Big Data for (sm)All: 5 Strategies to Make Data Work For Your Small Store

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The problem with the phrase “big data” is that people who own small businesses tend to think it doesn’t apply to them.  

I mean, sure, there’s often a massive amount of data about a large variety of criteria, which may be overkill for, say, a small quickserve restaurant.  

But strip away all the different categories that your more traditional users of big data might be interested in—you don’t need your customers’ employment or credit histories, for example—and just focus on getting quantity.  

big data for small store

Your POS, if you’ve got one worth talking about, should be recording all that data and repackaging it out to you in the form of reporting.  And it should be able to save it all in perpetuity, giving you historical insights into individual and group trends.  

When it comes to statistics and sample size, bigger is always better—the longer you’re running on your POS platform, the deeper and more precise the insights you get out of it will be.  It’s not the size of your operation that dictates the amount or quality of data; it just takes time, though probably not as much as you might think. Writing for the Smart Data Collective, some guy with the appropriate credentials noted,

“Believe it or not, if your company has been operating for a year or more, you likely have a ton of “Big Data” sitting in your company records.”

I’m not sure why any company still has records. Yes, your data has a warmth and immediacy to it that can only be achieved with vinyl, but you can’t beat the staying power and versatility of storing and accessing it digitally.

Regardless, after a year you’ll have enough information at your fingertips to start making much smarter business decisions.  This is especially important in the hospitality and retail industries, where predictability is not easily achieved.  Harnessed properly, the data you’ve got inside your POS can turn yesterday’s guesswork into today’s foresight, and you’ll find yourself better able to manage the efficiency and productivity of your staff, stay on top of inventory, and improve the customer experience by leaps and bounds.  

How so?

Well, the National Restaurant Association recently put out an incredibly useful paper with tips and strategies for small restaurants looking to use big data. The only problem with it is that it’s a mind-numbing read.  Since I’ve already gone through the trouble of reading it, I thought it’d be a good idea to summarize some of their tips here, in a way that won’t make your eyes glaze over like a balsamic reduction. That said, if you’re having trouble sleeping, hop on over here for the full read.  

Here we go, in no particular order of importance:

1. Have an understanding of what you’re looking to improve.

Big data needn’t be messy data.  It’s all well and good to run daily reports on revenue or popular items, but if you don’t have a specific thing in mind that you’re looking for, the data’s not going to help. There’s got to be some kind of problem you’re trying to address, or a goal you’re trying to achieve, and you need to know what that is to pull out the most relevant information.  Maybe your store is busy all day, every day, but somehow at the end of the month you haven’t got as much in the bank as you thought you might.  That’s a problem, and the first thing you can start to look at is where you’re spending money to get an idea of the bigger picture.

2. Where have all the flours gone?  

For a restaurants in particular, and more than a few types of retail stores, inventory is especially hard to purchase intelligently, because many ingredients are perishable. You don’t want to buy too much and waste anything, and you don’t want to buy too little and run out.

Having an advanced inventory control module in your POS makes all the difference. For a restaurant, for instance, a hospitality-focused system should store menu items as recipes and “consume” the right amount of each ingredient per order. Tracking waste is another important tool. When you begin to understand how much of your purchases make it to a plate and how much goes in the trash, your purchasing decisions become that much better. You may notice that some items don’t sell particularly well and cost you money just by being on the menu.  Other items might be hugely popular, and you realize you could sell more of them if you had the means to.

3. Stay on top of labor costs.

Spending too much on labor is one of the biggest mistakes owners make to cause a dent in their bottom line.  If your POS has a time clock feature, or you’ve integrated with a third party app that handles rostering and scheduling, you can easily identify how much any given hour costs you in labor overhead.  Read that information side by side with how much you pulled in for the same hour, and it’s pretty simple math from there to see whether it was worth the investment. You can also see which people on your waitstaff are excelling by looking at things like turnover time and average tip received.  And when you start poring through a year’s sales data, you can see in an instant when your busiest times tend to be, and make sure you’re staffing with the people who can best handle it.

4. Create more personalized customer experiences.  

Using your point-of-sale’s customer database, you can begin to really track what your customers are up to, inside your store and out. This isn’t as creepy as it sounds. Or maybe it is, but this is the world we live in now.  Social media and smartphones mean constant connection between you, your customers, and even their friends who aren’t yet your customers—special “bring a friend” or referral offers on your Facebook page can drum up new business.  And in the POS, once you’ve captured someone’s name and/or contact info, you can attach them to each check you ring up for them.  This means, over time, you’ll get to know their favorite products, and target promotions more accurately. Customer experience is improved when your sales staff can look at a customer’s profile, see trends in their past purchases, and create cross- or upsell opportunities on the fly.  For example, your employee might notice that a particular customer tends to always buy a belt when she purchases a dress, but this time she didn’t ask. That’s a good time to offer them up, and it goes a long way towards improving the customer experience.

5. More revenue channels also means more data channels.  

Loyalty programs, for example, aren’t just about encouraging repeat business anymore. Remember, every time a customer comes back, that’s not only another sale but it’s more information you can use to get another one from them. Even if you just replaced your “Buy Ten, Get One Free” punch card with a digital version of the same exact program, you’re getting actionable information every time your customer comes back. The National Restaurant Association cites the example of Pizza Hut, which uses the data it gets out of its loyalty program to understand customer purchase behavior—like where they place the order (online or instore), what coupons they’re using (from the newspaper or their email), and then they’re able to market to them using the methods the customer most prefers. Since implementing this initiative, the chain has seen a steady rise in customer retention—and if you’ve ever eaten Pizza Hut you know folks aren’t coming back for the pizza, which largely tastes like cardboard and rage smothered in cheese.

Once the playground of giant companies like Amazon or the US Government, collecting data on individuals is now well within the capabilities of nearly any business.  Cloud software has made it affordable, and in a tech landscape where complementary apps strive to play well with each other, small businesses may soon find that they’re aggregating a wider variety of datasets than they ever imagined possible.  But even if they just stick with what’s coming out of their POS, they’re already well ahead of the game.  As Albert Einstein said, “Any fool can know. The point is to understand.”  
Relatively speaking, it’s an excellent point.

Looking for Point of Sale software? Check out Capterra's list of the best Point of Sale software solutions.

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Dave Eagle

Dave Eagle is a former tech guy—and now writer—living in Vermont. Based on his online purchase history, we know that he is 42 years old, has 2 children, lives in a single family home, and has terrible credit. Please market to him appropriately. He writes a lot about technology, these days for the cloud POS company Kounta.

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