What Are Data Analytics?
A growing number of small companies are turning to data analytics for business insights. Simply put, data analytics connect the dots among an ever-growing number of big data points to find meaning—patterns, trends and correlations—that could have important business ramifications. Modern technology mines and integrates the intelligence collected from myriad sources and performs all the number-crunching. The cost for this insight? It starts as low as free, with options including “light” versions of more advanced tools.
Why Are Data Analytics Important?
Data analytics are important because it helps businesses optimise their performance. Applying it into the business model helps companies reduce costs by identifying more efficient ways of doing business. It can also help analyse customer trends and satisfaction, which can lead to new—and better—products and services.
How do different sectors use Data Analytics? Data analytics has been adopted by several sectors, including travel and hospitality. For example, the travel industry can collect customer data and figure out where the problems, if any, lie and how to fix them. Healthcare is another sector that combines the use of high volumes of data and data analytics can help in making quick decisions. Similarly, the retail industry uses copious amounts of data to meet the changing demands of shoppers.
What Does A Data Analyst Do?
If you’re considering a career as a data analyst, you might be wondering what tasks and responsibilities fall under the job title. Some of the typical tasks and responsibilities of a data analyst are:
- Manage the delivery of user satisfaction surveys and report on results using data visualisation software
- Work with business line owners to develop requirements, define success metrics, manage and execute analytical projects, and evaluate results
- Monitor practices, processes, and systems to identify opportunities for improvement
- Proactively communicate and collaborate with stakeholders, business units, technical teams and support teams to define concepts and analyse needs and functional requirements
- Translate important questions into concrete analytical tasks
- Gather new data to answer client questions, collating and organising data from multiple sources
4 Types of Data Analytics
- Before exploring how data analytics can help improve your business, it’s important to understand the different types of data analytics. Data analytics generally fall into one of four categories:
- Descriptive analytics find patterns in current and historical data to help businesses understand what has happened to date. Average revenue per customer and monthly website traffic are two examples of descriptive analytics.
- Diagnostic analytics takes descriptive analytics further by linking cause and effect to address why something happened, such as a sudden sales spike or influx of website traffic.
- Predictive analytics looks ahead to figure out what may happen in the future based on what has happened in the past. This insight can help a business predict product demand and budget needs. Prescriptive analytics is the most advanced of all four categories. It focuses on what a business can do next to achieve a desired outcome. Product recommendations based on a customer’s past purchases is one example of prescriptive analytics.
5 Ways Data Analytics Can Improve Your Business
Now let’s consider the ways data analytics may lead to positive outcomes for your business. Among the benefits, data analytics can:
1. Improve Decision-Making
As much as potential investors might like the business ideas you present to them, they'll always ask for hard numbers—annual sales, manufacturing costs and marketing spend, among them—to assess the worthiness of an investment. Likewise, bias-free, real-time data analytics is undeniably the more dependable guide for most every business decision you may face. You may be able to make decisions faster, too.
2. Drive Growth and Expansion
Which of your products and services are selling the most? The least? Where are sales coming from? Is now the right time to launch a new product? The answers to these questions, and plenty more, can be found in your data analytics, all of which may ultimately benefit your bottom line.
For example, if data analytics reveal that a line of handbags have doubled in sales over the previous year, you might choose to add matching wallets and eyeglass cases to your mix. Demographic data may also find more customers coming to your e-commerce store from overseas, leading you to expand your marketing efforts and display product prices in different currencies.
3. Reduce Expenses
Data analytics can pinpoint areas and processes where your business isn’t performing as efficiently as you’d like, leading to higher costs for your business. For example, if data analytics shows you’re too frequently running out of stock and sales are down, it’s probably time to re-examine your inventory management practices. Data analytics can also show which recruitment channels are bringing in the best job candidates, resulting in a twofold savings: One, you can avoid spending time and money on ineffective channels. Two, the thousands of dollars it can cost to recruit and retain an employee will be well spent.
4. Enhance Customer Satisfaction
Anything that causes your customers to feel disappointed or upset can negatively impact business. Data analytics can report dips in sales and revenue, but it can also illuminate earlier indicators of friction before they cause business harm. For example, an increase in help-desk calls may signal that your software doesn’t work as intuitively as expected.
Visitors quickly abandoning graphics-heavy product web pages could indicate the images are taking too long to load. The faster you can address such issues, the more customers may stick around—and appreciate your proactivity. Moreover, data analytics can help a company be proactive about delighting customers. For example, perhaps you’d like to reward customers who buy most frequently from you with a personalised, one-time discount to thank them for their loyalty. Data analytics can tell you who they are.
5. Manage Risk
Data analysis can pick up on anomalies in data that might indicate fraud, such as suspicious transactions; cybercrime, such as a data breach; and violations of business policy, whether intentional or accidental. For example, data analytics might uncover inventory levels that don’t match accounting records or duplicate payments made to the same vendor, perhaps by mistake—or not. Early detection may not only temper or possibly eliminate monetary losses, but it can also shed light on where a business may need to strengthen its processes to prevent such an event from happening again.
Before You Begin
As with most business endeavors, think through your objectives and how data analytics may help you achieve them before wading in. Do you want to expand to new markets? Better understand your customers? Make the most of your marketing dollars? Whatever your intentions—which may be all of the above and plenty more—data analytics can deliver a wealth of insight that puts you on a path to greater success.