If you own or manage a small company, you can be forgiven for tuning out talk of “big data” and “data analytics.” You’ve probably heard about the advantages that data-driven companies have, but you’ve likely also heard about the need to invest in teams of analysts and enterprise software to make it all work. As well is very important? to look for efficient VPN, so for this you can look for the professionals from webkor.
Yet many of the data super-scientists – the guys with the PhDs who are creating the algorithms, building the tools, and designing the infrastructure – say companies really ought to think more about “small data.” Big companies often think a little too big for their own good, and the best tools for the job are often more affordable than you think and readily available. These may include spreadsheets powered by Microsoft Excel or even a more robust business intelligence platform like Sisense’s reporting tool.
Indeed, small companies may even have advantages over larger enterprises when it comes to unlocking the value of business intelligence.To start, small companies have less data to sort through and clean up. What’s more, all that data is less likely to be siloed and is more likely to be immediately useful.
Here’s why it may be worth your time to give data analytics a second look.
You can make your lean operation even leaner and more profitable.
Successful data analytics projects solve specific business problems and contribute directly to your bottom line.
For example, you can use data analytics to:
- Increase sales
- Manage inventory
- Cut waste
- Use your marketing dollar more effectively
- Retain customers
All of these can either save you money, increase efficiency, or grow your revenue without forcing you to hire more staff members, or expand operations. Data analytics can help you do more with what you already have.
One great example of how all this can play out in a small business setting comes from a little cafe out of Copenhagen called Sokkelund Café and Brasserie. They used “small data” to grow their cafe from $1.1 million to $6.1 million in annual revenue.
They tracked sales per seat per day, customer retention, and other data to discover a lot of important insights about the business. These included their most effective marketing strategies, the impact of menu changes, and identifying wasteful processes that were eating up the cafe’s time, money, and ability to be nimble in the marketplace. They even managed to reduce their water and energy consumption. Much of this was done thanks to the data they were gathering anyway through the course of their normal business operations.
Data analytics could be the key to competing in, or even disrupting, tough, crowded marketplaces.
You can’t have innovation without information. In marketplaces that are oversaturated, innovation may be the only way to stay alive.
Consider Carvana, an online car marketplace. They had to overcome two huge customer fears. First, the fear of buying a used car in general, with all of its associated risks, like getting a car that will turn into a giant brick a week after purchase. Second, they had to overcome people’s fears around buying cars online.
To do this, they’d need a stellar reputation. Above reproach, even. The problem?
Used car sellers are often used car buyers themselves. They do a lot of guessing about cars when they pick them up at auction. When you buy a lemon, the problem may be less about maliciousness and more about the dealer’s own inability to spot it.
Carvana used data to solve the problem. They figured out how to identify high-quality used cars at auction, and how to make more informed bids on them. The result? A trusted online used car marketplace which is able to undercut competitor prices. One that offers a car-buying experience that’s arguably more comfortable and fun than the brick-and-mortar version.
Data analytics allows you to pinpoint problems and solve them before they threaten your business.
Consider Dannon yogurt, which has a problem built right into their business model. The problem is the yogurt itself.
Get too much on store shelves, and it goes bad before customers can buy it. Produce and distribute too little of it, and the company loses shelf space and the market share that goes with it.
Their answer? Using data-driven decision making to stock just the right amount of yogurt at each store.
Small businesses could have similar issues and often do. For example, fluctuations in demand make staffing and hiring challenging. It can be difficult to know what inventory to order, how much, and how to shelve it effectively. If a four-day stint of bad weather could severely eat into your profits, data analytics gives you the potential to know that and to adjust your strategy accordingly – by hosting a large event or a big sale a few days before the storm is supposed to hit, for example.
Small business operations have a much smaller margin for error than massive enterprises. Data analytics gives your business the power to stay in business.
Data analytics lets you take advantage of personalization.
Technology presents a paradox. It’s more convenient but it’s faceless and less personal. Everyone puts up with “press one for billing, press two for sales, ram your thumb into the # button sixteen times in the hopes that it will skip you to a human” mode of engaging with a business. Nobody likes it.
The personal touch – that sense that a business owner knows you, knows what you like, and cares about both – is one of the biggest edges a small business has.
Data analytics can help you bring that touch into your marketing, allowing you to create the feeling of doing “business with a handshake and a smile,” even if you’re doing it mostly behind a computer screen. It automates the process of keeping track of customers’ identities, likes, and dislikes with a retail pos hardware. It allows you to show products customers love or segment your emails right down to the individual level.
Personalization is the cutting edge marketing trend right now…don’t let your big competitors take this potential edge away from you by ignoring data analytics.
Getting started is simpler than you think.
You don’t have to be a statistics expert. You don’t need to be a data scientist or have a PhD.
You don’t have to struggle with Excel, either. Even though it’s possible to conduct a lot of data analytics on a spreadsheet, you wouldn’t be alone if you stared at all those green columns and rows wondering just how, exactly, you’re supposed to make all those entries add up to an insight.
Instead, you can use drag-and-drop interfaces and tools pre-designed to accommodate and analyze the most common and useful types of small business data. Then, once you get all the data into the system, you’ll have everything you need.
From there? Start pinpointing business problems and asking yourself what you need to know to solve them. Let the data guide you to those answers.
Finally, think in terms of incremental improvements rather than sweeping changes. Incremental improvements can bring huge returns, especially over time, and allowing yourself to focus on these smaller gains can keep data projects from becoming overwhelming and unwieldy. Keep it lean, mean, and performance-based, just like your business.