Embracing location profitability as a pivotal measure of the crypto ATM network performance

In 2021, the crypto ATM market in the US grew by 8-10% monthly. The number of machines installed by the top 10 operators covers more than 75% of all the crypto ATMs across the country. Remarkably, in the first quarter of 2022 there was a noticeable ramp down gravitating to ~3.2% in February, ~2.2% in March, and close to zero growth in April. That might certainly be driven by a number of factors like crypto price fluctuations, seasonality, new players entering the market, internal cost pressures, and so on. But one peculiar reason behind all that might actually be the raising understanding that "bigger doesn't necessarily mean better". In other words - the hectic placement of crypto ATMs seems to no longer generate the projected sales and margins but rather it has increased the bottom-line and related costs.

Two major topics come to my mind:

• How to identify and capture the high-performing locations (current and prospective)?
• How to measure location profitability itself?

One might say that it's a subtle art to finding the cash-cow locations in the crypto ATM business. And I agree – that is to some extent true. Though, it's not rocket science as well. The utmost thing here is getting clarity on the attributes that distinguish the leading locations (and those close to them) from the rest of your network landscape. For that purpose, it's crucial to delve down into a number of nuanced details. To facilitate this research, I've made some guiding questions to explore for every single crypto ATM location that you have, i.e.:

• What does the location look like and what is there (a mall, a gas station, a post office, a grocery store, etc.)?
• Does it belong to a metropolitan, micropolitan, or other areas?
• What is the population density and income per capita / household there?
• What are the operation hours of your crypto ATM (9/5, 24/7, etc.)?
• How many customers visit your crypto ATM, when (in terms of time), how frequently and how much do they spend per visit?
• What is the ratio of returning vs new customers?
• What is the effective uptime per month (actual time in operation net of any sort of issues that impairs functionality, i.e.: no internet connections, empty / full cash drawer, functional glitches, any kind of damage, etc.)?
• What are the competitors around and how their offerings differ from yours (in terms of fees, UI/UX, the convenience of the location itself, hours of operation, etc.)?
• Which external information from the public domain might help you to better understand the above?

Once you are able to answer all the above questions, it's essential to gather them, collate the embedded data, and figure out dependencies, correlations, anomalies, etc. Having that on the table will help to scrutinize, and both outline the key attributes driving profitability, as well as the common issues. The latter ones which, if resolved, would help to seize the underutilized profitability potential of many other locations that you have in your portfolio. Consequently, this will ultimately enable you to raise your company's tangible value. You can even go further - compare your locations and those of the key competitors (based on the publicly available data) to see how that correlates with the attributes pertaining to your machines. For instance, by comparing your poor- or under-performing crypto ATMs with those of the competitors that they have shut down / or relocated, and by means of many other scenarios of comparative analysis.

Another essential step is engaging your scouts to search for locations with attributes that indicate the utmost potential for high financial performance. Once found - install your crypto ATMs there for a pilot and monitor their performance once they are turned on. That would be a much more sensible and reasonable investment rather than any ad hoc and straightforward expansion.

Second topic raised - how to measure the location profitability? First of all, the whole work on this matter should start in parallel and alongside an exploration of my first question described above. Such effort means creating a holistic and comprehensive analytical model that would incorporate all the aforementioned data and will enable the highlighting of both existing and prospective high-performers as well as promising candidates. If done properly, such a model could also include relevant estimations of probabilities, helping you to better assess and manage your appetite and tolerance to key embedded risks.

Doing all this manually might certainly be an option. But, given the span, scale, and scope of data that needs to be processed, and the volume of analytical work to be done, choosing this way will most likely lead to multiple struggles, mistakes, and misinterpretations. As such - a much more safe and reasonable option to follow would be to either build an in-house or engage external expertise to set it all up and make it smoothly running.

That's exactly one of the analytical angles that we work with within ThinkTech and this is how we can help your crypto ATM business to reach new heights.