Dynamic Pricing: Using Python to Edge out the Competition
25 Aug 2022
When it comes to competing in the world of retail, setting fixed margins on top of costs is no longer cutting it. Pricing products and services has become a delicate dance, which businesses have to approach with utmost thought and deliberation. Companies are using increasingly sophisticated tactics and employing big data and Artificial Intelligence to continuously adjust prices in response to real-time supply and demand. This enables businesses to constantly keep atop the latest fluctuations and have a better understanding of the market. It is no wonder then that organizations are willing to invest in dynamic pricing software that will help them monitor, estimate, and manage their pricing strategies. This is exactly what we were tasked with by one of our clients.
Dynamic pricing, also referred to as demand pricing or time-based pricing is a strategy that has taken over ecommerce. Our client was looking to create a solution that would apply this concept to predicting airfare volatility and offer highly customized pricing to its customers in order to maximize revenue and, at the same time, provide more value to its clients. Now, more than ever, as the world slowly recovers from the pandemic, airlines are in no position to leave money on the table, which is why their revenue management teams are pushing to invest in software that will help them manage the pricing war.
Our client company was looking for skilled Python developers to join their distributed team in coming up with a predictive airfare calculation tool. Within the framework of the collaboration, our team worked on developing a pricing solution that would utilize all of an air carrier’s real-time and historical data (flight schedules, seat availabilities, fare structures, promotional calendars, etc.) in order to calculate fares dynamically.
Our dedicated Python team assisted our partner in creating a solution that takes into account all possible circumstances at the time of an airfare request, such as market conditions and the buyers’ specific behavior in order to produce a highly customized price.
By anticipating the buyers’ willingness to pay for not only in-air but also non-air products and services, the solution calculates the dynamic price as well as combines it into lucrative bundles for customers (e.g. hotel deals, event tickets, etc.), thereby boosting customer experience.
- Automatically adjust for competitive conditions
- Dynamically adjust by competitive segment, channel, or market
- Adapt to individual user behavior and preferences
- Legacy compatible
- New delivery capacity
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Our partner considered a multitude of factors when selecting a dedicated Python development team. Having assessed several software companies, the client ended up selecting VOLO based not only on our team’s professionalism and expertise, but also on our time zone and proximity to their main customer in Dubai, as the job required on-site activities and continuous support.