Jurassic Park is one of the best movies ever made. It set the special effects bar incredibly high, much as Scott Ridley’s Alien did a decade earlier.
There’s a part during the Jurassic Park “science tour” where a digitized DNA helix (Mr. DNA) explains how they make the genetic code for the dinosaurs – video below.
If you don’t want to watch this awesome video, here’s the synopsis: Jurassic Park scientists have dinosaur DNA from petrified mosquitos and they use frog DNA to plug in the gaps. The combination produces the megafauna dinosaurs.
This analogy is how we explain Big Data to the average person: Big Data grabs useful tidbits of information that you don’t have to augment what you know (and hopefully execute). We term it the Jurassic Park Effect because the analogy is pretty clear.
People can use our explanation to render appropriate imagery for how Big Data works at a basic level, but unless you tell them why it matters to their life or business – usually in dollars and cents – they lose curiosity. And we don’t blame them.
As Dale Carnegie famously said,
You can make more friends in two months by becoming interested in other people than you can in two years by trying to get other people interested in you.
Brick and mortar has suffered from an absence of data rigor at almost every level. Even the application of data within a store’s four walls (which can sorta be defined as Big Data) is limited. In fact we authored a central piece in RSPA’s April/May version of Connect Magazine to discuss what Big Data is and what merchants should be demanding from their solutions providers. The article discusses what merchants should be doing with their own data today, and what it’s worth to their top and bottom lines. We highly recommend reading our article if you follow our online content.
One thing we lightly touched on in the RSPA article – and which we’ll cover in more detail here – is what can be done with aggregate Big Data.
Aggregate Big Data is known as a data lake in the data science world. A data lake just holds lots of data with field tags so it can be processed when needed. A way to think of this within the confines of retail is with checks: every check has an item, price and a few other fields. So a data lake of check data would have rows upon rows of data in the item “column” along with columns of the other fields you might want to flag.
Why should merchants care?
Amazon’s data lake is its biggest advantage. That Amazon sees 1 of every 2 online purchases is enough to help it drive the right product assortment, pricing and customer recommendations. Amazon didn’t do this overnight: it meticulously used its burgeoning data lake to create its advantage.
It’s not that Amazon is killing brick and mortar so much as brick and mortar isn’t using data as well as Amazon, thus killing themselves. We won’t get into the semantics on this article, but brick and mortar needs to think about how it can compile and use data to its advantage.
This is where Dale Carnegie tells us to explain why it matters to the merchant.
Merchants that tap into data lakes are able to:
1. Fine tune hours of operation to meet foot traffic patterns in their area. This means taking advantage of well-performing hours to boost profitable revenue, while curtailing extended hours that are unprofitable to the business.
2. Identify new item trends and associated prices. When Furbies were hot, or Adkins was in-vogue, knowing how these new items would perform helps determine inventory and offerings. Pricing is also critical, thus aggregate data can help find pricing schemes that create higher velocity. The net result is increased sales.
3. Suggest upsells. Looking across the shopping baskets of many businesses can determine what items are selling well together, and where opportunities arise to increase profit. If item B performs horribly by itself but is incredibly profitable, knowing that offering item A will boost the sales of item B by 50% would be worthwhile. If done properly there’s not only a lift in sales but in profit.
4. Harness promotional recommendations. Looking across multiple outlets helps to determine what promotions guests are responding to and, if customer data is being collected, the types of customers responding to said promotions. Realigning marketing accordingly drives conversion and revenues.
Unfortunately there are no data lakes of any consequence for brick and mortar merchants. Ideally one would be looking for full transaction data (also known as SKU, or stock keeping unit) for a large number of outlets across a diverse-enough geography to represent the overall market. Even better would be aggregate customer insights affixed to SKU purchases.
So while data lakes are enormously valuable, it’s the sophistication of the brick and mortar merchants that keeps them from being built. As we’ve discussed in prior articles, many leaders in this industry are simply ignorant to what’s possible. As Henry Ford said,
If I had asked people what they wanted, they would have said faster horses.
That’s why choosing the right POS system will be critical for realizing the benefits of aggregate Big Data.
Asking merchants to disclose SKU data, at least in the restaurant vertical, has never happened at a large scale. Sure, some third party providers are accessing said data to perform a service or deliver a product, but the amount they have is paltry. Even companies who are building indexes for benchmarking – think Knapp Track, BlackBox and MillerPulse – are only taking top-line, weekly revenue numbers across a very small swath of the market. Retail is little better.
Because merchants are standing in the way of their own success (we know, it’s crazy to think some of their executives get paid millions of dollars to staunchly hold these positions), one cannot rely on them to successfully carry their businesses forward. When it’s been 40 years and proven methodologies have not organically migrated over, you have to look elsewhere.
Which is why we are bullish on POS companies solving these issues.
POS companies are moving to cloud. We don’t care if that’s an iPad that talks over the internet or a hybrid operation with a local server for redundancy: POS systems are going to be connected. Once POS companies have aggregate transaction data they will be able to pool it together and solve these issues for their merchants.
Before you give us the classic merchant knee jerk of “Oh no, someone has my data?!” let’s rationally use some of those brain cells.
1. Brick and mortar is getting its a$$ kicked by online retailers who use data. The Wall Street Journal published an article noting that brick and mortar needs to start use their data to remain relevant: “Legacy retailers have to put their mountains of purchasing data to work to create the kind of personalization and automation shoppers are getting online.” You don’t say…
2. The transaction data we’re talking about here is aggregate. This means you cannot see data specific to Bob’s Bistro store # 12, or even the Bob’s Bristro brand. Data is thus productized in aggregate, much like MasterCard has build their Adivsors group off aggregate customer data sliced into cohorts.
3. As if this sort of data aggregation is only happening with cloud POS, read your existing service provider contracts more closely. Using a back office tool? Subscribed to MyMicros? Here’s language from a legacy POS since we know 99% of you don’t even bother to read what you sign:
XYZ may use and disclose transactional and system configuration information in the form of anonymous, aggregate usage statistics that XYZ derives from Your locations via Your use of the Software
Surprised? You shouldn’t be.
You’re the ones holding up market progress so your providers are finding ways to improve your own business without involving you.
But many of your service providers aren’t actually doing anything with your data… at least nothing that you can benefit from. A very legitimate question every merchant should be asking their provider is:
Hey, with all this data of mine you’re collecting, why aren’t you giving me better solutions yet?
The short answer is that most providers in this industry are former merchants, thus they themselves don’t know what to do.
However, unlike legacy service and POS providers, POS companies investing in cloud connectivity are more sophisticated. By collecting and pooling aggregate transactional data they’ll be able to produce amazingly valuable solutions. Like Steve Jobs and Henry Ford before them, they will give you something you needed, but didn’t even know you wanted. Instead of requiring merchants to figure out what to do with all the aggregate data, prescription on the part of the POS provider should be used:
“Buy 47 Furbies and list them for $19.99. We expect $1,819 in new sales for the month of January if you take this action.”
For all the hemming and hawing merchants will undoubtedly display after reading this article (or their existing partner contracts), just remind them how Amazon has kicked their rears and ask if they’re happy to let that keep happening. If their answer is yes, walk away. You can’t fix stupid.