Transcript
Sabian, we still see many companies rely on Excelbased pricing. While it may feel familiar, isn't it holding them back? Indeed. I mean, Excel is very easy and fast to set up. It's a natural way of of kind of starting your pricing journey, but sooner or later you will reach the limits. Be it performance and scalability for calculating all the prices for multiple SKUs be reliability when it comes to pressures of the software collaboration functions and of course as probably everybody has experienced for himself it's errorprone also at times. So therefore um sooner or later company companies realize that it's not not good enough for for the long run. I see. So optimizing let's say 1,000 SKUs across four channels online offline and then two geolocations let's say on a weekly basis or not even daily basis sounds almost like an impossible mission.
It might work but if you go for a software as a service solution it allows you many more opportunities beyond uh what Excel can do. It's much more performant more scalable. You can run price optimization on every single skew in the catalog and you can do individual price calculations for every skew in all the channels online, offline, multiple countries and currencies. You can do that completely separated or you can have them in a relationship to each other. So that gives you kind of an endless space of opportunities to to make the pricing even more tailored and more deveraged. Plus integrating all data such as competitor pricing, inventory, market demands. Having all of these in one place is also super critical. Absolutely. I mean, when you start in Excel, you start very simple and then you grow over time and you realize you're kind of going beyond the capabilities.
If you have all the data in a SAS platform, it opens also the opportunity to apply AI and use all the data from inventory to competition and your own ERP system to optimize for revenue and profit leveraging price elasticity. Or you can run automated clearance sale. You can run article segmentation in the background that tells you the different roles of your items. All that is possible um applying AI in a SAS platform which you might not be able to do in Excel anymore. Some argue that Excel feels more transparent. What would you say to that? It's a very important argument uh and transparency is key um in the end because category managers are responsible for the P&L of their pricing and therefore they need to understand the prices in order to kind of understand, defend and explain them. Therefore, we don't believe in a black box.
Um our AI solution is making the recommendations very transparent. We provide a feature which is called a decision tree which guides the user step by step through the calculation and explains the key um reasons why a certain price has been recommended. That's such a critical point. Trust, adaptability, and clarity are definitely the foundation of an effective pricing platform.