shifts.
  3. Cultural Observation – immersing in various cultural scenes to identify emerging styles and subcultures that may influence mainstream fashion.
  4. Trend Mapping – creating visual representations of trend evolution and interconnections to forecast future style directions.
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10
Q

Expert Panels

A

gathering insights from the industry.

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11
Q

Scenario Planning

A

developing future scenarios based on social, technological, and economic trends to anticipate shifts.

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12
Q

Cultural Observation

A

immersing in various cultural scenes to identify emerging styles and subcultures that may influence mainstream fashion.

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13
Q

Trend mapping

A

creating visual representations of trend evolution and interconnections to forecast future style directions.

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14
Q

The Role of Fashion Industry Professionals: 4

A
  1. Developers (designers and product develops)
  2. Gatekeepers (fashion editors, buyers, retailers)
  3. Promoters (marketers, influencers, and media outlets)
  4. Analytics (trend forecasters and data scientists provide insights)
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15
Q

Forecasting Companies and Their Services:

A
  • Trend Reports
  • Consultancy Services
  • Digital Platforms (online data bases and tools)
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16
Q

Sustainability and Social Responsibility:

A
  • Ethical Production
  • Circular Fashion
  • Conscious Consumption
17
Q

The Future of Fashion Forecasting:

A
  • AI and Machine Learning
  • Blockchain Integration
  • Virtual and Augmented Reality
  • Personalized Forecasting
18
Q

How many product launches fail?

A

Statistic: More than half of new products fail

19
Q

Price optimization

A

the practice of analysing customer and market data to find the most optimal price point for a product or service.

20
Q

Price Elasticity

A

a measure of the relationship between a change in the quantity demanded for a particular good and a change in price.

21
Q

Artificial intelligence

A

Artificial intelligence (AI) is the ability of a computer to perform tasks that usually require human intelligence

22
Q

4 types of Data Analytics and explain them

A
  1. Descriptive – reports
  2. Diagnostic – examining and analyzing data discovery and future state needs
  3. Predictive – artificial intelligence (AI) driven data tools to predict outcomes
  4. Prescriptive – predicts outcomes and identifies solutions/ actions
23
Q

Predictive & Prescriptive Analytics

A
  1. Provides an additional set of qualitative date
  2. Can help provide information about what the customer is thinking in real time
  3. Eliminations having to only look at Last Year or gut instinct to make decisions about the future.
24
Q

First Insight

A

is a leading software provider specializing in real-time analytics that help retailers and manufacturers make smarter merchandising, pricing and marketing decisions