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.

retail-analytics-2016

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.

Be a Digital Winner to Win over the Retail World

Earlier the Retailers tend to increase their Business by building new store. However, the scenario has changed a lot. Knowing about the customer’s base or knowing the customer database is the new trend among the Retailers. A question that arises in everyone’s mind is; what is the role of brick-and-mortar store in today’s world. In-store purchasing among the customers is decreasing day by day. Now most of the customers depend upon the internet for taking their purchasing decision. The retail analytics companies or the Brands need to be a Digital winner to win over the Retail world of today.

retail analytics

Steps to win over today’s challenges:

The traditional stores are the most affected by these changes. Thus the retailers have to follow some steps to protect themselves from extinction. This includes:

  • Taking decision that will not help the retailers to sustain their position today but also to protect themselves tomorrow.
  • Making the in-store shopping experience of the customers much more exciting.
  • Updating the customers time to time with latest offers, discounts, etc.
  • Paying attention to the proper decoration inside the shop. This involves placing the right product at the right place, putting the advertisement at a place so that if can attract more customers etc.
  • Checking now and again the contents of the Advertising messages that are an important tool for the Promotion of Products or Brands.
  • Paying extra heed for Personalization of the advertising messages.

Some Examples:

  • If we look in to the U.S. based Retail firms we will find that more than 250 apparel Retail Stores have closed by 2013.
  • The size of the new stores of Walmart is about one-third time smaller than before.
  • The number of vacant retail store in U.K have risen 355 percent between 2008 and 2013.
  • A recent article on Retail Analytics by Tickto have pointed out a very important fact that, although in this generation of technology the process of data collection has much widened up but the major challenge for the Retailers is how potentially they are using these collected data for increasing their business. This led to the growth of Business Intelligence (BI) system.

The Retail Analytics Companies need to follow certain steps to make the Retail Analytics a Fruitful one:

  • First the Retailers need to choose which approach of Retail Analytics suits them the most.
  • The second step is to find that the retail analytics approach chosen is quick or not to bring a positive result.

The retail analytical project or the approaches to be chosen also varies from one firm to another. Like the online retailers depends mainly on extensive or vast customers data and information. While on the other hand the Retailers of the Brick-and-Mortar stores mainly depend on various channels to collect the Customer’s information.

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.

It’s Time for the Brick-and-Mortar Stores to Analytically Plan Their Strategies

The Brick-and-Mortar stores are experimenting with various things like from changing their in-store design to changing the position of the products inside the stores. All are being done mainly to attract customers. These brick-and-mortar stores lack behind in this matter. They have insufficient or inadequate numbers of customer’s data than those of the online Retailers. This increases the need for a Brick-and-Mortar Store Analytics.
brick-and-mortar store

Changing Scenario:

The Advancement of Technology has made the situation to change a lot. Now a day the brick-and-mortar store retailers need to access the same data as the online retailers. The advent of smart phones has made the job much easier.

In today’s world there are two types of customers that is one who rely on the online marketing site and the others who still date have faith on the physical marketing or on the retail stores.

Dealing with the online customers is much easier than those of who come to the retail shop. The online retailers with various smart tools and technologies keep and maintain a regular assessment of their customers. They keep on changing their rules and regulation, their business plans to attract more and more customers or to retain the old ones. The major problem is being faced by the brick-and-mortar stores. They have lack of data to have a proper understanding about their customers.

How the Processes Work?

There are various ways through which this Brick-and-Mortar Analytics can be done. As soon as a person sign up for a website the web cookies start tracking each and every buying detail of customers. These details can be further used for Retail Analytics to plan their strategies accordingly. By looking at this they can design individual customer plans. The retailers can plan for the discounts to given, the place where the products must be kept to attract most the customer’s attraction.

in-store retail analysis
Steps That the Brick-and-Mortar Stores Can Follow:

  • The brick-and-mortar stores or the physical stores can opt for video marketing facilities at their shops. This will help them to have close observation on their customers as well as their employees.
  • All the brick-and-mortar stores must follow the test and learn marketing procedure to get a better result.
  • Reviews can be another way to judge the customer’s behavior. Reading the customer’s review the retailers can get a better picture about what are the things customers are liking, what are the things they need to have a change.
  • Wi-Fi in store kiosks is an excellent way to keep a close eye on the customers who are inside the stores.
  • Personalization of the products, offers or discount can be done knowing the individual customer’s behavior.
  • Brick-and-mortar stores can have an online catalog of their products. This way they can attract all the technologically savvy customers.
  • Most of the customers are getting more and more inclined towards the online trends, so online payment mode,
    e-banking, PayPal are the other things the Retailers can keep in mind.

Conclusion:

Merging the two marketing arena like the online as well as the brick-and-mortar retail stores can give a much better result.

Heat map analytics and its impact on Retail

The dictionary meaning of Heat Map is the graphical representation of any individual value. The matrix of this representation is represented by colors. The different colors that are seen in this graphical representation have different meaning or depict different values for different data. However, in Retail the heat map help the Retailers in many ways like;

  • It helps in knowing the hot spots,
  • Dead areas
  • Bottlenecks

How the Heat Map Works?

The in-store heat map system takes the images being captured by the network cameras or the IP cameras which help the Retailers to have an idea about the customer’s traffic pattern in a particular time or during the real time. The information can be collected from anywhere in the network.  in-store heat map Benefits of in Store Heat Map:

The benefits of heat map system in Retailing are many folds. These are;

  • By having a clear view on the customer’s traffic pattern or by collecting information about this helps the retailers to improve the in store.
  • Help or improve the customer service techniques being used by them to satisfy the customers.
  • It also helps the retailers to improve or plan the promotional activities and the marketing techniques. This helps the retailers to meet the customer’s demand by using the customer’s traffic data containing customer’s buying habits, behavior.

By using the heat map system in the in-Store Retail Analytics process the Retailers can see positive changes in terms of the customer’s flow, items that are sold , average sale value and many more. Features of the cameras that make in store heat map a beneficial one; The network cameras that are used in the in store heat map are,

  1. Scalable
  2. Flexible
  3. Cost Effective

All these above three characteristics make heat map a powerful Retail Solution.

The Various Heat Map Analytics Tool That Can Be Used by the Retailers to Get a Better Result in the Retail Store:

    • Mouse flow: It is a live analytic tool. This helps to know the website visitors. This help the retailers to gather information about the customers by knowing where they click, where they browser or on which item they are giving extra attention. This system captures all the mouse clicks, keystrokes etc.
    • Lucky Orange: This is also a live analytics tool that helps the retailers by giving them information about how many customers are currently visiting their sites. This system compares the historical statistics to see what kind of customers are mainly visiting their sites, what keywords are being used more frequently and so on.
    • Crazy Eggs: It helps the retailers to analyze their customer’s engagement through heat maps. These give an information about which portion of their website attracts most of their customers.
    • Click Tale: By aggregating the total number of mouse clicks of the customers the click tale tool creates a visual representation of where the customers are viewing more or focusing more on the website. The tool calculates by seeing the mouse move, click, attention of the customers, etc.

Conclusion: This shows that the heat map system makes the in Store Retail much more smooth and fast. It also helps in making the in store retailing fruitful.

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.

How Big Data Analytics Is Helping the Retailers to Meet Their Customer’s Demand?

Big Data Analytics is the process of measuring a large number of data sets containing large and different types of data. This big data analytical process is being helpful in knowing various market trends, customer’s preferences and many other business related information. Many big retailers now appoint big analytics to get a fruitful result from their Retail business. To get the most effective result from Big Data Analytics the Retailers merges the structured data with the semi structured data

Goal or Motive:

The main motive of the big data analytics is to improve the business by collecting a large volume of transaction data as well as the data that are useful to meet the customer’s satisfaction level.

big data analytics

Benefits of Big Data Analytics:

  • Led to more effective marketing.
  • Help in knowing new revenue opportunity.
  • Help in providing better customer service to satisfy their needs and demands.
  • Improve operational benefits.
  • Helps in implementing services that are far better from the rival companies.

How to Implement the Big Data Analytical Process?

Big data analytical process uses tools that are commonly used for advanced analytics processes like:

  • Predictive analytics.
  • Data mining.
  • Text analytics.
  • Statistical Analysis.

Mainstream Business Intelligence software’s (BI) can also be used in this data analytics method.

Some Retailers implementing the big data analytical system also now a day depends on the Hadoop clusters technology to collect huge amount of raw data. These raw data is being further been filtered and used for analytical warehouse. It may also be used by the hadoop software.

Pitfalls in Implementing the Data Analytical Process:

  1. Lack of internal analytical skills.
  2. High cost of hiring experienced analytical professionals.

The Benefits That the Retailers Are Being Experiencing from the Big Data Analytics Process

  • Delivering information about individual shoppers; this big data analytics process helps the retailers to know their customers well. The retailers through this process can know their customers by their name, their shopping habits etc. The big data analytics process keeps a track about the last few purchase of the individual customers.
  • Helps in guiding the customers to discover their associated products; The retailers by knowing the buying habits of the customers , knowing their daily needs and demands can guide them to make their shopping much more easy and smooth. This way the big data analytics process is useful for the retailers as well as the customers.
  • Tracking and analyzing the shopper’s visit data in online retailing; with the help of this big data analytics process the retailers now with a click of mouse can measure the shopper’s behavior, the amount of time spent by the shoppers in each page. This helps the retailers to design their page layout, preparing their promotional messages keeping the customers need and demands on mind.

 

Conclusion:

Big data analytics process thus is useful for both in-store retailing as well as for online retailing. This big data analytics blur the difference between online and physical marketing processes.

However, the Retailers also need to keep in mind that the Data Collection method for both physical and online retailing is different. This can be a matter of concern among all The physical retailing involve much more transparency in the data handling process, includes individual privacy concerns and also honor the individual customers preferences.

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.

in-store retail

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.

 in-store retail analytics

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.

Importance of Retail Analytics and Their Various Impacts on the Retailers of Today’s World

The Retail Analytical approaches or planning the Retail Strategies analytically help the Retailers to know their customers individually. It also helps in making the Retailers to save their money and limit bad expenditure.

Knowing the customer’s behavior is the key to success for the Retailers.

The Retailers who know their customers well are making much profit than the Retailers who are unknown to their customer’s needs and wants. When the customer’s behavior intersects with goals of the retailers or the suppliers then the profit rate is at the peak. This can only happens when the retailers know their customers very well. Thus Retail Analytics is very much necessary. It has been found that if the offers or the discounts arranged for the customers are being made maintaining various retail analytical strategies then the profit maximization rate for the retailers is also high.

Problems faced by the Retailers:

One of the very common problems being faced by the retailers is that they are unable to understand how to react and treat their individual customers. This is a common problem for in store retailing. The retailers also sometime face a problem in deciding what the offers should be or discount to be offered to their customers. Another mistake made by the retailers unknowingly is that, when a new customer enters the retail shop the retailers are unknown to the customer’s potential or the customer’s behavior so they treat every customer in the same way. To meet with this kind of situation various retail analytical strategies and plans should be designed. Coupons can be given at the entrance of the retail shop or discount offers can be sent as email to the existing customers. By seeing the response of various customers the customer’s behavior can be judged.
analytics1Retail Analytical Approaches made by the Retailers;

  • There are certain actions that the retailers plan and are then targeted to every customer might they be new or old. These types of actions are known as the collaborative filtering action. These types of offer or the discount are often being targeted to the customers of the online store or in-store.
  • The retailers also sometimes make their offers or discount by dividing their customers into small groups. These groups are made according to the customer’s choice, customer’s behavior.  This type of segmentation among the customers is most commonly being termed as the behavioral segmentation. This is a retail analytical process that can be done when the retailers know their customers very well. These types of retail analytical approaches also help the retailers to save some expenditure without spending on unnecessary offers or discount. The retailers also can spend the money on n house designing, preparing various new merchandising scheme or building up new promotional strategies. This segmentation among the customers also helps the retailers to serve their customers who are very important for their business.

The Retailers also sometimes plan the offers and discount by predicting the behavior of the customers individually. These retail analytical approaches are known as the propensity model. These retail analytical approaches can be used by the big retailers who deals with ten to twenty millions customers each of whom plays an important role individually for the business. These propensity models help the retailers to know the individual customers buying behavior. This also led the retailers to prepare various unique treatments towards their customers.