Why Small Data Is a Big Deal

In this special guest feature, Tara Kelly of SPLICE Software highlights her list of three big advantages of small data. Founder, President & CEO of SPLICE Software, Tara Kelly, has a passion for enabling clients to engage in a meaningful, Data Driven Dialog(TM) with their customers. As a serial entrepreneur who has developed three companies including one outside the technology field, Tara’s expertise is multidimensional but focused on creating businesses that use technology to enhance operations, service and the customer experience.

Big data may be the most influential business trend of the decade, and big data experts predict that datasets will continue to grow exponentially. According to remarks delivered in a keynote address at last year’s Hadoop Summit, Hortonworks CEO Rob Bearden predicted that enterprise data volume would “grow 50x year-over-year between now and 2020.” Bearden also predicted that most of that volume will come from new data sources, including social, mobile, online and machine-generated data.

Retailers understand that unlocking insights from this growing volume of data can help them drive sales and spot emerging consumer trends, so they are scrambling to adopt the complex technologies and embrace the new analytics tools necessary to generate those insights. But it’s important not to overlook the value of the small data that a business accumulates over the course of its operations.

Small data is the information businesses collect directly from their customers. It includes contact information for social media, phone numbers (mobile and landline), addresses and stated customer contact preferences. Small data can be collected during the course of operations or gathered during a specific initiative, such as a loyalty program drive. Small data has three distinct advantages:

• It’s available: Businesses collect small data directly from their customers, so the company can narrowly define the data they want to generate instead of relying on data from a purchased source, which comes in multiple formats. Like big data, small data requires analysis, but since it is by definition limited in scope and supply, analysis can typically be conducted using the standard business intelligence tools the company has on hand. Small data doesn’t require a data science degree or sophisticated analytics engine to process.

• It’s accurate: Inaccurate data and information of poor quality is estimated to cost US businesses more than $600 billion per year. That’s why it is crucial for companies that use big data to make sure they access data from reputable sources and analyze it effectively to identify outliers and generate accurate insights. Small data is typically simpler to map and apply – companies keep the data fresh via in-house processes and design collection to generate the data they need.

• It’s functional. A large data set containing primary data collected from a variety of sources requires significant expertise to analyze and apply. When processed using sound methods, it can yield valuable insights, but there is also a risk of over-analysis and misapplication. Small data that is generated in-house tends to be easier to apply directly to sales, marketing and service decisions since companies can influence the questions and actions that generate the data.

Big data tools can be incredibly valuable for businesses. And big data can do things that small data doesn’t do, such as revealing a big-picture view on trends and providing a way to apply insights on a macro scale.

But it’s important for companies not to get so caught up in the big data movement that they lose sight of the value of small data. The data that companies collect directly from their customers provides a way to get an intimate, actionable view of customer preferences, and it helps companies build trust-based, long-term relationships. That’s why small data is a big deal.

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