Data analytics is the science of analyzing raw business data and transforming them into useful information. The complete information is then used by businesses and their executives to make smart decisions that drive their company forward. Find out how you can apply it to your brand as a solopreneur.
Why Data Analytics are Important for Small Businesses
Data analytics helps small businesses grow by showing marketing strategies that increase sales. For example, by using data analytics such as A/B testing, a small business owner can test two different marketing tactics and choose which is better and which one is a mistake they should avoid.
The second use for data analytics is to identify trends for customer retention. The small business owner may analyze customer experience data like suggestions and feedback for cashless payment to encourage their customers to come back and do business with them again.
The third use of data analytics is for managing inventories in auditing. This can be done through spreadsheets to set prices and check if how many products are sold, aren’t sold, damaged, and lost. Auditing is very important in business because it helps the owner compute their total capital, revenue, profit, and losses for filing income taxes.
The final use of data analytics is to analyze the production of goods, marketing costs, and consumer demand to avoid wasteful expenses. A good example of this is computing the expected number of people to buy your new product. This is to prevent you from spending too much in the making of your goods.
Another use of data analytics as a cost-saving tool is analyzing which of the people in your area engage with your advertisements. By knowing the people interested in your ads, you’ll be able to keep on targeting them instead of spending money to promote your goods to those who aren’t interested.
How to Analyze Data as a Small Business Owner
1. Ask the right questions
The first step to analyzing data in a small business is to determine what kind of data is it that you want to be analyzed. It can be customer feedback, effective marketing strategies, cost of labor, revenue, etc. Choose the specific words and set specific number attributes for the data to be analyzed like date, sales receipt number, customer demographic, and so on.
2. Collect, compile, extract, convert, and store data
Once you have determined what data you desire to be analyzed, collect, compile, and store all the records and get it ready for analysis. You can do this by compiling all the transaction records in a folder, collecting all the paper from the suggestion box, researching public data about your competitors and have them copied into a document file, converting web-based data into a readable file, or making a copy of an inventory audit.
Before analyzing the data you have extracted, be sure to double-check if you’ve successfully collected everything you need and irrelevant data aren’t included.
3. Learn skills or use the best tools to analyze large amounts of data
Analyzing small business data isn’t really that hard. Most of the time, all you need is a formula of mathematical equations like demographic/total population = x 100. This formula can be used to analyze how many customers who have received an ad from you actually finished a purchase.
If 800 customers have received an ad from you and only 350 of them bought the promoted product, then the formula goes like this: 350 / 800 = x 100. That would be 0.4375 right? Then 0.4375 x 100 = 43.75. This tells you that only 43.75% of your customers bought your new product. If you find it hard to analyze data then use the data analytics tools here.
4. Visualize data for reporting
The final skill you need to learn in data analytics is how to convert your analyzed data into an easily comprehensible form. Luckily, there are a lot of tools you can use out there for this work. You can use Microsoft Excel, Powerpoint, and Apple Numbers for information presentation and printing.
Visualization is very important to easily compare periodical changes in business progress.
Data analytics is easy to learn as a business tool. Just know what you want to analyze, collect the data about it, and compute the numbers. You also don’t have to worry if you don’t know how to compute. There are a lot of technology-assisted tools and resources you can find almost everywhere. And day by day, the speed for data analysis improves as technology evolves.
