Using the Performance Trend of Your C-Store in Business Analytics
Nowadays, we are living in a data-driven world. The rise of business analytics has added depth to numbers for a wide range of industries — taking observations, metrics, and simple inspections to a whole new level. According to the business data analytics experts from Maryville University, the science has since been used in banking, manufacturing, and even by the government. For businesses especially, it’s imperative to analyze your performance trends if you want to operate successfully and remain profitable. Simple reports on traditional paper are no longer enough to paint you an accurate picture of your store’s strengths, weaknesses, opportunities, and threats. Data analytics, on the other hand, can empower C-stores to make more informed decisions like never before.
Tech writer Anushka Mehta outlines the four types of business analytics that retailers and C-store operators should be aware of, namely: descriptive, diagnostic, predictive, and prescriptive. Together, they can supply the answers to questions management often ask to make informed decisions — from what’s going on with the company’s sales, to how to solve a company’s most pressing problems.
That said, here’s how you can improve your C-Store’s performance using this nifty technology:
Predicting new trends
Wondering why your C-store might be quieter than usual, or more crowded during certain months? Depending on a range of factors like the season, weather, and demographics, you might find your customer activity fluctuating from time to time. For example, the Christmas season might mean more customers flocking to the store and stocking up for parties. On the other hand, you might notice less people coming in when the weather is bad. These are all events that contribute to buyer trends. That’s why having a forward-thinking mindset in evaluating C-Store performance is crucial. By looking at the analytics of your business’ sales, foot traffic, and customers, you can make more informed decisions and ensure you don’t miss out on any opportunities.
Getting to know your customers
Data is a powerful thing. Without saying a single word to a customer, you can get to know them through business analytics. By monitoring retail data, you are able to become more attuned to the tastes and preferences of your shoppers. Analyze them even further and you’ll soon be able to detect certain customer profiles, and learn what kinds of customers buy certain products. With that information, you’ll be more aware what products to recommend to them, equipped with deeper insights into customers’ buying habits.
Reducing labor costs and more
The right data can reveal meaningful information about your customers. With data analytics, you’ll be able to observe how many people usually come in the store, and pinpoint what the busiest times are. C-Store managers can then leverage this when figuring out how many employees to hire, or when to open and close up shop. Besides significantly reducing labor costs, you’ll also be able to save on utility expenses, too.
Replenishing your inventory takes time, but the last thing store managers want to do is to be caught with no stock and miss out on a sale. As stated on a feature on predictive analytics on Inside Big Data, there are many reasons that dictate the potential demand for items, and these can only be made clear through the use of extensive research and analytics. This can assist you in managing your inventory more accurately and efficiently so that you can avoid running into inventory problems — especially during hectic periods. You can even make sales comparisons year over year to track progress over longer periods of time. For novelty or seasonal items, you can examine the data over a 6-week time scale to see if it’s time to keep or get rid of them.
Maximizing your promotional impact
C-store operators must carefully study which items are flying off the shelves, and which ones they aren’t shifting. By analyzing this data, you can find out how to create strategic promotions to maximize the sales across all your stock. Perhaps you would like to try discounting slow-moving stock, or putting up discounts for products typically bought together. This price-based promotion is a good way to drive sales and encourage customer loyalty.
Measuring customer conversion rates
With analytics, you can measure retail conversion rates that quantify how successful you are in transforming aisle browsers into paying customers. This data can also help you understand possible reasons why customers may not be buying what you’re selling. Watch them move through your store and observe how they respond to your promotions. Perhaps all they need is more information or guidance from a human. From there, you’ll also see how they interact with your C-store and thus develop methods to enhance the customer experience.
Want to learn more about optimizing C-Store operations through data? Find out more about BandyWorks’ Quik Data today.
Business Article authored by Jessie Bay for the exclusive use of bandyworks.com