When will your customers pay to save time?

Dynamic pricing allows a company to make offers that maximize revenue based on consumer preferences and available capacity. But how do you know what it takes to have a customer deviate from a free solution to paying to save time?

If you set prices too low, you lose revenue and potentially generate more demand than your capacity. If the price is too high, then revenue is lost, and users become frustrated – impacting the brand. There are many cases in which pricing can be used to influence demand to match capacity dynamically. Whether capacity changes over time (i.e., seasonal products) or demand changes (i.e., energy consumption or highway use), managing demand via dynamic pricing presents opportunities to manage demand and/optimize revenue.

Express Toll Lanes along I-95 in Maryland Case Study

In this case of the Express Toll Lanes along I-95 in Maryland, EurekaFacts developed a model that not only informed dynamic pricing based on consumer preferences at various typical conditions, but it was specifically crafted to measure the value of time. That is the price that motorists are willing to pay to save five, ten, or fifteen minutes in their commute. The resulting model informed the rates that could be charged under various conditions so that the lanes have express traffic to meet capacity and revenue targets.

Furthermore, once the model was applied to long term traffic flow forecasts, the total projected revenue was used as the basis for issuance of bonds that would finance the road. But that is another story.

How is dynamic pricing determined?

EurekaFacts examined the introduction of express toll lanes along a segment of the I-95 corridor. More specifically, we developed a survey instrument to capture the stated preferences of motorists to use a toll transponder (EZPass) if they did not already use one. Then, we examined motorists’ intent to choose the express toll lanes to save time given specific scenarios presented to them. Some of these were road conditions such as rain, and others were related to the time of day and the purpose of the trip (morning commute, evening commute, leisure trips, etc.)

Since this decision is dependent on prices, we examined the likelihood of choosing the express toll lanes given the applicable conditions, at various price levels. We collected survey data using multiple modes for four weeks. We conducted advanced analytics to model stated preferences at various price levels and developed a data model that allowed planners to estimate the percentage of motorists that would likely choose the express toll lanes. Blending the model with projected traffic growth informed the right price points to set to generate the target level of demand. Since willingness to pay also varies with affluence, frequency of use, and general demographics, we collected data to control for these factors, too. The resulting solution offered the State of Maryland a way to implement dynamic pricing that they could use.

Where else is dynamic pricing used?

The applications for this type of effort are many. Dynamic pricing benefits can be significant not only for revenue optimization but also to align demand with capacity and manage brand perceptions around pricing. Dynamic pricing is also known as surge pricing, time-based pricing, and demand pricing. Time of day/time of use pricing and critical peak demand management also use dynamic pricing. Dynamic pricing examples include ridesharing services, energy pricing, hospitality, entertainment, and transportation.