By12:00 A.M. tonight, the world will have created over 2,500,000,000,000,000,000 new bytes of data — only to begin the countdown anew the first second of the next day. If you’ve just hesitated at reading that number, that’s “two-point-five-quintillion-bytes”. 

If you’re a small or mid-sized company wondering whether quintillion is the kind of big meriting the “big data” definition, the answer is a little less straightforward.

Big data, just like AI and ML, is one of those omnipotent buzzwords placed like a cherry on the cake to ensure a company’s progressive status. In particular, we’ve heard and read a lot about “big data for small business” without gaining a clear perspective on how exactly to define it in a small to mid-sized business context.

Can smaller businesses possess big data, or is that an oxymoron per se? What channels may be used to mine data in a small business context? And does size matter when it comes to gaining ROI from analytics and data? Let’s find out from entrepreneurs who’ve already put their data to big use.

Defining the “big” in “big data for small business”

“Talking about big data in the strict sense, small businesses that have massive data are usually those with a fair amount of transactions and a wide target audience,” says Dmitri Lepikhov, CEO of SaaS company MightyCall.

“These kinds of businesses usually have a wide geographic presence and target audience and will find patterns and unexpected insights through their use of big data. However, some businesses, like niche companies with a geographically localized audience don’t have the necessary data to strictly be called ‘big’. Yet they can still leverage data analytics to gain impressive benefits.”

Lepikhov’s own company has been named one of 2021’s fastest-growing U.S companies according to the Inc.5000 rating. The business credits its rapid growth in part due to smartly leveraging and analyzing data in a small business context.

Yet despite the booming conversation around big data for small business, what stops smaller companies from gaining those unexpected insights is precisely the “big” in “big data”.

A frequent situation is that while a business is automatically collecting data via several platforms, it may feel no clear purpose in putting their data to use if the company is doing well ‘as is’. Moreover, smaller companies often act on a hunch instead of strategizing their next move through analytics.

“SMB leaders over-rely on their experience/gut to run their business [and] financial performance is limited to the GAAP P&L’s produced by accountants,” says Lynn Corazzi, owner of a data consulting company Data2Profit, “[Meanwhile it’s] data [that] provides the common language between strategy, capability, and culture.

If you really don’t know what drove the results you’re getting, how do you know what to do going forward? If you don’t have data-based assumptions, how can you measure performance? And how can you measure performance if you don’t give the right information to the right people to manage performance?”

So how big should your data be to merit analysis? As someone who’s educated countless small and medium-sized companies on pushing the most out of business data, Corazzi is confident that truth is to be found in order.

Think of it this way: any kind of data that you have sitting around in Excel tables and that drives you a bit uncomfortable (or downright mad) with its length or breadth is big enough data to start with.

“I’ve built my business teaching SMB’s what can be done with Excel,” Corazzi notes. “Is it as cool as a new BI system? No. But it is a very cost-effective way to implement a culture of thinking Big Data. At some point, [businesses] should develop an SQL data structure and supplement with [the tool] Tableau.”

What kinds of data brings profit for small business?

Whether a business is getting its data regularly exported to Excel or it’s still tucked away on various software/cloud platforms, small business is likely already collecting a fair share of data.

To begin working with data in a small business context, first of all it’s necessary to understand that data falls into one of four categories, notes CTO and Co-founder of Technostacks Mrudul Shah.

1. Descriptive Analytics: Analyses past data like companies’ gross profits,
   revenue, sales, social media metrics, marketing statistics and enables
   report generation in various formats.
2. Diagnostic Analytics: Data mining, data drilling, and data recovery
   techniques are used in these analytics, which is done to understand the
   reason behind problems. In-depth insights are got from this type of
   analytics.
3. Predictive Analytics: As the name suggests, makes predictions of the
   future market trends, consumer trends using techniques like AI, ML, data
   mining.
4. Prescriptive Analytics: Prescribes a solution to an existing bottleneck
   on the basis of algorithms derived from AI/ML technology.

Next, we may analyze key sources of data for small and medium-sized companies.

• Invoices
• CRM entries
• Rates of spending, production, etc. per employee
• Consumer complaints
• Business phone system analytics
• Call recording transcripts
• Website traffic
• Social media performance
• Advertising performance
• Customer characteristics

Most of this data is widely available for smaller companies, and there’s no need to invest big money in getting big(ger) data, says Corazzi. “I worked with a company that doubled sales growth by having 6–7 key measure drive strategy, performance management, Sale Rep variable comp, and trade partner growth programs. That’s what happens when everyone speaks the same language and earns money from the same numbers.”

For companies looking to expand their data performance, tools like the following will make collecting, parsing, and analyzing data easier:

• Alteryx —combines a business’s internal data with publicly available
  information to gather insights
• Google Analytics — for tracking advertising ROI, Flash, video, and social networking sites and apps
• Emplifi — CX, social media, and marketing analytics platform
• Qualtrics — a platform for customer, product, brand & employee experience insights
• InsightSquared — revenue analytics and sales forecasting solution

Tools like the above will help companies group numbers in a highly organized, often visual-based way. However, don’t expect to make maximum use of the information without a human “translator”, a trained person in charge of your data.

As Corazzi comments, “The key recommendation that companies should consider is not the tool to be used, but rather the guide they choose.”

The relationship between Data and ROI

Are you a small company that wants to grow into the mid-size market? Think like a mid-size company. Are you mid-size and want to expand onto a global market? Think global. In a small to medium-sized business context, data isn’t always about “big” as much as about “thinking bigger”, experts say.

“Essentially…data allows small businesses to behave like large businesses but [smaller companies] can move faster towards innovation,” explains Maria Shelton, founder of Ardian Group.

“For small companies having access to data can make them gain insights to promote operational efficiency, productivity, and profitability. If anything, smaller companies have the ability to move quicker with decision making and task execution because they work more agile and nimble.”

For example, Lepikhov has already started leveraging his business data — which means analyzing thousands of the company’s call logs. “In 2021, we’ve hired a business analyst that has begun working with our data from call logs,” he says.

“Each of our incoming and outgoing calls is being analyzed carefully — whether it’s been picked up, missed, how long the call lasted, area codes from where the call was placed, etc. And that’s for each and every call.

We’re a small business, but we’ve got a massive number of calls each month, so you can imagine how much data we’re talking about. The process has just started, but step by step, we’re collecting important insights on aspects like lead generation, customer behavior, and customer experience.”

Meanwhile, Lepikhov encourages his small business customers to parse their own call logs even if they’re on the smaller scale of big. SMBs don’t have to go far and wide to collect such data or wait to collect thousands of calls, he says.

In a small business context, it can be gathered through a means as simple as a business phone system with analytics, which no business is small enough not to have.

In fact, small business owners who’ve started leveraging data show us that the relationship between data and ROI isn’t one of size. It’s one of perspective. Think of it like a parent buying clothes a size larger for their child because they’ll grow into it — faster than your blink. With data, it’s the same way.

When, with the help of a dedicated expert, you start to order and make sense of unstructured information that your company possesses and that feels like a leap out of your comfort zone to manage (e.g. all those CRM analytics, call logs, spreadsheets), that’s the kind of “big” data a company will rapidly grow into and that will bring in ROI.

Because if there is one takeaway both data experts and small business owners want us to have, it’s this: don’t think like the business you are today. Think like the business you want to become. Use your data and your small business agility to the full to accomplish that.