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How stationary trade catches up to online shops with POS tracking data

Due to increasing challenges in digitalisation, e-commerce has been increasingly surpassing stationary trade. According to the IfH Institut in Cologne, this trend will be increasing in the coming years. Parallel to a reduction in sales in stationary trade, by 2020, sales from online trade will increase to approximately 77 billion euros.

Despite the reduction, stationary trade will also play a significant role in the future. Online shops have recognised the increasing importance of stationary shops and are now constructing stationary shops. Yet in this case, for stationary trade, it is essential that it adapts to the changes in consumer behaviour and proactively adopts digitalisation. In the chart below, examples for the effects of digitalisation on consumer behaviour are shown:




Examples for the effects of digitalisation on consumer behaviour

In order to successfully meet current and future challenges, stationary trade must react to changes now more than ever. In particular, data can help to sustainably improve the shopping experience as well as all marketing measures. In terms of data availability, data analysis, data integration and data quality in particular, there is often an enormous gap to online trade. For continuous improvement in stationary trade, this gap can be closed via the use of digitalisation.

At present, there is still a lot of unused potential, especially in the area of in-store analytics solutions. This is because only few decisions regarding product ranges, surfaces and advertising  are made using POS tracking data and the key indicators derived from it.

This is one of the major shortcomings of stationary retail, which frequently generates between 80% and 90% of sales by means of its respective stationary sales areas. However, the majority of retailers have no knowledge about visitor behaviour within the shop. This knowledge exists, if at all, regarding only the 10% or 20% of sales with the respective online shops.
However, there have long been possible solutions to this on the market.

The following chart shows what can be achieved with the digitalisation of stationary retail:




Comparison of selected KPIs for online shops vs. stationary retail with and without digitalisation

In the area of digital tracking of visitor behaviour at the point of sale (POS) in particular, there are already a large number of innovative technologies. However, these are rarely used. In regard to the all-encompassing use of these technologies, stationary retail is rather reserved overall. However, using in-store analytics, many areas of optimisation potential can be detected. In the following, three typical areas of potential for improvement are presented.

More effective management of customer flows in certain areas of the point of sale

To be able to manage the customer flows within a shop better, KPIs first need to be defined. The following table highlights which KPIs should receive attention.




3D camera sensors that are installed in the different parts of the shop within the relevant areas are particularly suitable for determining the relevant KPIs.
The thus generated data can then be used to derive concrete measures aimed at optimising customer flows:

  • Restructuring departments
  • Creating gastronomic action points
  • More effective personnel planning
  • Improving the product interaction rate

Through these measures, customers can be guided into previously weakly frequented areas, while sales are increased at the same time.

Identification of shopping basket differences between customers with & without an advantage card

Who buys when, where and how much? These questions are often difficult to answer for stationary retailers. Although these matters can still be tracked in the case of owners of advantage cards, this is considerably more difficult in the case of the target group of non-advantage card owners. A severe disadvantage for stationary retail. 3D camera sensors, with which valuable knowledge about all customers can be acquired, may provide a remedy here as well. As before, KPIs need to be defined. These are listed in the table below:




Here, too, it is of course exciting to observe which concrete measures can be derived from the determined data:

  • Measures of floor management (placing of goods (brands vs. own brands, product ranges, etc.))
  • Marketing measures (Which items should be advertised how, where and with which correlating products)
  • Purchasing decisions (which pack sizes are promoted, which offers should be expanded)

Comparison & improvement of in-store advertising measures/visual merchandising

Window display presentations, print & digital displays, sale layouts - these are all typical in-store advertising measures. Stationary retailers can often only guess what kind of impact the different designs have on customers and how effective they are. 3D camera sensors with face recognition may provide a remedy here, too. The previously defined KPIs are as follows for this application case:




By means of the thus collected data, aspects such as the performance of the windows displays, of the advertising displays and of the sale layouts can be measured. Thus, ultimately, reliable conclusions can be drawn regarding the return on investment of each individual means of advertising. Based on this, it can then be calculated to what extent the often high expense is worthwhile and which efficiency enhancement measures are necessary in order to improve performance.
In addition, it is always important that a wide variety of possibilities be tested and checked again by means of tracking measures so that the best possible solution is ultimately attained.

Instore-Tracking - Typical Project Flow

Of course, there are many other application scenarios, which we would gladly explain in a personal conversation. At this point, therefore, the flow of an in-store tracking project should be commented on.




For a successful in-store tracking project, at the beginning it is particularly important to ensure a clean definition of the KPIs as well as to choose the right technology or the right combination of technology. Moreover, it should also be stated at this point that in order to obtain usable information, an information collection period should last at least three months. Only in this way can exceptions in visitor behaviour be estimated well and representative data ultimately be produced.

POS tracking as a competitive advantage in stationary retail

As described above, a great deal of potential in stationary retail can be revealed through the use of in-store analytics. Thus, retailers can not only set themselves apart from the stationary competition, but also close the existing gap to online retail at the same time.  In the coming years, the orientation towards digitalisation will grow increasingly in stationary retail as well and will exert a strong influence on stationary retail. The following overview provides an outlook regarding the success factors for digital tracking in the next few years:




The use of in-store analytics solutions can close the knowledge gap to the online shops on a long-term basis. In parallel to this, a more direct orientation towards the consumer is taking place, allowing higher sales and better frequency absorptions to be generated.

Missed the webinar? You can view the webinar (in German) as live again here and find out about concrete application cases of in-store analytics solutions.

We would also be happy to highlight the possible uses of in-store analytics solutions to you in a personal conversation!