Price f(x) offers an ML-based price optimization framework to improve the product portfolio and pricing of businesses.
They offer “segment-specific” optimized pricing and price recommendations which can be exported to and delivered in multiple formats including but not limited to ERP systems, CPQ, and price lists. With Price f(x)’s price optimization software, businesses can obtain and model the data they need for price optimization, and create machine learning models for segmentation. Their software can also test different pricing methods through simulations, and analyze the results to provide accurate pricing recommendations for products.
Price f(x) assures businesses that their software can provide price guidance to optimize margins, promotions, assortment, stock, and more. Their software is catered to product marketers, business analysts, and data scientists. Though their software can use data to run simulations to provide businesses with accurate price recommendations, the recommendations can be manually rejected or changed according to the user, allowing for full control over the pricing and repricing of products.
- Pricef(x) was fairly easy for us to start using. Our team didn’t need much training to figure out how to use it. Modifying it is another story, though. We found that process very complicated in comparison to Competera, for example.
- There are a few positives and negatives that come along with this software. The interface is clunky at best. A lot of our team members complain about how slow it can be. Their upgrades also aren’t free even though I think they’re very needed, since the platform needs some work. It is very customizable, and not too hard to learn how to use in the first place, but considering the other difficulties we have had with it, I would only say that it is “okay.”