“Big data” - an oft repeated umbrella term used to refer to anything that involves data, from supply chain logistics to helping dogs stay healthy. The true definition of big data is so expansive that saying it covers “everything” would not be far from the truth. That being said, our focus here is not to define big data, but to discuss how small businesses can better leverage the subsets of big data to make smarter business decisions and orchestrate magical customer experiences.

Unfortunately for small businesses there are a lot of myths surrounding big data.

Myth #1: Using big data is largely reserved for big businesses with big budgets
Truth: Now, more than ever, small businesses are able to reap the benefits of the massive amounts of data with an influx of tools and services specifically geared towards those who have less in resources and budget.

Myth #2: I need a data scientist to analyze the data
Truth: Many of today’s solutions perform the data mining and analysis automatically. Furthermore, once the mining and analysis is complete, today’s tools will also provide the results in actionable chunks, removing the “Ok, now what?” question from the equation.

Myth #3: There is not enough time to spend poring over data
Truth: Being too busy to look at data is like being too busy to make more money. The data is an enabler towards making smarter business decisions and a motivating factor for employees to become more involved in the competitive thinking of the company.

Today's world is bursting at the seams with data (44 trillion gigabytes of data by the year 2020 by one estimate) yet the question we would like to answer is, how can data be made useful for small business? Thankfully, there’s help to be had and a lot of it. From established industry giants to budding start ups, many companies are entering the fray to offer small businesses affordable, yet robust data mining and analysis solutions.

Ultimately, the extraction of insights must be actioned in a way that helps businesses achieve their business objectives. The following is a list of our guiding principles towards ensuring any investment in data analysis yields high returns:

1) Make customers the center of attention
Aggregate level data is where most small businesses play when it comes to their customers. Most businesses can tell you their sales for the month. But when asked the number of first time buyers vs. repeat customers, too few have that level of detail. How many are women vs. men? What items are typically bought together?

By focusing on customers as the focal point of the data set, as opposed to the product or service line, businesses then set themselves up for more sophisticated and beneficial analysis in the future.

2) Ask and you shall receive
Despite the large amounts of data out there, there are still some things that business owners would like to know or should know about their customers that cannot be found in the data made available to them. A fine balance must be struck between the quantitative data collected and valuable insights that can be learned from customers by simply talking to them. Proactively seeking feedback from customers and combining that with the data-driven insights already available enables a more informed picture of the customer which then facilitates further actions to be taken.

As an example, if a store owner only looks at the number of people that walk into their stores she might be missing out on some valuable information and insights that could be gathered online. By surveying individuals and asking them about their online preferences, she might learn that a large majority would like to buy online and pickup in store. Insights like this allow merchants to adjust the offering in order to get more value out of their businesses and further satisfy their customers.

3) Customers are like snowflakes - each one is unique
When evaluating customers, small business should avoid over reliance on the “average” customer. The differences in your customer’s preferences will play a role in how they buy, which means it should also play a role in your customer strategy. Variance should not be a complication, but rather an opportunity!

By focusing on the customer set that matters most, you can base your actions on that group. What inventory should be carried? What promotions should be offered? What are the best ways to market? All questions that factor into how to customize strategy(ies) for this group.

4) Eliminate silos
Data becomes extremely powerful when separate data sets are linked together. For example, when sales data is linked to email data it’s possible to find out how many people buy products from email campaigns. Or if call center data is linked to website data, getting feedback on what type of customers submit feedback online vs. phone is possible. The overall goal should be data telling a narrative of how customers are engaging with the business, which then will help the business customize the shopping experience appropriately.

5) Baby steps
Data can be intimidating, and without the right approach it can often feel suffocating. When strategizing on how to leverage data analysis, consider one area of focus and build a process around it - baby steps! Start with a single interaction point and take the data through from end to end and build from there.

Data is everywhere and anywhere. Business owners should no longer fear it, but embrace it as a means to improve the business and customer focus. Today, it is essential for all business owners to arm themselves with technology - both hardware and software, that turns the large task of data analysis into something easy and enjoyable. The old saying goes “Knowledge is power”. Thanks to properly leveraging big data, knowledge can become a superpower!