Application of Data Analytics in the Fashion Industry

Transcript

1. APPLICATION OF DATA ANALYTICS IN THE FASHION INDUSTRY FASHION INDUSTRY
2. INTRODUCTION INTRODUCTION
3. The fashion industry is an ever changing and highly competitive industry. Data science and analytics can aid businesses in solving issues that arise because of the dynamic nature of the industry.
4. SOURCES OF DATA SOURCES OF DATA
5. 1 3 2 SOCIAL MEDIA HISTORICAL DATA WIFI SIGNALS OF CUSTOMERS Hashtags, engagement on posts, likes and so on provides insight-ridden data. Can be obtained from retailers to understand spending habits of customers. Patterns are tracked to see how often customers visit, which sections they visit and duration of visit to store.
6. SOME TOOLS THAT CAN BE USED SOME TOOLS THAT CAN BE USED
7. 1 2 3 NATURAL LANGUAGE PROCESSING DATA MINING PREDICTIVE ALGORITHMS It is the branch of Artificial Intelligence that gives computers the ability to understand text in a similar way to human beings. Data mining is the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. Uses historical data to predict future events.
8. HOW TO LEVERAGE DATA HOW TO LEVERAGE DATA ANALYTICS ANALYTICS
9. TO AID IN DECISIONS SUCH AS 1 3 2 4 PRICING SUSTAINABILITY COLOUR CREATING PRODUCT CATEGORIES Big data can be used to price products using average previous sales data and that of competing brands. By predicting fashion trends and demand through the use of ML forecast algorithms, businesses can reduce wastage due to excess production. Colour preferences can be mined from sales and returns data. Big data can be leveraged to - decide new product categories and the continuation of existing product lines.
10. TO AID IN DECISIONS SUCH AS 5 6 7 TREND ANALYSIS RUNWAY TO RETAIL MARKETING CAMPAIGNS Sentiment analysis can be used on social media to ascertain popular trends. Training algorithms can be used to transform runway pieces into retail pieces based on local tastes and preferences. Big data can be used to personalise marketing campaigns.
11. USE CASE USE CASE
12. Burberry is a British luxury fashion label. They launched "Customer 360" to achieve "Clienteling" to boost sales. Clienteling entails analysing customer information to offer personalised services and hence establish a more interactive relationship. How does Customer 360 work? - With customers' permission profiles of customers are built using RFID tags, based on garments that they try on. - Customers are also asked to share their shopping history, likes and dislikes. - All of this data is recorded and analysed on SAP HANA post which real time recommendations are given to the store employee who is equipped with a tablet. BURBERRY Customer 360 Customer 360 A Data Driven Shopping Experience A Data Driven Shopping Experience
13. CONCLUSION CONCLUSION
14. There is large potential for fashion brands to leverage analytics which could have a positive impact in reducing the industry's carbon footprint. Major fashion brands such as Burberry, Zara, H&M, Rent the Runway and Ralph Lauren to name a few have adopted data analytics and many more will follow in the near future.