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.

Advertisements