Why Data Analytics is Important for Retail Industry

Why Data Analytics is Important for Retail Industry

Nov 26, 2019

What propelled the need

A few years back, a New York-based fashion designing company was facing challenges in understanding the trends and changing preferences of the consumers. Keeping in mind the various factors like age preferences, color matching, geographies, buying tendencies, etc. it was difficult to be on the same page of making insightful decisions. Though, the data were readily available in ample amount, recognizing benefits from them was lacking. In this hyper-active era, the demand of customers keeps on resonating. Their likelihood of buying any product depends on several factors. Tracking & analyzing the changing mindsets is like carrying out the brain-mapping. These challenges blocked the path of success and hindered the organizational growth.

How Retail Analytics came to the rescue

With analytics, this fashion designing company started playing fairly with the data being available. They headed towards the social platform and co-joined their data with the public forums. They even carried out sentiment analysis and analyzed the customers conversations and comments. This way, they got the idea as to where the fashion is heading towards. They even revamped their marketing strategies through the right media and channels. Within a few days, the results were visible, and the organization was back on the track of expansion.

Improve your churn rate and customer engagement portfolio with the retail analytics solution.

Talking at the organizational level

The competitiveness at the enterprise level is posing an unconquerable challenge in the retail industry. To be among the best, organizational services should be lean focused and experience centric. The deployment of retail analytics accounts for the outcome-driven digital platforms in this omnichannel business scenario. Modernizing front-end deployments with personalized solution accounts for unparalleled customer 360-degree view. This improves customer engagement & ensures customer satisfaction. The retail analytics is “Analytics of Everything” for the retail industry.

Data is the crux

The growing customer preferences & constantly changing buying pattern is getting more evident nowadays. With e-commerce getting more intelligent, the market is getting more dynamic & online driven at the same time. The subscription-based services offered by the e-commerce giants allures customers. The vast number of orders placed across the globe generates zillions of data whose storage & management at granular level becomes a challenge. Also, gaining insights from these data is possible only when the robust & agile analytical tool is being put to work. The smarter the tool, the more tailored will be the digital experience. Plugging data sets to various marketing platforms helps sharpen the pricing strategy. This way, the organization gets a better idea of managing their finances efficiently. Confirming benefits to both customers & organizations is one of the marked outcomes of retail analytics.

Transforming retail experience

The analytics brings forth KPI dashboards which are the utmost example for digital signage. Along with campaign management, the personalization & recommendation service is also facilitated with smart tools. The customer delight is also taken care of with the adoption of retail analytics, as the placements of products are optimized in a better way. In a nutshell, the transition in the retail industry from the disparate system to the smart system will bring a paradigm shift, both in exposure & experience.

Conclusion

The retail Industry works mostly in siloes. Data gets generated in enormous quantity but mostly goes off track or remains as a non-performing asset. The success of an enterprise depends on how strategic its business moves are. Here, the data comes into the picture as it plays a pivotal role in determining future business outcomes. Data Analytics improves business performance and accounts for an omnichannel experience for its customers.


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