We’ve all heard of big data, that nebulous term used to describe a fire hose of information that often overwhelms companies. 

Big data gained a lot of steam — and hype — in the early 2010s. It was seen widely as a huge resource from which to draw business decisions and plan next steps. On the extreme end, some observers pegged big data to cure cancer by deriving personalized treatment options or to keep vending machines always full thanks to real-time sensors monitoring your candy and chip choices. 

For sales teams on the early edge of digitizing their operations, big data sounded like a way to get every piece of information needed on prospects. However, while big data did indeed dig up tons of details, in some ways it became an unbridled force that was too much to handle. 

“It’s a beast,” says Derek Smith, chief strategy officer at ZoomInfo. “It is this really powerful, massive thing, and if you don’t harness it, if you don’t use it in the right way, it’s not helpful.”

Today, smart sales teams still see potential in big data. But they know that to take full advantage of it requires surfacing niche data points that are easier for people to digest and act on. We call that niche information “small data.”

Big Data’s Big Wave

Many companies wanted to jump on the initial big data train because, after all, having more data about customers or trends sounded like a competitive edge. But an avalanche of raw data came with risks.

So much data rolled down to sales teams that they weren’t ready for it. The supply outpaced the average professional’s ability to act on it. It was data’s version of the dot-com bust, Smith says, referring to a period in the late 1990s when too much blind investment in young internet companies led to a sudden collapse in their value in 2000.

“Too much data is a problem,” Smith says. “The more data you have, the more important it is to extract insights from that data because you don’t have the bandwidth to individually review all the data.”

The Evolution to Small Data

When tracing the progress of information since big data arrived, sales teams will immediately recognize certain milestones. For example, popular buyer intent data (also known as buyer signals) pulls from big data to present upticks in online interest in certain topics from potential prospects. 

While more focused than big data, buyer intent can also be overwhelming if it’s not narrowed down, Smith says. A seller could request intent data for 50 topics and get a list of 1,000 companies to go after; it’s not practical without refinement.

This is where the granularity of small data comes in handy. It can be a difference-maker because its benefits are more accessible. A recent spate of tools — like ZoomInfo’s Scoops, among others — caters to data-driven sales teams seeking such direction.

“Small data is big data which has been connected, organized, and packaged by complex algorithms in order to appear easy and actionable for humans,” wrote Riccardo Osti, CEO at Wonderflow, which sells customer analysis software.

Research firm Gartner listed small data as one of its top 10 data and analytics trends for 2021. “Small data, as the name implies, is able to use data models that require less data but still offer useful insights,” according to Gartner.

What Can Sales Teams Do with Small Data?

Small data can provide sales reps with context, insight, and guidance towards action. These capabilities increase the potential to close a deal.

Scoops, a feature in the ZoomInfo platform, offers a good example of small data. Each Scoop is a specific piece of information about a particular company taken from a market research survey. A Scoop might say, “A mid-level manager at Acme Media indicates the company will evaluate new applicant tracking systems in the next six months.”  

Knowing a company is looking at applicant tracking systems provides insight on where the company stands with tech stack purchasing and how they will hire talent, and most importantly, gives sellers of applicant tracking software next steps to take.

“That is one piece of data that is incredibly valuable,” Smith says. “It’s one answer to one question by one person, and it’s potentially more valuable than a million data points we have that make up one [buyer] Intent signal.”

Another valuable small data point: automated alerts that track the employment histories of prospects a rep has sold to. It is powerful to know when a champion of your product switches jobs to another company because it immediately opens the door for another sale to that person.

Company Attributes is another ZoomInfo tool that showcases small data. By filtering attributes, a rep is able to narrow down ideal companies by the size of the sales or marketing team, recent funding rounds, whether a firm offers tuition reimbursement as a benefit, or hundreds of other traits. This creates a hyper-focused prospecting list from small pieces of information.

Big Data vs. Small Data: Why You Need Both

In his 2019 book “The Invisible Brand,” author and marketing AI expert William Ammerman viewed optimal data as a way to reach goals and engage better with prospects.

“Rather than taking a bunch of data and analyzing it to draw conclusions, we can now interactively leverage live data to continuously refine what we are doing in driving towards our goals and key performance indicators,” Ammerman wrote. “It’s about interactions, and it’s about creating new insights, predictions, and prescriptions based on the latest information available — which might be less than a second old.”

Big data, buyer intent signals, and small data don’t exist without each other. Big data is the feeding point, intent sorts that flurry of information, and small data pinpoints specific moments. 

The evolution from big data to small data has provided sales team’s with useful tools. Small data adds a method of refinement to a rep’s arsenal that allows details to flourish into possible closed deals.

To see where small data can take you, check out ZoomInfo’s offerings.