The Marketing Benefits of Small Data

A yellow chair in a room showcasing the marketing benefits of small data.

Analysis, Data Analysis

New technological advancements and privacy pushbacks suggest that big data has its limits. What might the future of small data marketing look like?

Marshall Lemon

December 10 2019

The average marketer of 2019 thinks more like a data scientist than a marketer of 20 years ago, and for good reason: Data-driven marketing works. “Big Data” technologies have allowed marketers to leverage huge aggregated information blocks for their campaigns with promising results.

Nonetheless, big data has its limits. A growing backlash to mass data collection has caused some marketing professionals to fear that regulation efforts might ultimately harm their newfound capabilities. For others, however, this is simply a call for modest data collection — otherwise known as “Small Data.”


Small data refers to any dataset that can be fully understood by a human being without outside assistance. It could consist of a single spreadsheet or a few sheets of paper, and it might easily fit onto your personal computer. Regardless of medium, it is gathered for a highly specific purpose and can usually be digested within an hour or so. Former McKinsey consultant Allen Blonde years ago by stating that if big data is about machines, small data is about people.

Big data solves big problems and answers big questions. It shows us trends and insights from a scale that’s larger than what a single human can immediately understand. But for focused questions, big data seems to aggregate more information than marketing professionals can actually use — perhaps too much, considering that companies just aren’t using it for much of anything.

That’s not to say big data isn’t useful — it can greatly assist marketing efforts — but clever deployment of small data gets less industry attention than it should. One study of the construction and engineering industries suggests that 95% of collected data never even ends up being used. In these cases, small data initiatives could be more beneficial.

Arun Ramaswamy, CTO for Nielsen Global Connect, believes small data will ascend because it emphasizes depth and purpose. “Today’s economy runs on trust and transparency. For brands, this comes from using the right data, not necessarily more data,” he wrote. Ramaswamy much prefers the use of smaller, deeper data sets that focus on the specific preferences and needs of customers, than amassed broad-stroke general data.

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According to small data advocates, marketing doesn’t require such a massive data mill — it requires information that could be otherwise gained from speaking with customers in the field. With our current big data infrastructure, this data often gets buried within CRM and ERP marketing software.

The goal of small data is to find, define, and deploy the best data segments — whether collected in the field or from existing big data infrastructures. Small data campaigns will typically start with simple datasets, set manageable goals for their use, and focus on asking the right questions to gain specialized insights. In other words, small data campaigns set a hypothesis and determine whether it’s supported by the available data.

Wondering what kind of questions you should be asking? Here are some tips from data scientists.

Simon Ouderkirk, a small data enthusiast with Automattic, outlines the simplest test run of this philosophy: “Take a minute, think back on the last two or three months, and challenge yourself to identify the big untested beliefs that power your support team.” For example, a marketing team that believes customers want rapid responses — even if the responses don’t fully address their inquiry — might question whether customers would actually prefer slower, more in-depth answers. From there, marketers confirm their hypothesis by seeing whether customers with immediate responses were more satisfied than customers with detailed responses.


Small data is not about analyzing large reams of aggregated data. It’s about understanding the data you have and asking the right questions — making the “why” as important as the “what.” Sometimes that means mining for insights the team hadn’t originally considered. It also means re-examining your assumptions. What time of day will social media posts get the most engagement? Which customer segments would welcome new product recommendations? Finding these correlations may take time, but when applied correctly they can open brand-new market segments.

Martin Lindstrom, who literally wrote the book on small data, points out that simply visiting prospective customers at home provides small, focused datasets that can revolutionize your brand. His advice to Lego after noticing one child’s dedication to skateboarding turned the brand’s direction, and financial fortunes, around. Big Data finds correlations, but Small Data then finds marketers their causations.

Ready to start getting data for your initiatives? Check out PostFunnel’s guide to customer data platforms.

This article was originally published by our friends at PostFunnel.

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