Debunking the myths of fuel price optimization and AI

This article debunks the myths surrounding AI and data science in fuel pricing. The truth is that fuel price optimization is not a dark art. It’s a subtle change in pricing strategy that should remain predictable to your loyal customers, and undetectable to your competitors.
Debunking the myths of fuel price optimization and AI

It’s mathematics — not magic

There’s much perceived myth and mystery surrounding fuel price optimization. Often thought of as a “dark art” or “black box”, many people are under the impression that price optimization is a complex solution that will generate new and unexpected prices for your products at whichever price position it decides for you — leading many to distrust the process.

This misconception is understandable. Fuel Pricing Managers are analytical by nature and deal in facts, but they’re unlikely to be data scientists or advanced mathematicians, therefore artificial intelligence (AI) algorithms can seem intangible — and often scary.

The truth is that fuel price optimization is not a dark art.

Price optimization is an AI and science driven process that produces an optimal price position driven by your performance and targets. It should never generate wildly unexpected results but allows you to carefully broaden the price position you take in the market to maximize your profitability. It’s a subtle change in pricing strategy that should remain predictable to your loyal customers, and undetectable to your competitors.

Unpacking the black box

As a Fuel Pricing Manager, it’s essential that you’re commercially astute and well versed in analyzing performance data — but you don’t need a master’s degree to understand the mathematics used in price optimization.

The word “intelligence” can be misleading — artificial intelligence does not think for itself, it doesn’t have a prebuilt logic that applies its own ideas to your pricing models. It learns from the data you provide it. Nothing it calculates is outside of the realms of human abilities. It’s not simple, but it is just mathematics.

The beauty of using AI in fuel pricing is that it will analyze each of the required data-points and refresh the pricing model with the latest performance and market-based calculations. So, when it comes to generating prices using the model, they’re optimized instantly ― providing fact-based, data-driven prices, at speed across your gas station network.

This image shows a simplified version of Kalibrate Pricing’s data science approach. It shows the different elements that are analyzed, calculated, and applied in order to reach an optimized price. Each of these elements can be combined and calculated to provide a price that’s optimized for every individual site, and every single product at that site.

Fuel price AI data science calculation

This is the sort of process that your Pricing Analysts would do if they had access to all necessary data. But think of the time it would take to analyze and calculate each of these factors for every product across every site in your network.

Utilizing price optimization allows you to effectively analyze and respond to data, at scale, while preserving valuable man-hours.

Kalibrate Pricing is a trusted platform that utilizes AI to deliver optimal pricing decisions for your sites. Over 600 ,000 prices are sent from its systems every day, with live pricing across more than 65,000 sites in over 40 different countries.

If you would like to know more about price optimization and using AI to aid fuel pricing, download Fuel Price Optimization 101

 

 

 

 

 

 

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