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.

Location Based Analytics Makes Your In-store Analytics More Powerful

There are experiments going on at a regular interval in the world of marketing. There is new innovation in this field at daily basis. Through this the marketers want to gain the maximum profit out of the investment they have made. One such invention is the Location Based Analytics. Location based analytics is a step beyond to see and assess the result or the outcome of the mobile campaign being done by the Retailers. Tracking the views and clicks in the smart phones, laptops for knowing the customer’s choice and behavior is a process that was already in use among the retailers. But what is new is the use of smart phones location data. This allows the marketers to gather information about how many in-store visits are actually happening due to this mobile campaigning process. Thus in-store retail analytics become much more powerful with the use of location based analytics along with it. location based analytics  What Is the Main Objective of the Location Based Analytics Process?

  • The data collected from location based analytics gives information about the spatial behavior of the customers in relation to the previous exposed ad’s.
  • One of the main objectives of the location based analytics is to keep a track on how the mobile campaigning process or the already exposed mobile ad’s are effecting the buys of the customers in-store or inside the physical stores.

Why Location Analytics Process Can Be Used by the Retailers?

The location based analytics process helps the Retailers or the Marketers in many ways:

  • Place IQ: Place IQ or the Place visit rate is the process of finding out ROI of the mobile advertising, targeting and measuring tools. The retailers continuously send various product related advertisement to some existing customers or to some new customers of a particular location. The location based analytics data help to predict PVR rate or the place visit rate which in turn gives an aggregate of the number of messages being sent to the customers and the total number of customers are actually coming to their store physically. This in turn thus also depicts the in-store analytics

  • Location Conversation Index: this is a process of understanding how the mobile advertisement influences the in-store visit. Instead of tracking the number of people who had already viewed the ad or clicked the ad the LCI or the location conversation index track the number of people are visiting the geographical location or the physical store after seeing the advertisement. This also help the retailers to keep a track on their message or the advertisement that are being delivered and can also improve them if needed according to the customer’s response to them.
  • Placed Attribution: This is a process of linking the advertisement, messages of the retailers, marketers, etc with that of the in-store visit. This also not only depicts data about the in-store visit but it also helps the marketers or the retailers to assess the behavior of their customers very well.
  • Foot traffic Index: It helps to assume the foot traffic index of a particular retail shop at a particular geographic location.

Manage Your In-store Scenario Analytically to Meet the Market Competition

In spite of the large developments in the economic sector the Brick-and-Mortar store are still at the top most level in the retail scenario. Retailers in the today’s world also seems to be in a big dilemma when it comes to the areas of managing the in store scenario. Retail analytics plays an important role in managing the various services of the retailers. The retailers need to analytically manage the in- store, that is they need to practice the retail analytics theory. Though the term e-commerce is gradually increasing in the field of economics but calculating or capturing the exact amount is quiet difficult to find in the real world. This also increases the demand of retail analytics in today’s world.

Problems faced by the Retailers:

The mistake that is common among the retailers is that they are unable to bridge the gap between their online stores and the brick and mortar stores. This is a mistake being common among the big multinationals companies also. In-store analytics can help the companies or the retailers regarding this matter.

Factors Determining the in-Store Analytics Process:

  • Technologies being used by the surrounding market or finding how mature the technology is.
  • Who are the competitors in the market?
  • Who is the priority or the top concerns among the retailers and what are the technologies being used by them?


Understanding what is in- store Retail Analytics:

Finding the meaning of in-store retail analytics is very important. In-store retail analytics also deals with various things.

  • The first thing that comes when we are talking about retail analytics is that finding out the people data or tracking the people data. This is an important step in managing the in-store retail analytics This process of tracking people data involves finding out the data or keeping a track on how many people are entering the shop every day, how many people are buying the products among these people. Thus maintaining the traffic data is very much needed for in-store retail analytics.
  • The retailers in the in-store retail also need to keep a track on what is the consumer’s behavior. That means what are the promotional strategies that are attracting more customers, what are the products that are more common among the customers.
  • Wi-Fi store, mobile payment, queue management practices also plays an important role in the in-store retail analytics techniques.
  • Keeping a close eye to the inside scenario of the retail stores also play an important role in the in-store retail analytics process.
  • There is also a risk in in-store retail analytics process if it is not being done by the knowledgeable person. The result of in-sight retail analytics can affect the retail business badly if it is not done properly. The in-store retail analytics must be such that it brings a profit for the business.

Future Trends of the in-Store Retail Analytics:

In the recent years more and more retailers’ are opting for getting a multi channel perspective of the consumer’s behavior. The retailers in their in-store retail analytics procedure is focusing mainly on more and more interaction with their customers by the help of mobile, e-commerce or through the social networks. This will help to fill the wide gap between their online mode of retailing with that of their bricks and mortar store.