A Game Changer for Fashion Retail By Cioreview
The fashion sector utilizes multiple platforms, generating a significant volume of data every second. This article provides insights into the different sources of retail data in fashion retail.
Fremont, CA: The fashion industry functions across multiple platforms, resulting in a significant influx of data every second. This data holds the potential to offer profound insights into customer behavior and experiences, inventory optimization, pricing strategies, merchandise assortment planning, and numerous other aspects. As a result, data analytics has become an indispensable requirement for retailers and businesses.
Consumer market preferences are constantly changing and evolving due to various factors. These factors include trends, societal changes, technological advancements, economic conditions, individual experiences, marketing campaigns, pricing strategies, the impact of e-commerce, payment methods, product accessibility and availability, experiential marketing, environmental and sustainability concerns, generational differences, and other demographic factors. As these factors shift over time, the market becomes volatile and dynamic, directly influencing consumer preferences and choices. To understand and adapt to these shifts, data analysis is crucial in retail management and predicting the industry’s future. This analysis can be conducted using various sources such as e-commerce platforms, social media, physical stores, and third-party reports.
Data analytics in the retail industry involves examining various retail data, including sales, inventory, foot traffic, and pricing. This analysis aims to extract valuable insights regarding product trends, customer purchasing behavior, sales patterns, footfall trends, inventory management, and pricing impacts. By conducting such analysis, retailers can make informed predictions, create effective buying strategies, identify current and future trends, optimize inventory levels, implement discounts and sales strategies, manage open-to-buy (OTB), and ultimately make profitable business decisions.
Sources of Data
Retail data may be acquired from a variety of sources, such as:
Point of Sale (POS) Data:
The point of sale system (POS) offers transactional details for each purchase, including the items bought, quantities, prices, and returns. This data allows for a better understanding of the average size of each transaction (both in terms of value and volume), customer buying habits, best-selling products, and customer preferences. It enables retailers to monitor their inventory levels in real time, reducing instances of running out of stock or having excess inventory. By examining historical sales data, businesses can predict demand, recognize popular trends, and identify slow-moving items. Furthermore, it provides crucial insights into individual customer purchasing behaviors, which can be utilized to tailor marketing strategies for each customer, such as offering special promotions on birthdays and anniversaries. Ultimately, this enhances the overall customer experience and strengthens the relationship between the customer and the retailer.
Web and Mobile Analytics Data:
Web and mobile analytics tools, like Google Analytics, Mixpanel, and Adobe Analytics, are incorporated into websites and mobile applications to gather pertinent information. The information collected may encompass page views, clicks, navigation routes, session length, device details, location, etc. This data aids in monitoring conversions, such as finalized purchases, registrations, form submissions, abandoned carts, landing page visits, and time duration on each page. Conversion tracking enables the assessment of digital marketing campaigns’ effectiveness and the performance of websites and applications. The data can be utilized to identify customer groups and assist in customer segmentation, targeting, and positioning of products or brands.
