Big Data Tips for Small Enterprises
Big data is not just the realm of massive companies that monitor everything. Smaller businesses need to think like bigger ones.
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Big data is an immensely powerful thing when used correctly. It’s a mistake to believe that big data can only be used by big companies. More and more small enterprises are taking advantage of it, and it’s allowing them to achieve great things. They are able to make more informed decisions that drive their companies forward.
If you want to use big data, it’s not enough to just generate that data. Having lots of data is useless. You need to know how to actually use it. And this guide is going to show you how to do it.
Customers at the Heart
A business will spend 90% of the time interacting with its target audience directly or indirectly. But most companies are looking at the number of customers they are interacting with. They are not looking at the types of customers, and this is a good place for any small enterprise to start from.
An example of how I use this at my company, Oxygenmat, is to start with your sales numbers. Begin by taking that large figure and breaking it down. How many of these people are repeat buyers? What are they actually buying? How many are buying from mobile devices over desktops? What are the demographics of your main purchasers?
Answering these questions successfully is the first step to using big data for a real purpose. Letting customers drive how you use data will give you a 360-view of your customers.
Have You Linked Data Together?
It’s well-known that the more you know about your target audience the more powerful that data is going to get. You will interact with customers through a range of platforms. For example, you may have call center data, LinkedIn data, and email inbox data.
This should be linked together so you can get a full overview of your target audience. Link everything together, otherwise you could come up with entirely contradictory conclusions.
Once you link this data together, you should be able to segment it into entirely new categories. This will give you more data than you had previously, and therefore, you can use that to your advantage.
Ask for the Data
Big data is often characterized as something that you have to develop through studying your customers from afar. This is far from the case because as a business you have the ability to simply ask your customers about what they think. It’s the information you may not get from the numbers alone.
You can follow the lead of companies like Home Alarm Advisors by asking your customers in a variety of ways, such as through personal messages, comments on your website, and in-platform surveys. Asking questions and getting that feedback can help to make informed decisions because you can combine that feedback with the numbers.
The more informed you are the better.
Learn to Prioritize Customers
You may be wondering why customer segmentation is such a big part of this article. It all comes from the fact that your customers are not equal. Some are more relevant than others. As a small business, this is a hard fact to grasp because you are already grateful for all your customers.
There are two ways you can prioritize your customers. You can create a list of your most regular buyers and a list of your most lucrative buyers. These are the people you need to focus on because they are the ones who are most likely to stick with you in the long-term.
The majority of income for a business comes not from customers in general, but their most loyal customers. The same people are buying time and time again. There’s a reason why large corporations can accurately predict how much they are going to make whenever they launch a new product.
Apple, for example, knows they will make billions with every iPhone release because they already have a large following, even if they don’t bring in too many completely new customers.
Conclusion – Getting Started
You can start small with big data, and you probably should. It’s easy to drown in big data. To manage it all, consider starting at the bottom and scaling up as and when you need to. By doing this you are more likely to use big data better without focusing on quantity.
How will you take advantage of big data?
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