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The different types of POS systems

Updated: Sep 11

In this post we will shed some light onto how you extract your own POS data as well as what the difference between the various POS setups there are. Before we start, we need to mention that the method of data extraction as well as what it contains varies significantly depending on which POS system you are using and whether you want to extract POS data from a retail store or your online store. More up-to-date systems already have data analysis integrated into the product while older versions may only allow you to extract a file with raw data. And some systems may not allow you to extract any data at all, but just display it on the screen of your POS system. Accessing POS data from your online store For online stores, the process to analyse your data is much easier than extracting and analysing data from a physical device. This is mainly due to Google Analytics E-commerce Tracking and integrating that with your POS system, assuming you are happy to share your data with Google. In practice, this is done by adding a couple of lines of code to your check-out page which allows communication of your POS data to Google Analytics. That sounds complicated and, indeed, requires at least a minimum level of technical knowledge, even though there are very useful guides available. Chances are, however, that if you are currently running an online store you may already be using services from companies such as Shopify or Klarna that help to organise your payment process in a plug-and-play fashion. These companies have realised the value of offering this type of service and have therefore developed plug-ins that communicate data automatically to Google Analytics, which only require a minimum amount of work to enable the sharing. Here is a 4-step guide to how this works for Shopify. Accessing POS data from your physical store As noted above, this will be a lot more dependent on what type of POS system you are using as well as whether you are using cloud-based infrastructure or a local central server. In order to illustrate the difference, here is an example how this process works on a local central server where POS terminals are connected over LAN:

  • Customer decides to buy a bottle of water

  • Terminal: Server, please check price for product UPC 342831372

  • Local server: Checking the database for UPC 342831372, communicates the price to the terminal

In a cloud-based infrastructure, this works in a very similar fashion but with one major difference. The local server is not located in the premises (or nearby) of the store, but is inside a larger data center where a server is hosted by the store, meaning that the information travels over a larger distance to provide the price information and is dependent on other companies.

The reason for illustrating the differences between the above is to make the point: if you are using an older POS system, it will require a lot more know-how to first retrieve the information as well as analysing what it contains. Using a more updated infrastructure may make this a lot easier in areas such as data formatting and analysing. Other pros and cons between the two setups is that in order to have a cloud-based setup you need to have a good internet connection, as otherwise customers will need to wait longer to actually be able to pay.


In any case, even if you are a firm believer that a local POS setup is the better approach, you can still connect to the Google Analytics in a similar fashion as to what you would be able to do for your online store. This is due to the Measurement Protocol that Google has developed, which is specialised towards allowing devices involved in the POS process to automatically communicate with Google Analytics. Here is some useful information on how that works. Stay tuned for more posts on this topic!

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