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
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.