“Being a data and AI leader helps enhance organizational goals such as speed of new product development, and customer satisfaction, which in turn leads to greater profitability.” 

This is what a recent Harvard Business Review's study underscores, making evident that:

Data driven companies are more profitable than their peers. 

When we know that data is the way forward, the next step is to understand how to use data analytics to improve the decision making, boost your business, and help growth.

In this article we share: 

• What business data analytics is; 
• Difference between data analytics and data analysis;
• 4 ways to deliver value using data analytics across your business;
• How to start being data-driven for real and get ready for the future.

‍

A definition of Business Data Analytics 

Business data analytics is the process of solving problems through the analysis of data using data analysis, statistical models and predictive analytics.

The goal? Data-driven decision making (not to confused with data-supported decision making).

This means that companies that perform business data analytics treat their data as a company asset and work hard to turn it into actionable insights.

The success of business data analytics depends on:

• The quality of the data;
• The resources within the company;
• Data culture and democratization - it’s what enables all people in the company to use data-driven insights to make business decisions.

‍

Difference between data analytics and data analysis

However data analysis and data analytics concepts are similar, they are not the same. 

- Data analysis is the analysis of the data to understand its patterns;

- Data analytics uses analytical techniques to find new insights, make predictions and, ultimately, guide data-driven decision-making. 

Simply put, analysis is about understanding the data, analytics is about converting data into actionable information that lead to decisions.

‍

4 ways to deliver value with data analytics

From improving customer experience to streamlining business operations, and making more timely and effective business decisions, data analytics business benefits can be endless.

Here you’ll find 4 key ways in which business data analytics will help revolutionize your business.

1) Improve Your Customer Experience

Using data analytics makes customers happier. 

It helps companies understand what people like, don’t like, how they act and why. So, businesses can tailor their products and services to their needs.

✅ For example, an online shop suggests items you might want to purchase based on what you’ve liked before, making your shopping experience more enjoyable.

‍2) Streamline Your Business Operations

Data can help businesses run smoother. 

It finds places where things could work better and helps managers decide what to do. It’s like having a GPS for a business. 

✅ For example, a delivery company looks at data to figure out faster routes for its drivers, saving time and money; an automatic alert advises you when your customer ID is expiring, or when you reach a threshold.

3) Measure Your Marketing Efforts

Think of data analytics as a report card for your marketing. 

It shows what’s working, what’s not, and what needs improvement. This way, companies can spend the budget on the marketing channels that are working best for them, and get better ROI (Return On Investment). 

✅ For instance, a restaurant checks which ads got the most people to come in and eat, helping them plan better ads in the future, or look at the data and see which creatives have driven more bookings.

4) Help HR Build a Stronger Team

Data helps organizations drive decisions about hiring and training. 

It makes sure employees are happy and growing. It’s like having a personal coach for work, by monitoring data analytics.

✅ For example, a company looks at data to see employees performance and help drive decisions on who needs support, who need incentives or training. 

‍

How to start being data-driven for real? 

Data collection, data preparation, data visualization, data analysis, implementation.

Analytics can feel like running a marathon, when the results come at the end of a long and tiring process. 

So where should you start?

• Get your data infrastructure clean and ready - this is a priority for the data team in order to make all the following steps possible;
• Democratize data and enable self-service analytics - to make sure your employees have the tools to get the insights they need;
• Provide specific goals and KPIs to help teams measure success - well-defined and measurable goals empower teams;
• Support and encourage data culture - enabling all people in the company to see the value of a data-driven culture so that they’re more keen on using AI in their work;
• Approach AI technologies aware of their benefits and impact on the business.

‍

The Future of Data Analytics

It’s clear that data analytics are a goldmine and can benefit the business in more than one way, across different departments.

It’s also clear that when it comes to extracting business value from data analytics, there is still a gap organizations need to fill.

It’s time to get your data infrastructure ready, build a solid data culture, and approach artificial intelligence technologies to help you fill that gap, enabling everyone in the company to literally speak with their data, and safely leverage hidden opportunities.

If you are curious about how iGenius helps people to literally speak with their business data thanks to Crystal, our private GPT for numbers platform, you can see the product in action here.

‍