Everything About In-Store Analytics

Businesses need to monitor the the customer's behavior in order to ensure that their marketing is customer oriented. For this, in-store analytics offers competent insights on customer traffic and behavior.

Various metrics are considered during the analysis phase, mainly comprising of how the customers behave during their in-store visits. The store owners can take these measures to optimize their strategies for improving customer experience, hence their sales.

What Are The Benefits Of In-Store Analytics

In-store analytics provide retailers with real time information regarding how many customers and what customers do when they visit the store. This aids in a deeper understanding of consumer behavior, which helps in making sound business decisions.

Moreover, this also gives a number of other perks and advantages, when applied correctly.

Understanding Of Consumer Needs

The foremost objective of any retailer or business holder is to understand what their customers want or like. This is what in-store analytics is all about - identifying and quantifying preferences so it can be compared and improved.

As businesses need to amend their strategies in order to progress firmly in the competition, in-store analytics provides the foundation of improvements.

Insights from customer metrics can help reveal the following:

• Optimal product choice and placement

• Optimal store front attractions / offers to increase customer capture rate (street capture rate) who pass by the store and then enter

• Optimal store design to guide footfall to popular areas or products

Marketing Attribution

Retailers need to evaluate their footfall patterns to understand consumer behavior. Once the pattern has been identified, the retailers can easily move to marketing attribution. Retailers who have in-store analytics installed look at these key performance indicators:

• Number of visitors per day/week/month

• Time of visitors

• Length of stay aka dwelling times aka average time spent in which department or store

• Impact of various advertisement methods

• Impact of ad placement based on their locations

• Impact of advertising on hit rate and average purchases

Personalized In-Store Analytics

With the help of personalized in-store analytics, retailers can create a store environment which tailor-made and personal for a specific customer. The system can identify a shopper entering the store and create a unique omnichannel experience with location based data. For example,

• Create and send personalized coupons to the customer when entering

• Personalize digital signage displays

• Personalize in-store personnel service gestures to entertain the shoppers

Why In-Store Analytics Software Is Important

With the increasing complexity of the retailing market, the need for in-store analytics software has become quite apparent. Due to the increase in data of customers as well as the increase in the number of customer attributes, retailers need actionable insights that can help them change effectively.

Retailing involves having the right products and promoting them in the right manner so that shoppers convert to customers. That is why the collection of customer data is necessary for the retailers so that they may optimize the products and shopping experience accordingly.

In-store analytics helps minimizing the complexities of all the data so decisions and actions can be made.