Pricing that follows demand, and engines for your everyday decisions
With one result in place and the whole picture clear, it's easier to move the rest. For many clients, the biggest step is a pricing engine built on demand forecasting, one of the things we do best. On the same data, we add more automations and agents for the decisions your team makes every day.
- Your prices come from last year's list and gut feel.
- Your peak periods sell out early, at prices that were too low.
- Your costs have changed, but your prices haven't.
- 01
Read the history
We read your sales, booking or usage history.
- 02
Forecast demand
We forecast demand for each product and customer, taking in costs, seasons and capacity.
- 03
Propose prices
The engine proposes prices within limits you set. Your team sees why each price was proposed and makes the final call.
More automations and agents
Once the data is in order, each new engine is quicker to build: suggesting what else a customer is likely to need, flagging customers who are buying less, or an agent your team can ask about any product, price or order, with a source behind every answer.
- Engines that run on your own data, inside your own systems.
- Prices and suggestions your team can see the reasons for.
- Code and documentation your own developer can work with.
Our team built a pricing engine that runs about 1,000 demand forecasts for more than 10 million users.
Fixed price, from 50 k€.
Should we buy a pricing platform instead?
Maybe later. Pricing platforms are built for very large companies and take months to roll out. We start from the data you have now, and what we build can feed a platform later.
Will prices change automatically?
Only if you want them to.
How much history do we need?
Enough for your patterns to repeat, and we check that in the diagnostic.
Is this for B2B or consumer businesses?
It works for both.
- hello@loimigroup.com
- Loimi Group