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SmartData Collective > Analytics > Predictive Analytics > Top 5 Analytics trends in Fashion Retail
AnalyticsPredictive AnalyticsSocial Data

Top 5 Analytics trends in Fashion Retail

ajithnayar
ajithnayar
5 Min Read
analytics trends
Shutterstock Licensed Photo - 2086008427 | fizkes
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Technology has enriched the overall customer experience. As a result, today’s leading fashion houses are looking at several ways to utilize emerging analytical technologies in fashion retail today. 

Contents
Digital Marketing and Social Media AnalyticsCross-selling and upselling through PersonalizationPredicting future trends of fashion stylesManaging seasonal fluctuationsIoT devices in the fitness segment

Let’s look at some of the ways this is happening today.

Digital Marketing and Social Media Analytics

Digital marketing analytics expenses increased by 60% in 2015 as branding and advertising businesses boomed. Social media and online advertising on mobile will continue to grow as the integration of the offline and online customer experience is on the rise. This, in turn, has increased consumer brands’ ability to digitally influence customers and digitally empowered customers’ ability to influence brand image and value.

Cross-selling and upselling through Personalization

Owing to advancements in technology combined with the avalanche of data available today, enterprises across industries are leveraging inexpensive technologies such as Hadoop to analyze huge amounts of customer data, understand patterns and subsequently personalize their offers to their customers. This, in turn, helps them out-think and out-do the competition. “More data storytelling equals more engagement”.

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A leading Indian retailer boosted category growth by 50% with tailored campaigns based on affinity analysis, cross promotion between categories like kids, baby world, and toys.

Strategic customer segmentation enabled 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.

Predicting future trends of fashion styles

Analytics is helping retailers aggregate fashion trends and sales information from a wide variety of sources around the globe—from retail sites, social media, designer runway reports, and blogs covering trends—and making it accessible 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, users now have access to more context for their data, which ultimately leads to more insights and better decisions.

One company that has effectively utilized these analytics trends in fashion retail is Nihal Fashions, by implementing personalized shopping experiences for their customers. 

Managing seasonal fluctuations

Fashion retailers often struggle to quickly address seasonal fluctuations and capitalize on unexpected opportunities. A lot of competitive advantage is to be gained in innovations that help retailers get the best bang for their buck while maintaining customer loyalty.

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.

IoT devices in the fitness segment

While health and wellness have always been popular, it has become a trendy lifestyle choice for many over the past few years, driven by wearable technology.

Smart technology is embedded into clothing, sportswear shoes, and trackers. The large amount of information obtained from these connected sensors when combined with contextual data can result in highly useful and interesting insights for consumers.

Tracking the number of steps taken each day and heart rate, monitoring blood glucose levels, telemetry, and weight are just a few examples of data that consumers can obtain from their wearable devices. Consumers have started responding to such performance feedback and analytics from wearable fitness devices if that’ll help them lead an active and healthy lifestyle. By using beacons and real-time analytics, retailers can create innovative engagement campaigns to further enhance the lifestyle choices that their consumers make, boosting loyalty as a result.

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