Transforming Retail with In-store Analytics

With eCommerce stores, small shops, and large retail chains trying the attract the same customers, it is needless to say, competition is intense. For online stores, technology has always been the leading light but the brick and mortar retailers of today are also stepping up the game and utilizing the technology to level and exceed the competition.

One such key piece of technology that is helping the store retailers is analytics. It can help retailers understand the business better and provide information that can help in improving their day to day performance and customer experience. But it is simply not limited to this, with new advancements, retailers can take this info and access it anytime anywhere on their mobile devices making insight consumption further easier. 

What is In-Store Retail Analytics exactly?

Retail in-store analytics is the collection and analysis of all retail store data to generate meaningful insights. Retailers can see identify trends and patterns and get micro and macro-scale business performance. 

These solutions provide quick and comprehensible insights that can help not just direct sales but also merchandising, marketing, supply chain, inventory management, and preventing fraud. Some of such solutions also provide pre-built reports that comprise essential KPIs and metrics. These reports can comprise detailed insights on marketing campaign performance, email marketing, customer behavior, expense, revenue, and other important parameters. This can help in gathering the right set of insights in one place regarding all the needed parameters to make data-driven strategic business decisions.

There are various ways for retailers to gather the right data such as in-store wifi networks, cameras, location beacons, smart carts. This can help collect important information like their demographic data like, age, gender, geographic data, and more in-store data like what path they followed, where they spent time, and more. These retail store analytics tools consolidate data from various sources and create a unified picture, through which retailers can easily see how consumer, sales, merchandising data are correlated to each other.

What precise problems can analytics solve for retailers?

With the constant need to make customer experience phenomenal and outperform the online markets, retailers are looking to get deeper insights on POS performance, brand and product sales, inventory losses, merchandising performance, how purchase decisions are being made, what factors contribute to sales and much more. Below we discuss all that analytics can resolve for retail stores.

  1. Every person entering the store can be a potential customer, but how to know which one is a consumer and which one ended up being an explorer. How to know who didn’t make any purchase and why. Analytics can help answer these questions. Retailers can understand how customers behave while in the store, how is the store layout contributing to the sales, and what factors are contributing to the consumer experience. They can understand the sales inducing factors and make the right decisions to optimize these factors to convert the explorers into shoppers and customers into loyal customers. 
  1. It is just not enough to know what your customer purchases from the store but also to know what more they can purchase and what they haven’t purchased. Retail store analytics get insights on which factors contribute to sales and how well the POS and other factors worked to generate a sale.
  2. Every retail purchase, store layout, Pos display, and absolutely everything has multiple factors affecting them. The retailers need to make daily quick decisions which are usually guesswork and may or may not work every time. Retail analytics can change this by providing factual insights and empowering retailers to make data-driven decisions.
  3. In-store theft is still an issue for brick and mortar stores face on daily basis and end up losing a lot. Analytics can provide smart insights into which areas are more prone to shoplifting and what behaviors are essentially attributing to shoplifters which can help in minimizing this issue.

Believe it or not, retail analytics is here to stay, the faster retailers implement this, the faster they can reap the benefits and avoid losing the raging retail battle. Implementing simple analytics is not the answer anymore, retailers need to think many steps ahead in the future. They need to implement predictive analytics in day to day work and make futuristic decisions to optimize their work and improve customer experience.

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