In-store Customer Tracking
Everything about In-store Customer Tracking
What is In-store Customer Tracking?
In-store customer tracking is a technique used to answer the following questions: At what instances do shoppers go to the store? In what manner do they act? And how will these affect sales? Retailers have to tackle these concerns to maximize their brick-and-mortar shopper experience. To execute this, retailers have to employ a broad array of technologies in the marketplace that determine purchaser or buyer conduct.
How does the In-Store Customer tracking work?
Tracking purchasers is very important for brick-and-mortar retailers today. Gathering data about customer shopping behavior and utilizes it to swiftly adapt to their preferences and requirements will ensure customer loyalty. In-Store Customer tracking has the prospective to change how retailers/store owners converse with their consumers. It offers the insight to identify precisely when to engage and when not too.
There are four standard methods to in-store customer tracking: wifi, mobile apps, camera, and passive network. Using a combination of in-store cameras and face analysis software, shops can now accurately assess the demographic information of its shoppers, including metrics such as age and gender. This core data can be collected at each stage of the customer journey, tracking shoppers (and how they interact with a store) from browsing through to checkout. The anonymized information is then forwarded to a central server where it is processed and analyzed.
What are the advantages of Customer tracking?
Not only can face analysis technology, used in in-store customer tracking, identify and classify customers, it can help retailers optimise and plan their product offerings. By tracking the flow of people around a store, including where they stop and where they don’t, businesses can adjust the layout or reposition stock. Making small, data-driven changes like these can make a store easier to navigate for shoppers, while business can be boosted by making the most of highly-trafficked areas.
For brick and mortar retailers, this is key. While online brands have plenty of data to show what individuals are buying, face analysis has the potential to give traditional stores a wider view, showing who’s buying what and when, and even the emotions associated with the process. Access to this data allows shops to identify problems and grasp opportunities, providing superior customer service that will keep shoppers happy, engaged and loyal.
Performance metrics for anonymous in-store customer tracking
The ideal way to go about tracking people is in terms of the business benefits. Anonymous location-based data serves a wide variety of sectors, including Retail, Buildings, Hospitals, and Transportation. In-store Performance Metrics are a function of anonymous analysis of either a zone (with sensors) or device (with wireless technologies). Below are the metrics retailers consider:
Shopper Traffic to store (#Visitors)
Proximity Traffic (% Capture Rate)
Choosing Physical Store Site (Trade Area Analytics)
In-Store Product Positioning (Path to Purchase)
In-Store Employee Locations (Service Productivity KPIs)
In- Store Live Map & Product Information (Path Analysis)
While In-Store People Tracking depends on the factors of Behavior Analytics, the sales cycle starts at the point of entry to the store.
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