Business Data Analytics: What You Need to Know

By John Peterson – Business data analytics refers to data analysis techniques to derive meaning from a business’ data and information. There are four primary types of analytics: operational, predictive, prescriptive, and descriptive, that contribute to the overall process of business data analytics.

The analysis involves looking at a large body of data and determining patterns, trends, and other helpful information from it.

Business data analytics combines traditional business analysis with specialized statistical analysis to discover business insights. It is helpful for various purposes, such as identifying which products are more popular or determining whether your website effectively converts visitors into paying customers.

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Why does business data analytics matter?

It’s a precious tool in decision-making and business intelligence, used to analyze and solve problems that would have been much more difficult to pinpoint with older means of analysis.

Using data analytics correctly can also improve internal business processes and save money through better resources. Companies can make better-informed decisions on allocating funds and resources by identifying more accurate and efficient methods of conducting business.

Business data analytics is also essential because it helps business leaders better understand their organization’s financial success, its potential for growth, and areas that may need improvement. Using data analytics to gauge market trends allows for flexibility in business operations that can help an organization adapt quickly to changing environments.

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Type of data analyzed

At a basic level, anything that’s numerical. A business analyst might work with sales figures, financial metrics, and qualitative data (such as surveys) to uncover patterns and better understand a particular aspect of their business.

Analyzing sales over time, for example, can help you predict trends and avoid areas of decline early on. Similarly, analyzing survey results can reveal which types of products are most popular among your customer base.

Data analysis can scale with business size

From a one-person show to a multinational corporation, any business can benefit from data analysis. Larger companies may have in-house data analysis teams, and smaller companies may rely on freelancers or consultants to carry out tasks.

As a business owner, it’s essential to know how you can use your data in an actionable way to make critical business decisions. Without data analysis, you may select the wrong mode of advertising, you may exceed your marketing budgets, or you may fail to fulfill your target customer’s deepest desires.

Once the value of data analysis has had time to marinate, it’s time to execute. Should you choose to outsource data analysis, be sure to partner with a company that shares in your vision and core values. Regardless of your business size, data integration experts such as Striim can assist you in your mission of building real-time data pipelines that will deliver invaluable business intelligence.

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Key business data analytics strategies

Business analytics has made considerable strides in the past decade, and one reason is data collection. However, it’s not enough to collect data if you don’t do anything with it. That’s where business data analytics strategies come into play.

Learn from your audience

It’s important to remember that audiences come from all over and comprise a variety of experts, beginners, and stakeholders. That’s why it’s crucial to take cues from your audience as you craft your business.

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Gathering feedback from your target audience is vital. Ask the audience about your idea and how you can improve it. Ask about experiences with similar businesses to learn more about how customers will react to your business’s product or service.

Invest in big data

Big data analytics allows a business to use historical and real-time information to make critical decisions. If you’re in charge of your company’s big data strategy, there are strategies you can implement to create value from your data. These include:

  • Developing better decision-making abilities by analyzing data trends
  • Improving operations with quality control checks
  • Monitoring key performance indicators (KPIs)
  • Automating tasks to save time and improve consistency

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Use segmentation

Segmentation is a tool for analyzing customers into groups based on specific characteristics explicitly targeted. For example, if you own a clothing store, you might want to know how many of your customers are tourists who’ll only make one purchase before they go home. Segmenting your customers into those two categories will help you tailor marketing strategies to appeal to different demographics.

Leverage predictive algorithms

There are several kinds of predictive algorithms used for different purposes. The most common type is a regression model, which uses historical data to predict future outcomes. These are useful for determining what factors drive certain behaviors or events in your business, such as a relationship between time spent on social media and customer retention.

Final thoughts

Business data analytics is a powerful and helpful tool for any manager who wants to take their business to the next level. Not only can it help you identify problem areas before they get out of hand, but it also provides information about your sales and customer habits to optimize your company for success.

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