Businesses today can collect data at every stage of the customer journey. This data may include mobile app usage, digital clicks, and interactions on social media, all of which contribute to a unique data fingerprint for each customer. With more data available than ever before, business analytics is a growing field. However, the ways in which professionals use data to make decisions varies by industry. For instance, airlines may use business analytics to determine ticket prices, while hospitals may use data to optimize patient flow or schedule surgeries. In this article, we will discuss the tools and use cases for business analytics.
A. What is Business Analytics?
First of all, what is Business Analytics exactly? Business Analytics is the process by which businesses use statistical methods and technologies for analyzing historical data in order to gain new insight and improve strategic decision-making.
Business analytics combines the fields of management, business and data science.
Also, Business analytics refers to the use of methodologies such as data mining, predictive analytics, and statistical analysis in order to analyze and transform data into useful information, identify and anticipate trends and outcomes, and ultimately make smarter, data-driven business decisions.
There are three primary methods of business analysis:
Descriptive: The interpretation of historical data to identify trends and patterns
Predictive: The use of statistics to forecast future outcomes
Prescriptive: The application of testing and other techniques to determine which outcome will yield the best result in a given scenario
The main components of a typical business analytics dashboard include:
Data Aggregation: prior to analysis, data must first be gathered, organized, and filtered
Data Mining: data mining for business analytics sorts through large datasets using databases, statistics, and machine learning to identify trends and establish relationships
Association and Sequence Identification: the identification of predictable actions that are performed in association with other actions
Text Mining: explores and organizes large, unstructured text datasets for the purpose of qualitative and quantitative analysis
Forecasting: analyzes historical data from a specific period in order to make informed estimates that are predictive in determining future behaviors
Predictive Analytics: predictive business analytics uses a variety of statistical techniques to create predictive models, which extract information from datasets, identify patterns, and provide a predictive score for organizational outcomes
Optimization: once trends have been identified and predictions have been made, businesses can engage simulation techniques to test out best-case scenarios
Data Visualization: provides visual representations such as charts and graphs for easy and quick data analysis
According to a recent study by MicroStrategy, companies worldwide are using data to:
- Boost process and cost efficiency
- Drive strategy and change
- Monitor and improve financial performance
The research also shows that, over the next years global enterprises predict their investments in analytics will accelerate.
“Using data analytics is a very effective way to have influence in an organization. If you’re able to go into a meeting, and other people have opinions, but you have data to support your arguments and your recommendations, you’re going to be influential” – said Harvard Business School Professor Jan Hammond
B. Analytics use cases
Business analytics can enable new types of marketing campaigns. The data collected by businesses give insights into customer behavior which helps businesses understand the effectiveness of advertising campaigns with different audiences. Targeting audiences that are more likely to respond to specific campaigns or products increases efficiency overall. In addition, understanding consumer habits can help businesses improve customer retention. By identifying customers who are less likely to return, businesses can offer targeted promotions. This provides a cost-effective way to gain customer loyalty.
Another very good example is delivering relevant products. Products are one of the largest investments companies make. The product management team’s role is to recognize trends with the help of Analytics that drive strategic roadmap for innovation, new features, and services.
Other business analytics examples include the operation and management of clinical information systems in the healthcare industry, the tracking of player spending and development of retention efforts in casinos, and the streamlining of fast-food restaurants by monitoring peak customer hours and identifying when certain food items should be prepared based on assembly time.
For example, fast-food restaurants have begun to implement business analytics to streamline their restaurants. By monitoring how busy the drive-thru is these businesses can increase efficiency during peak hours. When the line gets long, the digital order boards change. They begin to highlight items that can be prepared quickly. This leads to more simple orders that can be completed quickly. When the lines are short, slower items with higher margins are featured. In this way, the restaurants can respond to real-time needs to improve efficiency.
Business analytics has many use cases, but when it comes to commercial organizations, BA is typically used to:
Analyze data from a variety of sources. This could be anything from cloud applications to marketing automation tools and CRM software.
Use advanced analytics and statistics to find patterns within datasets. These patterns can help you predict trends in the future and access new insights about the consumer and their behavior.
Monitor KPIs and trends as they change in real-time.
Many companies use descriptive analytics for a deeper look into the behavior of customers and how they can target marketing strategies to those customers.
Diagnostic analytics: Focuses on past performance to determine which elements influence specific trends.
Through data mining, for example, a business may be able to see which customers are buying specific products at certain times of the year. This data can then be used to segment those customers.
Through text mining, companies collect textual information from social media sites, blog comments, and even call center scripts. Then, this data is used to improve customer service and experience, develop new products, and review the performance of their competitors.
Through data aggregation marketing teams use data like customer demographics and metrics (age, location, number of transactions, etc.) to personalize their messaging and offers.
Forecasting can be used for several different things, such as retail sales around specific holidays and spikes in specific internet searches around certain events – like an award show or the Super Bowl.
Through prescriptive analytics business analytics can show you the best course of action for a given situation. While descriptive analytics shows what has already happened, and predictive analytics tries to forecast what might happen next, prescriptive uses that information to give you potential solutions based on similar situations (Year over Year data, seasonality data, product launch data). For example, ticket sales for a holiday show are lagging over last year’s sales. Prescriptive analytics may suggest a need to lower prices or add a matinee performance in response.
“Forecasting based on historical data is useful for setting yearly goals and predicting online user behavior, such as traffic and conversions. Customer journey analytics allow you to identify first-touch interactions with a potential lead, all the way to the conversion step. Having visibility to all touch-points in the nurture process lets you optimize the steps in between and improve the user journey.” – Jackie Jeffers, Analytics Strategist at Portent
C. Business Analytics benefits
Improved decision-making: Business analytics helps organizations make data-driven decisions, which can result in better outcomes and improved performance.
Increased efficiency: By analyzing data, businesses can identify inefficiencies and implement changes that improve processes and reduce costs.
Enhanced customer experience: Business analytics can help businesses understand their customers better and provide personalized experiences that improve customer satisfaction and loyalty.
Competitive advantage: By using data to make informed decisions, businesses can gain a competitive advantage over their rivals.
Risk management: Business analytics can help businesses identify and mitigate risks by providing insights into potential threats and vulnerabilities.
Improved financial performance: By using data to identify trends and patterns, businesses can make more accurate forecasts and improve their financial performance.
Greater insights: Business analytics provides organizations with insights into their operations, customers, and competitors that can help them make better decisions and achieve their goals.
D. Business Analytics Tools
Business analytics tools are helpful for companies to stay competitive and maximize revenue streams and efficiency.
Power BI
Power BI is a business analytics tool developed by Microsoft. It allows users to create interactive dashboards and reports that provide insights into data. Power BI integrates with a wide range of data sources, including Excel, SQL Server, and cloud-based services such as Google Analytics and Salesforce. It also offers a range of visualization tools, such as charts, graphs, and maps, that make it easy to understand and analyze data. Power BI is available as a standalone tool or as part of the Microsoft Office 365 suite of productivity tools. It is widely used by businesses of all sizes to gain insights into their data and make data-driven decisions.
Tableau
Experts agree that Tableau Big Data Analytics is one of the best business analyst applications, given its dynamic and cutting-edge capabilities for unstructured text analysis. Tableau’s business analytics platform, which includes robust and reliable statistical tools, empowers users to perform an in-depth analysis and predict patterns based on current and historical data.
QlikView
QlikView is a business intelligence and data visualization software developed by Qlik. It has unique features, such as patented technology and in-memory processing, facilitating the delivery of ultra-fast business analytics reports. Included among the best business analyst software tools, QlikView allows users to visualize data relationships using specific colors for related and non-related data with automatically maintained data association.
Rating and review of Analytics and Business Intelligence Platforms by Gartner
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