In-Store Analytics: Why Retailers Should Utilize It

Brick-and-Mortar stores are struggling with both rival in-stores and online platforms for a better market position. The introduction of Predictive Analytics has raised the level of competition and made the race more troublesome for any industry. And hence, a trivial blunder can cost the closure of any retail business.

The Retail stores must have a fair idea of its objectives before considering in-store analytics. Big data can be confusing, but a clear Business Intelligence strategy enables any organization to get through easily.

We will discuss Retail Analytics Solutions and objectives selection for retailers to explore further.

in-store analytics

Conversion Rate and Footfall Data:

Knowing the exact footfall information of any vital store is very crucial. Retail insight will allow the retailer to react and adapt according to the available data in real-time. The analytics thus enable the retailer to understand and predict in-store customer behavior and so can enhance the store performance and widen shopping environment. Retail insight underpins the store for better sales, staff optimization and increased productivity.

Customer Service:

The retailers need to identify the busiest sales hour in their stores to ensure enough staffing to meet the customer demand. This cuts cost, drive high conversion rate and improve the buying experience for the customers.

It is important for the store manager to keep accounts for the peak periods of Break time and after work hours service to boost the conversion rate. Moreover, the staff should undertake operational tasks during their free times.

It is needless to mention a hassle free and interactive shopping journey will bring back your customer over and over in your store.

Category and Space Productivity:

Retail Analytics will provide the retailers with the information of the shop zone, promotion message, seasonal effects, display units in the retail store enjoying the highest sales irrespective of the products. This also includes predictive analytics. Such strategy will easily pinpoint the optimal location inside the store allowing the retailer to push the high margin products over there to enjoy a high ROI.

For example, in a retail store, during the summer holidays, the retailer noticed a high sale in the organic juice. The retailer placed some outdoor games, summer clothes in the dwell time area, and put a promotional offer on summer product. And in few days, the sale rose by 30%. This is how Predictive Analytics work in retail outlets.

Customer Response:

The behavioral insight of retail technology solutions is immensely beneficial for the retailers. Learning the customer journey in the shop highlights product exposure, in-store engagement and navigation route throughout the retail. This can lead to an improved result for the retail owners that drives the shoppers deep into the retail for best exposure and long visits time.

The retail landscape in on a constant change. If the retailers can use the Big Data with Business Intelligence Strategy the store can easily know the customer demographics on the real-time and aim at increasing cash flow ROI.

in-Store Shopping – Fun Package with Retail Analytics

India is now on a growth ride. In 2012, GDP was 5.1 which raised up to 7.3 in 2014. This growth is inevitable in the retail sectors in India. Retail sectors are becoming well organized and attaining maturity day by day. For the right marketing and procurement decision, you can entrust your business with the retail analytics. Retail Analytics provides the analytical data on inventory level, demand – supply chain, etc. Retailers in today’s world are maintaining transparency in the shopping experience.

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Price Transparency in Retail Analytics Companies in India :

There was a time when we had to depend upon the shopkeeper to show us their products and we were to choose just from within their displayed products. But now with the retail shops, we can enjoy the benefit of thorough browsing and choose any item of their desire. There was a time when the price of a definite product was not unique for all. In some cases, shopkeeper used to set price depending upon the attire of the customers. Hence, price comparison was also not possible, and an individual had to depend upon mere bargaining strategy.

But with the introduction of fixed price shops in India, shopping experience became better. Almost all leading branded stores and shopping malls of India are equipped with gadgets like Tickto that allow receiving offline mobile offers (through Bluetooth). They are so designed that you will receive the orders that are meant for your needs only. The artificial intelligence will identify your product choice from your previous shopping details from your mobile.

However, with the introduction of the auto detector machine, there is a risk from people to start gaming in the business system.

Transparency in information:

As soon as you enter the mall, you will be informed of the product detailed information. Thus, the users know how much he should be charged for a specific product. Also with the better information technology, the customers can know how well they should be treated by the seller. Today the seller are more eager to know more about the buyer’s shopping experience than the sale of their product and ask for a review for their products and services. This is just to maintain a healthy relation that will bring future customers into their business.

If a customer is not satisfied with the product, the result can be worst on local forums, blogs, discussion etc. However, this can also be well tackled with the comments and responses made by the seller. The sellers can appoint web community to participate in the forums, blogs and give updated feedback to their customers. This helps in building a strong community, which helps in the long run in product promotion.

Thus, if you are a new customer, before buying any product you can be well informed about the product, and services by the seller in just a few clicks.

Easy Product Detection:

After entering the mall, you have to switch ON your mobile Bluetooth and you will automatically receive the promotional offers, discounts and revised price list of the shops you are visiting. You can compare the product price and choose the shop from where you want to buy your desired product. You will also be guided to the location of your product. The only thing you need to do is to PAY. Now you can truly state – “Shopping was never so easy before.”

Analytics Companies in India is growing every day. It has become a strong platform for building loyalty and turning unhappy browsers to regular customers. It is the analytics firm that is grabbing the regular shoppers and making a business from them and is a win – win market condition for both the buyer and the seller.

In-Store Retail Analytics: a Way to Increase the Footprint at the Stores

Companies are experimenting with various techniques to increase the footprint of the stores. The in-store retail analytics plays a major role in this matter. The digitally savvy customers are changing the retail environment every day with their various needs and demands. Thus assessing the customers in today’s world and increasing the footprint is quite a tough job being faced by the Retailers. This should be done quite analytically to get a profitable result. From retaining a Customer for a particular Brand or for launching a new Product that might attract Customers, need to be planned properly.

in-store retailing

Methods to Be Followed by In-store Retail Analytics to Increase the Footprint:

The dictionary meaning of Regression Analysis is to find a relationship between different variables. This process is widely used for forecasting or for predicting something. Path tracing is a model that uses this regression analytic model, these in-store retail analytics models can widely be used for knowing various aspect of human behavior.

The Human Behavior and its aspects can easily be Predicted or evaluated by joining the nodes of the graph or various points of the graph. This again demands the understanding of the topological structure of the human behavior. This model is used to enlighten various important part of a human behavior like this depicts what is the most shortest path that a human being opt for while looking at the entire graph starting from the source of the graph to its nodal point. There is always a path or a way that lies in between this two that is the shortest path which is being opted by the people or the human being at a much local level and the path that lies at global level or at a much wider level.

The job of this process is to predict the graphs or the path that are being widely used by the customers of different group or people of same status. Unlike this modern method, the earlier methods focused on the layout of the graph or in improving the visualization of the graph.

Graph readability is another technique being used by the company to know their customer’s behavior. In this process the companies pay attention to how their customers are behaving after reading or understanding the graph. This mainly depicts the graph reading behavior of a customer. This graph reading behavior of the customers varies with the tasks the in-store retail analytics deals with.

 footfalls in stores

Conclusion:

If the result of this methods are studied analytically it can be concluded why a customer is sticking to the previous graph or brand, or what is the reason for a changing the decision, these also depicts what are the common path being used by the customers, etc. These are all complexities of a human behavior and are hard to find. There must be various trial and error methods to be followed before concluding something. The modern day methods have somewhat made the job easy for the analyst to conclude something about the customer’s behavior and increasing the footprints at the retail stores. Thus the in-store retail analytics plays an important role to increase the footprint at the stores.

In Store Retail Analytics : Its Potential and Impact on Managing the Customer’s Behavior

The world of Retail is changing at a fast pace. The retailers today are experimenting with lot of things to attract new customers as well as to retain the old ones. Thus retail analytics plays an important role among the Retailers to succeed in their business. Customers are a most essential part of business. Both for online and brick and mortar stores customers are an integral part of the business.

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Scenario of In-Store Retailing:

The online Stores are experimenting with their styles, designs, placement of their products to attract the customers and so that their products catch the eyes of the people.

Although the brick and mortar stores are dominant among most of the customers but these stores lack behind due to improper technologies to conduct and judge their customers behavior. However, now most of the physical pay stresses to know their customers behavior. The retailers of these stores now have a close eye on the buying habits of the customers, movement of the customers inside the shop. In-store retailing is emerging at a fast pace in today’s retail shop. The retail shops now have security cameras inside the shops to keep a watch on their customers.

The use of multiple cameras can track the behavior of the individual customers as they roam about in the shop.

Benefits of knowing the Customer’s Behavior:

In-store Retail Analytics also help the Retailers by providing data about the Customer’s Behavior outside the shop. They provide data about where the customers are going, where the customers roam about, whether they are shopping alone or with friends. These data help the retailers to plan accordingly and project their products in front of their customers to get most of the output out of it.

On the other hand the brick and mortar stores those are lacking behind these sophisticated technologies also conduct these surveys on assessing the customers’ behavior. They instead of using all these technologies they walk around the shop to look at the customers to assess their behavior whether their plans and programs are working well on their customers.

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Trends of In-Store Retailing:

The data collected from in-store retail analytics processes help the retailers by providing data of POS (point of Sale) as well as data related to the cash register of the store.

Another part of in-store retailing involves displaying the products and offers in a right manner so that it can attract and catch the eyes of the customers. Placing the products in front of the window or the glass door can catch the eyes of the passersby also.

Customer traffic information plays an important role among the retailers. The data revealing the number of customers regularly entering the shop is very much an integral part of a good retailing. The data obtained from in-store retail analytics process also helps the retailers to know whether the promotions and the offers they designed for their customers are working well or not.

Conclusion:

On the Retailers point of view in-Store Retail Analytics is a process of anticipating and understanding the customer’s needs and wants in a better way. Improving the staffing, identifying new offerings and planning valuable promotions for the customers are all a part of the in-store retailing process.