What is Data Analysis?
We have advanced far enough into the technological era that we can now speak of the pre-internet era as almost half a century ago. Technology has made advancements in data that have become essential to businesses. It becomes jarring to think of how businesses functioned without such insights in the past.
Big data, data analytics, machine learning, intelligent data, and data science have changed the game in the business world to such an extent that companies that had previously nothing to do with tech have ramped up their digital transformation. You can see such effects in any industry you view.
What does it all build towards? As a result of vying after data, you see a massive surge in demand for data analytics. More trends are being given birth due to the rise of more and more diverse data collection methods and analysis tools. Data analysis helps businesses make decisions by offering smaller companies an opportunity to be on even footing with their bigger competitors. All of this has created more efficient operations and improved productivity.
Procedures and Steps of Data Analysis
Businesses small and large are experiencing the impact of data analysis through data-driven decision-making processes. The steps for implementing an analysis process look something like this:
- Setting clear business goals before ever starting to play with data. What’s the ultimate objective of the task you’re about to embark upon?
- The data sources are confirmed and chosen for primary and secondary data channels.
- Metrics and KPIs are defined.
- Metrics are monitored regularly to see whether processes are driving the needle
- Aggregated data is analyzed to extract insights
Popular social hubs like Facebook, Instagram, and LinkedIn offer valuable analytics that are used to create a demographic of a brand’s ideal customers. The features are determined and then tailored to the customers.
With the right analytics tools, consumer patterns are made clear through business analytics. Your data analysis processes should provide the data you need by predictive analysis, which includes the following:
- Segmentation. The customers are split into separate categories based on demographics, behaviors, and attitudes. Each segment is targeted with a different product.
- Forecasting. Analysis helps predict specific patterns that let businesses utilize the demand for their service beforehand.
- Pricing. Analyzing data from multiple sources can help nail down better pricing for a product in your market.
- Customer Satisfaction. Customer journey and customer metrics like satisfaction are converted into actual data that businesses can use to improve consumer patterns.
Types of Data Analysis
There are four common types of data analysis:
- Descriptive Analysis
- Diagnostic Analysis
- Predictive Analysis
- Prescriptive Analysis
This analysis asks the question “what happened” and then answers it by summarizing past data in dashboards. Key performance indicators describe how a business is performing based on chosen benchmarks.
The next question is, “why did it happen?” Diagnostic analysis answers this by drilling down to find the causes of outcomes.
Then you ask, “What’s going to happen?” That’s where predictive analytics comes in and saves the day by providing forecasts reliant on statistical modeling for risk management, sales forecasting, segmentation, and customer success.
The last question is, “What do we need to do?” For that, prescriptive analysis takes all the data you have so far and churns it all down to provide you with a course of action to take in a current problem or a future issue. This helps improve decision-making.
Importance of Data Analysis for Your Business
Unstructured data is converted into structured data and analyzed to give you trends and insights to show you where there are “leaks” in your metaphorical boat or even growth opportunities.
If your business is looking to expand, data analysis can help you understand where you are hemorrhaging cash and what you can do to save that money and spend it to boost your operations. You can mitigate risks through data analysis by running scenario analyses based on historical data.
Data analysis gives your business a decision modeling process that you can use to predict most types of scenarios and plan for them in advance. With data at your disposal, you can drive performance and improve efficiency by streamlining business operations to be more time and cost-efficient.
With detailed customer metrics available to you, using data analysis can lead you to improve customer satisfaction and make smart business decisions in the process. Analyzing data gives you essential information about how your marketing efforts can be more targeted and specific to the most responsive demographic, saving you money and time.
Data analysis has equipped businesses with new strategies that they can use to improve customer satisfaction, expand their businesses, and protect their assets. Businesses can use the data trends at their disposal to uncover insights about their customers and use those insights to optimize their performance to reach new markets, create more value for existing customers, and provide a long-term plan for executives, key players, and shareholders.
Prescriptive analysis lets companies follow a data-driven plan to ensure that their operations are optimized daily. Companies like Apple, Netflix, and Facebook use this form of analysis for improved decision-making.
Leverage BatchData’s APIs for your analytics strategies
Find out how you can extract greater insight into your customers and business metrics by pairing your data with BatchData’s Property Data, Geocoding, and Address Autocomplete tools. Check out our products page to learn more.