When deciding on what the price should be, Sales teams are used to considering fairly static factors like customer size, purchase frequency, geography and whether it is a spot order or long-term agreement.
But there are increasingly more volatile factors that must be considered, like the price the competition is charging and the cost of raw materials.
Then there are truly dynamic factors that can influence prices quite considerably, like available capacity or inventory levels.
When you consider all these factors, it is almost impossible for sales teams to gather all this data and process it in time, to deliver optimal prices to customers.
The PROS platform has the perfect set of capabilities to help, watch this demo to learn how the Real-Time Pricing Engine, part of PROS Smart Price Optimization and Management can help your business handle market complexities in real time.
Full Transcript
Many B2B companies operate in highly competitive markets.
Within these markets, the prices that their customers are willing to pay will vary depending on many different factors.
Companies at the top of their game want to consider a wide range of factors when determining optimal price points. This places a huge burden on their sales teams. When deciding on what the price should be, sales teams are used to considering fairly static factors like customer size, purchase frequency, geography, and whether it is a spot order or long term agreement. But there are increasingly more volatile factors that must be considered, like the price the competition is charging and the cost of raw materials. Then there are truly dynamic factors that can influence prices for sales teams to gather all this data and process it in time to deliver optimal prices to customers.
The PROS platform has the perfect set of of capabilities to help by combining the power of market leading artificial intelligence with the speed and processing power of a real time pricing engine. Optimized dynamic prices can be delivered in real time wherever they are needed.
PROS helps us understand how different attributes impact the price a customer is willing to pay and ranks them according to how influential each one is.
Here is an example of model results for a food wholesaler.
We can see that the current inventory level is one of the most influential attributes impacting pricing behavior.
This attribute order is not fixed and varies from transaction to transaction.
We also see there are many other attributes that influence the price a customer is willing to pay.
In order to feed the current inventory levels to the model, we create a data repository, a lookup, where we can get a real time feed of the current inventory levels.
As soon new values are passed through due to the integrated nature of the PROS platform, they are immediately used along with all the other relevant attributes to generate new price recommendations.
Price recommendations are made available to applications that need them through a highly performant always available API.
PROS also provides a user interface that enables a user to simulate what the price recommendations will be for each specific scenario.
This allows us to check how different inventory levels will influence the prices.
Let’s check the price of beef back ribs for restaurants group when we have plenty of inventory.
The AI is recommending a price of twenty five dollars and ninety cents and we can see that knowing the inventory levels are high result in the customer being willing to pay less than if supply had been tighter.
If we now look at the same scenario, but assuming that stock levels are low, we see that we can now charge twenty eight dollars and seven cents and that it is the low inventory level that is the main factor driving this ability to get a higher price.
PROS pricing solutions enable seamless price management without any delays and errors. With the pros platform, sales teams get intelligent prices delivered exactly when they need them, so they always get delivered the right price at the right time.