How to become a surcharge heavyweight
by Calum Robinson, Economist, Cash Management Solutions
The vast and diverse nature of a nation like the U.S. means that competition differs greatly between ATMs. As a result, we see deployers assess individual ATM competition levels. This information is then used to set what is believed to be an appropriate amount of surcharge per transaction based on the level of competition.
Obviously, an ATM in a sports stadium, theme park or resort hotel is deemed to be able to command a much greater level of surcharge than an urban ATM with several competitors.
This very simplistic example highlights the need for surcharge to be market appropriate, but what if this analysis was broken down further? How would your surcharge be impacted by the wealth of the area? The time of day? User demographic? Economic environment? Average transaction value? Local events? The number of cash-only stores? The list goes on …
Deployers who consider all these factors and build an optimal surcharge strategy stand to increase their revenue by approximately $1,000 per ATM per year.
Those that fail to grasp this could be left in a fight for survival as its profitability is hit in a currently challenging environment.
Each of your ATMs has its own micromarket radius full of variables that influence its respective demand. Analyzing how these variables differ between locations and how they impact ATM demand is the key to unlocking the optimal level of surcharge for your network.
If the surcharge per transaction is too low, you are leaving money on the table, and if the surcharge per transaction is too high, your customers will go elsewhere. The purpose of optimization is to get this delicate balance just right, resulting in a maximization of revenue.
The example below highlights the effects of surcharge optimization on two ATMs in separate locations:
ATM 1 is in a highly competitive area, surrounded by well-established chain stores that process both cash and card transactions.
ATM 2 is in a remote gas station with an inherently less affluent user demographic and particularly high average transaction value.
Both ATMs began with the same level of surcharge, yet when optimized to reflect its micromarket variables, surcharge per transaction decreased at ATM 1 and increased at ATM 2. The result was an overall increase of 16 percent in the deployer's surcharge revenue.
By understanding how each ATM's locational traits impact its demand curve, you can deduce how an increase or decrease in surcharge would impact the ATM's withdrawals.
This economic principle is known as price elasticity of demand and is inferred by the demand curve for a good or service. Different traits result in different demand curves, and this means ATMs having varying elasticities and optimal surcharge rates.
Price elasticity of demand
ATM price elasticity of demand measures the responsiveness of the number of withdrawals (the demand), to a change in the level of surcharge (the price). As we can see from the above example, each ATM has a different elasticity, which is realized through its respective micromarket variables.
By forecasting and understanding these variables and subsequently the ATM elasticities, you can set a level of surcharge per transaction that is optimal for each ATM.
Inelastic ATMs will see an increase in surcharge revenue from an increase in the per transaction surcharge. This is because the number of withdrawals will fall by a less than proportional level to the increase in surcharge per transaction. On the other hand, elastic ATMs will see an increase in surcharge revenue from a fall in the per transaction surcharge. In this scenario, the increase in the number of withdrawals outweighs the reduction in surcharge per transaction.
The point of this article is to highlight the need for targeted micromarket analysis beyond a single variable such as competition. The sunburst diagrams provide just a few key traits that impact elasticity, they also highlight how ATM traits can differ greatly not just between sectors but also geographical location. As a result, we can see similar but by no means identical sunburst shapes.
How to do it
To accurately maintain an optimized surcharge strategy deployers must continuously assess the micro market variables. Deployers must be dynamic and proactively search for changes to the variables, no matter how small.
An adaptable and dynamic philosophy is key to maintaining an optimal position in a volatile economic environment, however, if you really want to gain an edge it also requires looking beyond the here and now. By forecasting future changes, deployers can capitalize by implementing the appropriate surcharge as it happens. By only reacting to changes deployers can end up missing out on large revenue opportunities, e.g., optimizing surcharge for events.
Unfortunately, the level of dynamism in a surcharge optimization strategy is dependent on the size and pricing stance of the deployer. A dynamic surcharge strategy with an independent surcharge for each individual ATM would provide the best results, however, this is often unrealistic for large super-deployers and those deployers who implement a network surcharge rate.
You can still operate a more optimal service without full implementation of the ideal scenario. A more appropriate solution for a super-deployer, for instance, might be a banded system categorizing ATMs by core characteristics such as sector and competition. This encapsulates a substantial proportion of the optimization improvements available to deployers while avoiding the costs of performing individual optimization analysis across every ATM.
Deployers with a blanket surcharge rate can use ATM weighting to their advantage. By giving each ATM a weighting based on its potential surcharge revenue, the deployer can optimize the broader network surcharge rate to take into consideration the respective revenue provided by each ATM.
This article was reprinted with permission from the CMS Global Cash Report, Summer 2017.
Companies: Cash Management Solutions