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Moneyball For Convenience Retailing, With C-Store Expert Hiram Mac

If you’re looking for a convenience store for sale, opening a convenience store business or already own your c-store, see this interview from convenience store industry expert Hiram Mac introducing Moneyball for convenience store owners.

He’ll show you how you can use data to increase your profits:

Tell us more about c-store ’nomics?

c-store 'nomics is a blog centered around convenience retailing I started over a year ago because I hadn't seen anyone cover the industry from a 'bottom-up' perspective.

The content coming out of the major industry publications are insightful but seem to provide a perspective that's from the top looking down. At first, the blog posts were general in scope- so many issues beckoning so many thoughts on how they might best be tackled. But then adding our own trial by fire experience based narratives which fleshed out the posts with real-life examples and anecdotes made them incrementally more popular. Initially, I was just covering activity inside the c-store but then I started to release findings from fueling operations. I mean it’s no surprise the relationship is tightly coupled.

So with all of that writing momentum building, after publishing the tenth post or so I started to think why not actually start formalizing this into a real hard product book? Fast forward all the way to about a month ago, I released the book "c-store 'nomics arbitrage: mining for efficiency and opportunity in convenience retailing" on Amazon and I'm currently in the process of marketing it.

Why did you get into the convenience store business?

My dad has been in the business for over 40 years so while from an external perspective it seems like it would’ve been a natural fit for me I wasn't entirely sold at the beginning of my professional career. Having just completed graduate school with a masters degree in statistics the last place I thought I could add any value was the gas station business. As a brash 23-year-old, I quickly dismissed the opportunity making an excuse which was something along the lines of there wasn’t enough data to analyze. After working with dad for a couple of years while dabbling in many other things at the same time I decided to fully strike out on my own- mostly to learn about how business was being done in Corporate America. That led me down a path of becoming deeply interested in software development which then brought me full circle back to financial trading since economics was my undergraduate major.

After ten years of building software platforms at various companies and hedge funds, one day dad called saying he really needed some help scaling the business. Having reached the 20 plus location mark he knew that investing in some sort of technology was the pivotal strategic step forward but was at a loss for direction. Instead of buying an off the shelf solution we collectively decided that I would build one for the company. Once the infrastructure of a back office accounting and pricing system was developed along with latching in the point of sale feeds the data analysis could begin.

You could say this time around (round two) I approached the business from the perspective of wanting to solve a real problem that I knew other c-store operators were also facing.

What data have you found best increases profits at convenience stores?

Tireless analysis has become the foundation for discovering the 'secret sauce'.

We’ll try to analyze data from a myriad of sources in an effort to find connections where one might not normally find them. As an evolution, you start with performing simple transaction level data analysis then add data points like zip code based temperature readings and peak period foot traffic counts. But then you eventually hit a wall in finding any sort of meaningful insight so you throw in something off the wall like shelf sensors to create 'action' heat maps.

Uh oh. Now you're drowning in too much data. Let's get simple again. How about looking at a sibling industry to see how they’re capturing market share. Well, the data for the development of QSRs in the area can be easily found from Yelp data. Now you can see how this would snowball into even more discoveries.

So the long answer to your question is quite literally everything is for the taking.

What are some other interesting data-driven insights you’ve seen?

Hooking up a bunch of IoT devices to your store in the way that a doctor might attach multiple probes to perform an EKG sounds great in theory but you’re left with far too much data to analyze.

How about something more intuitive which starts with a simple question like the following: Is our customer base shifting to a healthier product mix?

The heavy-handed approach would involve adding keywords to our price book for every item we might deem as ‘healthy’ but the exercise becomes far too subjective. How about something more objective like individual product calorie counts? Now, of course, I’ve made a huge assumption of associating lower calorie consumption with healthier eating but one which isn’t entirely unreasonable. Therefore, if we can plot average transaction or even aggregate calorie counts over time and there’s a significant shift (up or down) then we know we might be onto something. And surely we were which became leverage for pushing back on vendors that were trying to have us sell more high-calorie food to stores which saw consumer bases that were seeking lower calorie (or ‘healthier’) options.

Does opening a restaurant inside a convenience store increase ROI? There are so many variables which factor into this. I’d say mostly yes with the condition of if and only if the restaurant fare is complementary to the store product mix. And I mention that tight coupling because the product mix directly reflects consumer preferences which ultimately dictates flavor profile. As a generalization, you’d think twice about opening an experimental vegan QSR when the fresh category has been a consistently dismal performer.

How do you maximize profits inside your convenience store?

If you think of it as an optimization problem then you know you’ll have to minimize something to be able to maximize something else. A traditional stance might suggest minimizing costs while maximizing revenue. And there’s a lot of truth to that guiding principle. But that in itself isn’t surgical. Sure it’s easy to squeeze suppliers and raise prices.

On the minimization/maximization front, you’re adhering to the formula but the approach is static. The dynamic approach involves breaking down the problem into two dimensions: segmentation and time. With the former, category managers armed with the ability to hone in on specific analytics have been able to do a decent job of figuring out the right product mix and calibrating buying accordingly. For the latter that’s where even the brightest of that bunch get stuck.

No one has a crystal ball or even the manpower to identify, capture, and monetize every trend. But we do have the ability to be reactive and therefore nimble.

If you can be quick to market after fully vetting that a trend may be worth following then don’t hesitate to run with it.

If you could have anything from a technology perspective for the store what would it be?

Funny how you ask this question from the vantage point of a POS developer. For us, that’s exactly where a choke point has historically been and will continue to be as long as we’re locked into the Dresser Wayne, Wincor-Nixdorf, and Gilbarco closed eco-system. We’ve been looking for a significantly better POS that can better handle concurrency (multi-threading), experience less latency, prove to integrate with third-party fuel equipment, and integrate well with a loyalty system. These aren’t just ‘nice to haves’, they’re very much essential to the operation itself.

What do you think about PCI Compliance/ EMV?

Long overdue and very much necessary. It's a race to the finish line until becomes a race to the bottom. We’re far behind Europe in this area and by the time we catch up, there will be another costly integration. Either way, any industry-wide initiative that protects the consumer is ultimately one that wins and gets everyone onboard.

Do you see a return on your technology investments for your stores?

You get out of it what you put into it.

Many traditional operators might see technology as merely icing on the cake but for us the more we're willing to embrace and then rely on it to drive decision making, the better informed we become. Being a statistician at heart, I like to think of decisions in terms of probabilities: which particular decision is most likely to lead us down a road of realizing a particular micro objective. While the macro one might be predicated on driving more traffic or increasing bottom line, the ability to clearly narrow the scope of the micro ones is how you'll end up getting there.

For example, if fuel sales all of a sudden started to decline, we might become far too hasty in pointing the finger at the usual suspects: incremental higher prices at the pump, stiff competition, road/site obstruction, or even inconsistent supply which might have led to outages during peak periods. But what if none of those seemed to be contributing factors? Taking a deeper dive we might see that fuel price elasticity (change in fuel gallon sales to changes in price at the pump) which tends to exhibit mean reversion has started to move out of whack. We may have gone from a period where no matter how much we raised prices, demand never saw a decline until it ultimately fell off of a cliff. Linear thinking isn’t accommodative enough to be able to understand what the heck just happened.

But human psychology might be. Psychological ‘line in the sand’ price levels can cause consumer knee-jerk reactions especially when it comes to fuel pricing. The second street prices start to jump beyond $4, consumers flee in what seems to be an epic exodus. Ok, great you’ve discovered that high prices have become the offender and simply start to lower them or just consider riding out the rough patch.

But wait for a second here do you realize you’re actually leaving money on the table? It comes from a place where there’s a deep-rooted unwillingness and inability to further segment the problem down to the specific area of decline such as specific fuel grade or an erosion in brand quality and value. It’s the step that’s rarely if ever considered because it’s just too hard to measure as a result of simply not having the right tools at your disposal. That’s where great technology comes into play.

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