While consumers always want the latest and greatest, retailers find themselves in a bind, wanting to clear their inventory of previous year’s models while capitalizing on the excitement of the newest models.
Dynamic pricing, when done using a pricing engine like Quicklizards, relies on an 80%-20% method for price calculation. The 80% in this equation is the work handled by the AI algorithms and machine learning techniques.
As dynamic pricing has proven itself over time, we are starting to see the concept push its way into new industries
With just about a week to go until the end of the holiday shopping season, many retailers are finding themselves stuck with overstocked products that didn’t sell.
Using data collected allows retailers to take advantage of opportunities, and turn real-time data into profitable business opportunities.
It’s clear that the medium should have a large impact on the price presented to the customer.
Retailers should be open to changing their prices as often as needed
The taxi’s surge charge is designed to maintain a balance between supply and demand. As the surge price multiplier increases, the number of people willing to pay the surge fee decreases. When done right, the result creates a perfect marketplace, where there are enough taxis to satisfy the demand.
The holidays are just a few weeks away. Before you know it, Black Friday, Cyber Monday, and 5 weeks of intensive retail activity will be here
Calculating the exact commission level to maximize profits is anything but simple
Pricing strategy, employee roles, and process workflows all must evolve for the transformation to yield its benefits.
Dynamic prices uses different algorithms to help organizations reach their profit and sales targets
savvy retailers are embracing the digital transformation to their pricing
The five stages of pricing maturity run from manually calculating prices by hand all the way through AI and machine-learning generated pricing
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