When Big Data and Small Data Work Together

In the search for insight, how relevant is the “size” of the data?

Data management technology has certainly come a long way, but to a certain extent Big Data is just a new name for an old problem that marketers continue to face: making sense of a large quantity of data that seems too unwieldy to analyze, interpret, and act on.

Obviously, data size is relative. Large, mature organizations with millions of data points have different challenges, needs, and resources compared to small and midsize businesses. However, when it comes to customer data and developing actionable insight, their issues are in many ways quite similar; they have all this data sitting around, what are they going to do with it? How will they analyze, interpret, and act on it to drive meaningful results in their business?

Large organizations that have armies of analysts and statisticians working with their data often work with data partners to enhance their databases with additional data points. By adding Small Data to their records—demographics, firmographics, socioeconomics, and propensity models—they develop greater insight and generate higher performance from their models.

Conversely, midsize businesses often work with data partners on custom regression modeling using solely the data points they obtain either directly from customers or from their internal CRM system. Unlike some larger businesses, they have the Small Data points they need, but not the necessary tools and expertise to leverage it. Their Small Data is more like Big Data to them simply because they can’t analyze, interpret, and act on it.

Size is relative, thus irrelevant

Since the essence of Big Data is unmanageability, Big Data doesn’t necessarily have to be terabytes or petabytes in size to be considered “Big.” Any amount of data that a marketer can’t easily analyze and convert into meaningful, actionable insights with internal data management resources could arguably be considered “Big Data,” at least as far as the owner of the data is concerned.

Therefore, when it comes to developing insight, I would say that the size of the data is fairly irrelevant. In fact, Big Data and Small Data can work together, one complementing the other, to generate the best results. Ultimately, success via insight depends not on the size of the data set, but on the effectiveness of the analytics used to generate results. In other words, it’s less about the size of the data and more about what one does with it that counts.

A McKinsey analysis of more than 250 engagements over five years revealed that companies that put data at the center of their marketing and sales decisions improve their marketing return on investment (ROI) by 15 to 20%. That adds up to between $150 billion and $200 billion of additional value based on the global annual marketing spend of an estimated $1 trillion.

Early adopters of Big Data analytics have gained a significant lead over the rest of the corporate world. Of more than 400 large companies, those with the most advanced analytics capabilities are outperforming competitors by wide margins. According to Bain & Company, the leaders are:

  • Twice as likely to be in the top quartile of financial performance within their industries
  • Five times as likely to make decisions much faster than market peers
  • Three times as likely to execute decisions as intended
  • Twice as likely to use data very frequently when making decisions

Finally, another key factor to mention is relevance. Is the data that’s being collected relevant to the organization collecting and using it? Any data can be captured, but should it be? Would Golfsmith benefit from knowing which customers use a Mac versus a PC? Probably not. But could Microsoft leverage that data point to optimize its marketing campaigns? Probably so.

For direct marketers—regardless of the size of their data—the key components to managing data and developing actionable insight are to develop a data-centric approach to marketing; create an appropriate data management infrastructure; collect relevant data; and, use effective analysis tools to help create well-defined marketing campaigns that improve results and drive their businesses forward.


Paul Theriot, Alesco Group

Paul Theriot was destined for success from an early age; his first job was as a pizza delivery boy in his hometown of Houston, and he was quickly promoted to “chief pizza maker.” Now he serves as president and co-owner of Alesco Group, and brings more than 20 years of leadership and marketing experience to the table. His insight and strategic direction have been pivotal to Alesco Group’s overall growth. Prior to Alesco, Theriot was a senior leader at AccuData America for nine years and helped sell the company to a buyout team in 2003. He’s also held leadership positions at the LA Times and Merril Lynch. Outside of the office Theriot enjoys surfing off the California coast, visiting art museums, running and weight training, and spending time with his two daughters.

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