How Does Customer Tracking Technology Work in Offline Retail Stores?

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When a visitor enters a website, their every move can be documented. Analytics software registers every page visit, every click and even how long they stay on a page. Until very recently, this kind of data wasn’t available to offline retail stores but now with the creation of customer tracking technology, the offline world can start to compete with the online one.

Understanding the customer

The use of customer tracking technology pairs with data analytics software to provide retailers with the type of information once seen only online. This customer analytics or retail analytics allows businesses to understand more about their customers and therefore their stores than ever before. But how does it work?

Wi-Fi pinging

One of the main ways that big data platforms acquire information about customers without intruding into their person data is called Wi-Fi pinging. Every internet enabled device such as a laptop, tablet or smartphone has a MAC address. If the device has Wi-Fi enabled on it, connected even without being switched on, then the device is constantly searching for the nearest place to connect to the internet.

Every time the device manages this, it leaves behind a marker than it was there – the MAC address. So stores simply need to create a network of Wi-Fi hotspots throughout the store and they can see where a certain device connects to the internet. This creates a picture of the movement of the individual without taking any sensitive or personal data – it simply creates a profile of them connected with the MAC address of that particular device.

The picture created

At first, this may seem interesting but not wholly useful. However, add this information to good data analytics tools and quickly, a picture can be created. This picture takes the layout of the store and looks at where customers go and where they don’t go. Add to this information about special offers, seasonal products and other data and you can quickly build up a picture of what parts of the shop are working – and what aren’t.

Another aspect of this analytic software is the use of CCTV imagery. Again, this doesn’t take any sensitive data but can offer broad details such as gender and even age group or if the person has children. This can pair with the MAC address data to build an anonymous picture of the person that can help study their patterns within the store. So do women with children tend to use the seasonal aisle when they are with their kids? Or do they only go there when they are alone?

The data collected can also surprise retailers and learn them more about their stores. For example, one think tank recently conducted a study based on customer analytic software. They found that 50% of customers visited a store twice a week while 10% of the people entering the store never went near the register – meaning they didn’t buy anything. Further it showed that a promotion in the east side entrance of the store was more successful than at the west side of the entrance. It even showed that 10% of visitors had been to more than one store in the chain.

Staff management

Another area that customer tracking technology can assist with is staff management. At any time, a manager must make decisions about the number of staff within the store. Often this is done by a combination of intuition and experience or sometimes based on schedules handed down from a head office. Whatever the case, it can be a little random because there is only so much data available to make a more scientific decision.

However, with the use of customer tracking technologies, the store manager can access a wealth of statistical data to create much more accurate staff rotas. A good software platform can allow the manager to create a profile of each staff member including things such as preferred working times and number of contracted hours. They can then apply this information to the customer data collected by the software and create a rota that is scientifically based.

The results are that there are more staff available at times shown to be busiest by the customer data and less at the quieter times. Managers can provide facts and figures to head office to show why these staffing choices are made and can quickly adapt things if the pattern is shown to be changing. Data can be offered on a real time basis that allows the manager to quickly assess the staffing levels and call in back up staff if it seems they may be required.

The software can also help with matters of paying staff and managing their individual sickness and absence record – because all their working times are connected to their profile. So when it comes to time to work out wages or manage performance, the data held can simply the process.

Personalisation

The ability to collect this kind of data may seem intrusive but increasingly, people are coming to expect a higher level of personalisation than in previous times. People expect that businesses will collect some of their personal data through systems such as loyalty cards or email subscriptions. There is also an anticipation that stores will soon be offering you customised product recommendations as soon as you walk into the store because their software will know what you buy.

Conclusion

As the Internet of Things and other smart devices become a bigger part of our lives, the ability for stores to use the kind of data that has previously been held online means they can offer the best experience for customers. No more waiting at tills because there aren’t enough staff available. No more promotions you can’t find because they are hidden in odd corners. Data analytics and customer tracking software allow offline retailers to give the kind of experience for customers that online has previous held a monopoly on and could be the saving grace for the world of high street shops in the near future.

http://www.storetech.com/people-counting-offer

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1 Comment
  1. […] In-store analytics is a system that uses technology to gain insight into customer numbers, movement patterns and a number of other data areas for physical stores in similar ways to the analytics offered for online ones.  The system uses existing technology such as CCTV cameras and Wi-Fi hotspots to build a picture of what a customer does while in the store, without collecting personal information or infringing data protection rules. […]

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