With the advancement of pricing automation technology has come a deluge of content focused on the merits or downfalls of intraday pricing. And with all that chatter in the fuel retail space about intraday pricing, our thoughts on the matter are more pertinent now than ever. So, we are here to review those thoughts, beginning with our take on the value of intraday pricing strategies.
First, let's consider how intraday pricing has emerged. Due to a strong push for automation, access to much faster, much greater computing power and more deregulated markets, intraday pricing has been portrayed as the end-all, be-all for fuel price generation. And while it may not be the panacea to every ill, intraday pricing is more than feasible. It's occurring, right now, all around you in the fuel market.
Why? What's the value? Pricing more frequently, especially with the backing of algorithmic intelligence, will keep you more closely aligned with the market. You will always be at the forefront of pricing capabilities when you price intraday. But there are, of course, some risks.
Two common objections to the idea of intraday pricing stand out:
1) Why remove the human element?
2) Won't intraday pricing increase volatility and potentially decrease margin?
Let's start with the first. It's important to understand that automation doesn't always mean removing the human element. In fact, at Kalibrate, we see the two as inseparably working together to improve your volume. Kalibrate will never support a "machine learning only" approach to pricing, because we believe that a machine alone cannot determine the complexities of fuel pricing in a way that someone who understands the relationship to the store and market can. It's critical to incorporate all of the 7 Elements of Fuel and Convenience Retail Success — market, location, facilities, operations, merchandise, brand and price — with historical behavioral data and demand forecasting in order to really understand price in all of its complexity.
The second objection is legitimate. If you are adjusting price based solely on machine learning, stability in the market will be compromised and margins typically decrease in those circumstances. To successfully implement intraday pricing, you need more than what the numbers and machine learning models can provide (which brings us back to that first objection). Beyond machine learning, you need to understand your strategy relative to your competition, how you can effectively implement that strategy and how you can monitor on an ongoing basis. You also need to get to the heart of incorporating data into volume targets, ensure you're leaving out those times when it is not acceptable for an algorithm to make pricing decisions (such as during price restorations, certain events or market conditions), and validate that your experience and knowledge is incorporated in automated pricing strategies.
Obviously, a lot of work goes into a successful intraday pricing strategy. The bottom line is that intraday price generation, including optimization, is real, feasible and occurring constantly. Price generation will occur as often as new data triggers the process. Only with both immense computing power and immense business knowledge can you achieve the level of optimization, and the margins, you desire.
Kalibrate deploys a range of pricing techniques and can advise on which are most appropriate for your site and your market, be it simple rules, sophisticated rules, rules based on demand modeling or optimization.
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