Little Data vs. Big Data: Which One Should You Use?
Big data vs. small data: is it war? Amidst the rising buzz about data-driven marketing, AdAge posted an article taking a stance against big data. Author Jeff Hassemer, chief product officer at Trueffect, challenged that “small data” might actually be better than big data for some marketers. According to Hassemer, many marketers feel the pressure from the C-suite to use data, but are overwhelmed with the options:
“If ‘big data’ sounds daunting, you are not alone. Countless marketers say they don’t even know where to begin (…) All that data, flying at us at hyper-speed, to be culled, analyzed and sliced a million different ways until a few key pieces of information that we can use to affect response emerge.”
For modern marketers who strive to be data-driven and don’t know where to start, what are the rules around using big data vs. little data? When should marketers be looking at fewer data points, rather than more? And is there a difference in outcome?
It’s about quality, not quantity
Hassemer comments on the confusion marketers feel about quantity of data:
“Big data, in certain applications, is almost magical—but if a retailer has 2,000 data points about an individual customer, how does she understand which are the important attributes and which are just noise? Furthermore, what are the odds that she gets a better result with 2,000 attributes than 1,500 or 1,000 or 500?”
Herein lays the quantity vs. quality conundrum (or, in Hassemer’s words, important attributes vs. noise). It’s less about small data vs. big data; instead, it’s about finding and using relevant data. Marketers must understand the difference between “more data” and “more valuable data.” In a recent post, 6sense data scientist Lisa Lakata explained the difference, noting that more data does not necessarily equal more information:
“Many variables in fact represent the same information… therefore, think beyond the numbers. Think: Are those really thousands of distinct signals, or is there only a fraction that are truly distinct with several different ways of representing the same information?”
Indeed, sometimes “smaller”, specific types of data (for example website visits or whitepaper downloads) may not classify as “big data” but can nonetheless provide valuable insights to marketers.
It’s also about how big you are
Using little data vs. big data also boils down to the size of your company. Larger enterprises, like IBM, will have years of data under their belts. IBM marketers will already be familiar with looking at marketing automation analytics and examining full-scale campaign data. As such, an IBM-sized enterprise may need a larger set of more dynamic, previously untapped data to move the needle.
On the other hand, an SME might just be starting their marketing efforts. In their case, starting small (data)—for example by examining website visits—may be just as valuable. After all, if you’re new to the data game, you have to start somewhere. In these scenarios, the real question to ask is: “What types of data have I not tapped into, that can drive more valuable insights?”
Hassemer agrees, noting:
“Big data will employ huge data sets — some third-party — to allow companies to personalize content to the consumer. That’s good news if you’re an enormous e-tailer [or B2B enterprise]. But it’s impractical if you’re a smaller outfit specializing in one particular product or category.”
When weighing little data vs. big data, above all, consider quality of your data. In addition, consider context: Are you a company just getting off the ground, or a bigger enterprise? Keeping these two points in mind will help you rise above the noise about “big data vs. little data” and do what is right for your marketing efforts.