Customer Analytics

Top 5 in-store retail analytics use cases

In this world of the hyper-competitive retail market, in-store analytics is gaining lots of traction. And for the obvious reasons: it helps the retailers to keep a close eye on their customers and offers much more valuable insights on store performance. Even better, all this data can be followed up with different actions.

So, here are the top 5 in-store retail analytics use cases:

  1. Understanding Customer Behaviours

Deeper, data-driven customer insights are much more critical to tackle the challenges like personalizing campaigns and improving customer conversion rates to increase revenue, avoiding and predicting customer churn, and lowering the customer acquisition costs. But the consumers in today’s world interact with the companies via multiple interaction points – stores, social media, mobile, eCommerce sites and much more. This dramatically increases the complexity and wide range of data types that you have to analyse and aggregate.

  1. In-Store Experience Tracking

In the past, merchandising was even considered as an art form, with no true way to measure some of the specific impacts of the merchandising decision. And as online market sales grew, a new trend emerged where the shoppers would perform their physical research on the products in-store and then purchase online at a later point of time.

  1. Better Promotions

Improving the conversion rates is much more essential in retail as online real estate for good continues to be flooded. With the help of targeted promotions and predictive analytics, it is possible for the retailers to uncover with products and offers are most popular, what is being signed up for and more. With the help of this data, they can continue to test and analyse some of the new ways to capture customer interest.

  1. Tracking the Customer Journey

In today’s’ scenario, customers are more empowered and connected than ever before. Using the channels like the social media platform, mobile and eCommerce, customers can access just about any kind of information in the seconds. This informs what they should buy, from where and at what price. Based on the information which is available to them, customers make the buying decisions and purchases whenever and wherever it is convenient for them.

  1. Operational and Supply Chain Improvements

With the help of retail analytics in the supply chain is one of the more recent ways, retailers are upping their game. The data can be sued for everything from the product tracking to improved quality, better forecasting and real-time inventory management. It also helps to speed up the delivery of goods; something consumers have come to expect. Making much better decisions at this level of operations not only cut down on costs but also has the ability to impact the bottom line.

The power of these insights is immense to enhance the end-user experience. Glimpseanalytics can help you to implement these systems in your retail environment.

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