The restaurant industry has long lacked the insights available in other industries. That’s because the market is incredibly fragmented and lacking much of the sophistication that other industries have developed when such data is made available.
For example, in the hotel industry the STAR report is nearly universal, available to large chains and independents alike. Furthermore, the hotel industry knows how to leverage the STAR report data to optimize REVPAR, or revenue per available room.
Not that the restaurant industry hasn’t tried to produce something of value, but there have been three core failings of status quo benchmarking attempts:
- The available data isn’t robust enough
- Benchmarking providers aren’t engineers
- Resulting actionability is non-existent
The available data isn’t robust enough
There have been multiple attempts to create restaurant benchmarking tools but there’s only one that we’re aware of still standing: Black Box intelligence.
Founded over 25 years ago by a chain restaurant operator, Black Box gathers self-reported sales data from restaurant chains.
Inherently this gives us significant pause as data scientists.
First, the classic adage goes crap-in, crap-out. If you’re being fed self-reported data without sufficient auditing you cannot possibly have confidence in the underlying data, let alone any attempted abstractions derived from such data.
We would be more convinced in the accuracy of their benchmarking variance if there was a covariance matrix linkage to other broad-based economic data but that doesn’t seem to be happening.
But more concerning is the complete absence of non-chain data.
The restaurant industry has a very long tail. For example, Walmart represents 25% of US grocery spend, and with another five grocers one can get a handle on 60% of US grocery spend. In the restaurant industry no one operator represents 25% of restaurant volume, and even cobbling six operators together won’t get you to 25% of restaurant market coverage.
Independent restaurants represent at least half of industry spend, with some sources showing their representation to be as high as two thirds.
That’s a lot of data to be missing, especially when distribution of chain restaurants is clearly non-uniform.
Per the below graphic, trusting chain-only benchmarking data in certain counties of California would mean that you’re ignoring 84%+ of spend data in making decisions.
Uh, relying on this data is a dangerous business practice.
We get that something is better than nothing, but this is very sloppy – if not outright perilous – data science.
Here’s a really easy math example.
Let’s say your sales are down 1%. You want to know if that’s worse than the market.
You go to Black Box and see that your “market” is down 2%. You feel awesome.
Well, Black Box’s coverage of your market is 5% of sales since it’s chain-only restaurant data.
What if independent restaurants are instead up 4%?
Here’s a quick weighted average calculation for your market that would be accurate:
5% * (-2%) + 95% (+4%) = +3.7%.
Whoops.
Guess you shouldn’t be celebrating.
Benchmarking providers aren’t engineers
The restaurant benchmarking products that are available weren’t founded by engineers and data scientists and accordingly we feel that they lack the necessary rigor that we believe the restaurant industry needs.
Restaurants are a very, very challenging line of work.
Long hours.
Perishable inventory.
Thin margins.
There are lots of things going against the restaurant industry, and a flimsy benchmark isn’t doing anyone any favors.
Giving someone erroneous data to make decisions might be worse than giving them nothing, frankly.
Imagine if some guy got in a car crash, crawled through gasoline, then fell into in a cave on the side of the road.
The line of thinking from the existing benchmark provider is to give this guy a lighter for some luminescence but they’re totally ignoring the fact this dude is dripping petroleum fumes.
Resulting actionability is non-existent
Because the existing benchmarking tools were not built by data scientists they never made the tool actionable, which is precisely what a low margin industry needs.
Ask yourself these questions:
- Does my benchmarking tool give me daily resolutions – because what happens on a Wednesday is different than what happens on a Friday?
- Does my benchmarking tool quantify in dollars my market opportunity by store and region?
- Does my benchmarking tool tell me WHAT my problem is – traffic, sales, frequency, recency, or average check?
- Does my benchmarking tool tell me HOW to fix my problem?
- Does my benchmarking tool measure my actions to tell me if I outcompeted the market?
Aben has taken higher fidelity data from direct card network and POS partnerships to project total spend at a local market level (i.e. a two mile radius around a store) and deliver confident prescriptions about what your problems are, what they’re worth, what you can do to fix them, and if any action you took actually moved the needle.
While we can’t give away years of PhD-level data science for free, we are giving away swaths of the underlying data to give the industry a much more statistically valid benchmark with which to make decisions.
No more worrying about a self-immolating benchmark product: we’ll give you the spotlight you need to escape the cave.
What is Aben providing gratis?
For starters – and in our opinion the biggest win for the industry – we’re providing statistically accurate data so you can be confident in making decisions. Pursuant to the government’s map of chain restaurant distribution above, you can see how dangerously misleading chain-only data can be when used for decisioning.
There’s no concern about self-reported data either since Aben’s data automatically sees nearly every credit card swipe and marries it with cash and check tender types (POS data + surveys) to project full market sales trends.
Aben’s free benchmarking comes at state and DMA level resolutions and will have sales data available on a 9-day delay in year over year trending.
At least to start with.
Aben has a lot more data than this, but we can’t give away what other companies pay for.
Want local market benchmarking (i.e. more granular than DMA and where you customers actually spend), in your segment (fine dining, QSR, etc.) across more than sales metrics?
That requires an investment.
Want to measure your actions against competitors and see if you’re taking share of wallet?
That merits an investment.
That necessitates an investment, too.
At the very least merchants can be confident that they’ll have accurate data for a true pulse on industry dynamics.
To claim your free benchmark, just go here and sign up with your business email.
That’s it. Truly.
The restaurant industry is hard enough without a looming recession.
Hopefully Aben’s free benchmarking can lessen the burden.
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