As mentioned above, the company changed prices once a year or less frequently.
The sales history of any book from the pilot test group was
as: "For the last 12 months, a book X had the same price, equal to Y, never changed".
The retailer's experts defined a price range permitted as
where Y is the initial, manual calculated price.
As well, they set an additional constraint:
Y+50% couldn't be higher than the printed book market price.
Then the Imprice AI-driven algorithm began the demand sensing. Within the set price range, (Y-10%; Y+50%), the algorithm started to raise and reduce prices, evaluating how it affected sales.
Preliminary demand sensing took 4 weeks, because there was no price change history, but only "For the last 12 months, a book Xi had the same price, equal to Yi, never changed".
Prices were allowed to change one time in 3-4 days, because the retailer's sales cycle was equal to 2 days.
Due to that, mostly, customers didn't see price change during decision-making. It helped to avoid any negative reactions.
The Imprice AI-powered algorithm set prices fully automatically. A pricing specialist only had to monitor the results.
The second step, a preliminary demand sensing, was completed in 4 weeks.