If you are a business owner or digital marketer, analyzing customer data is essential to your company’s growth.
In fact, it’s the only way to make really good decisions in a data-driven marketing context.
Global organizations — Netflix and Amazon, for example — know this for a fact and are collecting billions of data points every day.
But if we reduce our focus, there’s an important topic that needs to be considered: small data.
In this post, we will show what small data is and how it relates to big data, clarifying how you can use the correct data for your marketing efforts.
Let’s begin?
What Is Small Data?
First of all, think of big data as raw data. It is collected and available for analysis, but it’s not very useful without refining it first.
When you break your big data down into digestible pieces, it is easier to generate reports and real-time dashboards.
Those pieces are called small data.
And when it comes to small businesses, they don’t store excessive amounts of data.
In fact, most companies store only gigabytes of data and use customer relationship management (CRM) software and website analytics — such as Google Analytics — to analyze website and customer transactions.
Furthermore, small data can come in many forms. You may generate a report in your CRM system and collect customer data from eCommerce or different sources.
The most important thing is to guarantee that the insights provided by the small data are organized, accessible, and easy to understand.
Finally, here’s an important distinction.
➤ Secondary data is collated by research organizations, which sell or share their data with other organizations.
For example, the U.S. government shares census data for free. Anybody can download the data into their spreadsheet and use it to project market size or customer demographics.
➤ If you decide to conduct your market research, you are collecting primary data.
This data can be obtained from business transactions, industry reports, or direct conversations with employees, customers or vendors.
This data is often detailed and collated in spreadsheets and fits the small data definition.
Small Data vs. Big Data: What Is the Difference?
Here’s the thing.
Big companies collect data and use it to predict behaviors, segment audiences and drive innovation and automation.
But the downfall of big data is the need to have big — or costly — computers and large, expensive software programs.
In contrast, small businesses generate and use smaller data sets.
Since smaller firms are often more agile and frugal, they tend to use data more efficiently.
Should you focus on small data rather than big data?
For most small businesses, it is easier to process and interpret data in smaller data sets than trying to process vast oceans of information.
Big data consists of massive volumes of information in a single, expansive repository.
On the other hand, small data consists of well-defined tables that are easier to analyze and use to make business decisions.
The conclusion?
Big data is not really that actionable for professionals, while small data can be presented in a more relevant and compact way.
For small companies with limited resources, it makes sense to work with data that means something and can make a difference for their business.
For instance, if you are trying to analyze which sales lead performed better, looking at which ones directly result in sales will narrow your focus.
Then, you can identify the sources for those leads and try to understand why they are more effective at generating revenue.
What’s the Importance of Small Data?
Small data provides digital marketers and small business owners with the information they need to make actionable decisions.
Unlike big data, which requires extensive data mining and processing to answer analytical questions, small data powers real-time decision-making processes.
In addition, small data powers machine learning and artificial intelligence models, which are essential tools for automating key internal workflows.
Using small data to focus on crucial problems will help solve undiscovered challenges by large data sets that focus on the same issues every other data scientist looks to resolve.
The small, detailed observations uncover innovations because of the unique, focused small data research conducted using one-on-one human interaction.
Small data drives better, real-time results, helping businesses that are looking to disrupt standard practices.
Is Small Data the Next Big Thing?
It’s hard to say, but it’s definitely something to dedicate your attention.
Small data sets are essential for powering automation, allowing businesses to expand and grow without increasing headcount and adding extensive fixed costs to the business.
Refined small data resources provide detailed answers to important questions.
Besides that, small data can be gathered using different methods, such as:
- Customer satisfaction surveys.
- Social media channels.
- Customer focus groups.
Because of this, businesses can tailor their research methods to answer the exact questions.
The human factor is also essential for researchers using small data sets. Real people contribute to insights and intelligence used to develop artificial intelligence solutions.
This isn’t a new concept.
There was a time when small business leaders spoke with their customers regularly.
But today, with the internet, virtual meetings and data analytics tools, it is easier to rely on a computer algorithm to decide than to spend time with customers and learn directly from the people who buy their products.
The entrepreneurs who meet with their customers in one-to-one meetings understand the importance of building a well-defined buyer persona to drive productive marketing campaigns.
What role does small data play in AI?
Artificial Intelligence is a process that mimics human behavior. It is often used to trigger and control automated processes.
Some data analysts believe big data is needed to create effective artificial intelligence solutions.
But often, all big data does is create solutions in the same way as others using the same extensive data resources.
Artificial Intelligence must use data to make precise, repeatable actions to solve problems or create repetitive and automated tasks.
By using small sets of accurate data, it is easier to create varied scenarios and options.
It might sound like an oxymoron, but small data helps artificial intelligence systems behave more like humans, which, in turn, creates more value for sales and marketing processes.
Small data also focuses on the end-user customer and their experiences shopping at your store or visiting your website.
Wrap Up: Small Data is all about Accurate Results
With the help of customer satisfaction surveys, one-to-one interviews and other human-focused techniques, researchers can find critical answers to unsolved problems.
And small data can be that special aspect of your strategy making it all possible.
Want a valuable tip before you go?
Read this edition of the Rock Content Magazine about the pillars of data-driven marketing and learn how to improve your data analysis and visualization!
