EVOLUTION OF DYNAMIC PRICING
Dynamic pricing is an AI-driven process of setting optimum prices in order to maximize the revenue, increase profit margin or gain other business goals. Driven by large volumes of data, we are operating in a world that demands extreme customization and personalization. A sophisticated price algorithm is a customised heuristic, integrated within a pricing system. Furthermore, it enables a pricing team to implement and adjust differentiated price strategies across many different products and customer segments.
Before machine learning pricing algorithms how did businesses set and manage price?
Before algorithmic pricing, companies focused on margin targeting using cost-based pricing. Unfortunately, margin-based pricing or cost-based pricing leaves ALL businesses vulnerable to revenue loss, lost profit and customer flight. Cost-based pricing is like a demand algorithm that is very rudimentary. Basic algorithms such as cost-plus pricing placed companies at risk. Either they drive up rates too high – resulting in volume loss – or they set prices too low – leading to loss of revenue. So in a way, there has always been algorithmic pricing around. It has only become more sophisticated than it used to be.
Why is an algorithmic pricing solution is better?
Usually pricing strategies were based on manual and intuitive calculation based on human-centric analysis on cost. These strategies have human-errors involved. To overcome limitations, dynamic pricing algorithms were developed. A new generation of highly accurate and easy-to-use solutions appeared. A dynamic pricing solutions are now capable of considering cross-elasticity and demand fluctuations while processing billions of data points at once.
You may ask how are we different from a pricing consultancy?
Of course, pricing consultancies typically identify high-level price strategies and benchmarks that form a guiding stone. However, with an algorithmic pricing solution that we have to offer it gives you an optimal benchmark per deal per sale!
How does a dynamic pricing algorithm work?
Dynamic pricing algorithms create flexibility to set prices targeting different target points by shaping an optimum value offering based on market trends, demand fluctuations, customer behavior, purchasing power, and other key factors.
The majority of pricing algorithms use historical sales data based on which the demand function is estimated. The functioning of a pricing algorithm is based on four main stages:
- Historical data on price points
- The demand function is build based on identified dependencies.
- State-of-the-art math processes dozens of pricing and non-pricing factors to generate optimal prices.
- After the recommended prices are applied, the algorithm goes through the cycle again taking into account the latest repricing results.
You need an algorithmic pricing solution!
Switching to algorithmic pricing requires time, resources, and efforts. Each business has its own approach and it’s not always easy to choose the right dynamic pricing engine. We believe that in a rapidly changing world of pricing and AI the solution’s time-to-value is crucial. Numbers always speak better than words, so try our dynamic pricing engine to boost your business.