(Feedsy Exclusive)
You might have come across the term ‘big data’ before, and wondered what it meant, and how it could help your business achieve success. In this article, we’ll define big data in simple terms, and give you a clear understanding of its potential.
Proper interpretation of big data can help small businesses like yours improve products, fine-tune services, and streamline business practices. So, it’s definitely worth taking the time to learn the basics.
Ready? Fantastic.
What is ‘Big Data’?
‘Big data’ is a term that refers to the huge quantity of stored information that has been collected from a multitude of digital sources. There are two types of ‘big data’:
Structured data. This includes things like customer relations information and purchase histories.
Unstructured data. This includes things like blog posts, photos, and updates published on social media sites. Unstructured data accounts for about 90 per cent of all big data.
The sheer quantity and seeming randomness of raw big data can be overwhelming. But, with proper organisation and interpretation, invaluable insights can be gained that can truly revolutionise the efficiency of your small business.
The Potential of Big Data for Small Business
Now for the exciting stuff. Big data has big – no huge – amounts of potential. The interpretation of big data will give you a way of seeing your business, its products, and its practices in a new light.
Here are a few things you could learn from big data and its proper interpretation:
- How to reduce expenses by pinpointing the root of unsuccessful ventures
- How to save time by making processes and practices more efficient
- How to optimise your products and services to meet the needs of your target market
The good news for small businesses is revelations like these are not dependant on the quantity of big data you have. Rather, success with big data is dependent on the quality of interpretation.
Practical Ways Small Businesses Can Utilise Big Data
Here are three practical ways your small business can utilise big data at an affordable cost to make meaningful steps toward longterm success.
1. Analyse Your Competition
Today’s consumers tend to check out a few products or services before they decide which to buy. You, too, can analyse your competitors to determine how they present their products or services, how they connect with their audience, and whether or not their business and marketing tactics are translating into sales.
Using tools such as Google Trends can give you a free insight into the popularity of a product or brand. And, social media networks can demonstrate a business’s connection with their customers. Have a look, for example, how popular your competitor’s posts are on Facebook and note which inspire the most engagement.
Gather this information and compare it to your own. Recognise their successes and failures, and use these insights to tweak your products, services, marketing strategies, and online presence.
2. Optimise Your Business Practices
If your small business uses practices and processes that generate data, you can use this data to improve efficiency. As we all know, saved time is saved money.
Some examples of processes relevant to small businesses that generate data include:
- Production machinery (such as printers)
- Online ordering systems
- Delivery vehicles
What you do with this data depends on the nature of your business. You might adjust your stock levels based on sales predictions, or test an alternate delivery route based on live traffic reports.
3. Get to Know Your Customers
Big data can give small businesses like yours the means to a clearer, fuller understanding of their customers. In particular, you can discover your customers’ pain points, likes and dislikes, favourite products and services, how they shop, and what they remember about your business when recommending you to others.
This kind of data can come from the ‘unstructured’ category we mentioned above: places like social media accounts, blogs, and review sites. Depending on your business, you may also find useful information in Google Analytics, sales information, and public sources of data (e.g. the national census).
