Data plays a vital role in the fashion industry. It is used to drive decisions and strategy that generate sales, gain a better understanding of customers, and boost overall profit. Fashion designers and companies use data on a daily basis run a successful fashion business. However, the commonly perceived data used by fashion designers differ from the standard mathematical statistics commonly associated with the term “data”. Hence, data is not usually associated with the word fashion.
But, today’s top fashion houses are deploying several ways to use emerging analytical technologies in fashion retail today. Read on to understand how the modern fashion industry uses data.
Owing to progress in technology coupled with the huge amount of data available today, companies across industries are leveraging inexpensive technologies like Hadoop to analyze massive customer data, uncover patterns and use the insights to personalize their offers to their customers. This, in turn, helps them roll customer engagement and recommendation engine to grab market share.
A prominent Indian fashion retailer was able to increase category growth by 50% with highly targeted campaigns based on affinity analysis, cross-promotion between categories like kids, baby world and toys.
Accurate customer segmentation helped the business to drive a consistent marketing strategy across all concepts. Customer acquisition, retention campaigns, and maximization strategies enabled an increase in customer engagement and loyalty. By understanding customer attitudes, their purchase behavior and identifying fashion trends, they make smarter marketing decisions.
Sales in select categories grew by 92% with targeted retail campaigns, using models like Market Basket Analysis, K-Means, Churn and Propensity.
Not every eCommerce website has its presence in multiple countries, nor is every fashion site trying to sell everything under the sun to its customers. Many of them operate only in a single country, and sometimes even in specific cities. Gathering product information for many of these niche companies become difficult. Manually gathering product data related to thousands of products can prove to be difficult, time-consuming, costly and prone to errors when done using the help of manual-data gathering processes. That is why many of PromptCloud’s smaller retail partners who operate in a certain niche, use our eCommerce Product Data API in order to make sure that they have enough information in their product pages to look legitimate enough and also to draw in more customers.
Analytics is enabling retailers to aggregate fashion trends and sales information from a wide variety of sources around the globe—from fashion sites, web forums, designer runway reports, and blogs tracking fashion trends—and making it available in real-time – across menswear, women’s wear, children’s apparel, accessories, and beauty.
In addition to the ability to combine both internal and external data sources (e.g., web data), users now have access to more context for their data, which ultimately results in more insights and better decisions.
Fashion retailers often have difficulty with quickly address seasonal changes and react to unexpected opportunities. A lot of competitive advantage by pricing analysis is to be gained via web scraping and data collection from retail sites that help fashion stores get competitive advantage and drive sales.
With the right real-time insights, retailers can shorten seasonal cycles to meet changing customer preferences. This, in turn, can help negate surprises in customer demand and minimize losses.
By using analytics, fashion retailers can have more flexibility in their supply chain responsiveness. Greater precision with in-season control can also be enabled by using modern analytics solutions to derive insights and optimize the 5Ps – product, promotion, pricing, placement, and people.
From leading and famous fashion labels to the new brands, everyone is leveraging data analytics to gain crystal clear insights into current trends. From individual updates on distinctive trends to collective fashion choices, web crawling can provide access to critical and crucial information. Here’s how it helps!
With some of the market biggies and leading companies embracing data extraction, they have the opportunity to gain targeted information on individual products. Quite naturally, that will help them develop ideas about consumer preferences and consumption patterns.
Data analytics is the key to predicting consumer choices and preferences. Other than leading fashion labels, eCommerce sites have the perfect opportunity to know customer demands. Web crawling will help them identify customers’ browsing patterns thus comprehending their choices.
When it boils down to understanding processes in the fashion industry, it’s imperative to understand buyer sentiments. Intuition and emotions regulate buyers’ decisions and choices. Data analytics will help you delve deep into the nuances of these aspects.
These are some of the basic aspects associated with data analytics in the fashion industry. With the ever-increasing popularity of data extraction and web crawling, industry insiders are opting for a highly effective and dynamic analytics tool.