In general, it takes us 2 to 3 months to offer you our first optimized price recommendations! Implementing a pricing tool such as ours requires several configuration steps before it can be operational.
The different stages of implementing a pricing solution:
1. Making data available
Providing data feeds is the first step and often the most time-consuming. It is necessary to have orderly and accessible data in order to minimize the implementation times of the pricing application. During this stage, the PricingHUB IT team exchanges a lot with the client’s team in order to achieve accessible data flows.
Once this information is shared, we can start implementing the pricing tool on our side!
2. Integration of data flows into the application
For this crucial step, our teams generally need 2 weeks from receipt of all the data to correctly integrate the different data flows that our clients make available to us.
3. Creating portfolios
That’s it, our pricing solution is ready, now it’s time to create your product portfolios and start optimizing your prices.
Two options exist:
- Price optimization by following competitive alignment rules (called rule based pricing)
If you have chosen to use this method of optimizing your prices, once your portfolios have been created and your rules configured, you will be able to access your first price recommendations very quickly! In fact, our artificial intelligence algorithms are able to provide you with recommendations the next day.
- Price optimization according to your objectives
If you have chosen to take advantage of the price sensitivity of your consumers to achieve your business objectives, once your first portfolios have been created and your constraints defined, an experimentation phase is necessary to test the price sensitivity of your consumers. This period varies but it is recommended to respect a learning phase of 2 to 6 weeks for the pricing algorithms to perfect. The longer the phase, the more we will be able to test multiple “price points” and the quicker it will be possible for us to reach the optimum.