In today’s world, especially when everything is at the disposal of technologies, use of data analytics has always been the source of understanding, analysing, and strategising businesses. With the right data processing and analytics, the companies can drive the right strategies, identify growth opportunities, and ensure that all their decisions are backed by data.
Since everything relies on data, only those with the appropriate type of data can successfully traverse the market, make future projections, and modify their business to match market trends in our digitally driven economy. However, the majority of the data we produce today is unstructured, which means it has a wide range of volumes, sources, and other characteristics. As a result, it is challenging and expensive to manage and evaluate, which is why it is a major issue for the majority of businesses.
Infact, according to Forbes, 95% of businesses cite the need to manage unstructured data as a problem for their business. And this is just the beginning! Statista has estimated that the world will produce slightly over 180 zettabytes of data by 2025. The modern businesses are combining this data with additional research that can further enhance their data like qualitative research, survey audits, and more.
The numbers are overwhelming, however, if you know how to harness the power of data analytics for business, you can exponentially increase its growth. This blog is all about understanding how to use the power of data analytics for business success.
Let’s get started.
What is Data Analytics and Processing?
Data analytics is a subset of business analytics, which focuses on using data to analyse both recent and past business performance in order to get insights that help the businesses in making better decisions. The data is not just useful for the executives, even the business leaders may use it to make business related and data-driven decisions.
Many people presume that data analytics can only benefit large businesses, but even the small and medium sized businesses can leverage the advantages of data to enhance decisions and ensure business growth. The right churning of data will help you run it more profitably, attract and retain consumers, and enhance operational efficiency.
Types of Data Analytics
Data can be a solid foundation for all B2B strategies. But if you wish to succeed in the use of data analytics, knowing about the types of data analytics is vital to choose the right one for your business needs.
1. Predictive Analysis
As the name suggests, predictive analysis uses data to estimate the chance of a condition arising or the likely course of an occurrence. In order to determine the future trends of business, predictive analytics uses a number of statistical approaches. These techniques analyse both current and past data. There are three basic fundamentals of predictive analytics: Predictive Modelling, Decision Analysis and Optimisation, and Transaction Profiling. Examples of Predictive analytics include direct marketing, customer pricing, and retail sales forecasting.
2. Descriptive Analysis
In order to define better ways of tackling the future events, descriptive analytics examines data and analyses past events. By analysing previous data, it examines and analyses the performance to determine what caused past success or failure. This kind of analysis is used in almost all management reporting activities, including sales, marketing, operations, and finance.
In order to categorise consumers or prospects into groups, the descriptive model quantifies relationships in data. It uncovers a variety of interactions between the client and the product.
Examples of Descriptive Analysis include: sales performance, dashboard reporting, fraud detection, and product demand forecasts.
3. Prescriptive Analysis
Prescriptive analytics automatically combines large data, mathematical science, business rules, and machine learning to predict an outcome and then proposes a choice alternative to take advantage of the prediction.
Prescriptive analytics goes beyond forecasting by additionally recommending actions that will benefit from the forecasts and outlining the implications of each decision option for the decision maker. Along with predicting what will happen and when, prescriptive analysis also considers why it will happen. Additionally, prescriptive analytics can recommend options on how to seize a future opportunity or lessen a future risk, and it can also explain the implications of each option.
4. Diagnostic Analysis
This analysis uses historical data over other data for the query or for the solution of any problem. We try to find any dependency and pattern in the historical data of the particular problem.
Businesses choose this analysis because it gives a great insight into a problem, and can also keep detailed information about their disposal otherwise data collection may turn out individual for every problem and it will be very time-consuming. The most common techniques of diagnostic analysis are data discovery, data mining, and correlations.
How is Data Analytics Helpful in Business?
According to Forbes, 70% of companies will switch to wide and small data by 2025 and this is a testament to the fact that all the businesses will eventually move to data analysis in the upcoming years. Let’s discuss below how beneficial is data analytics for business and how they can harness the power of the data for growth.
1. Make Data-driven Decisions:
Customer data is vital to a company as it allows for business performance insights which can eventually help in making informed decisions. Making smarter decisions is one of the main benefits of data analytics in a company. For your business, knowing what has happened in the past, what is occurring now, and what can happen in the future can be transformative.
Businesses that employ data analytics are able to anticipate the needs and behaviours of their customers in a better way which ultimately increases the likelihood of delivering those services. Once the businesses have information on data regarding customer needs, they are able to drive strategies which are directly linked to customer retention
2. Reduce Costs
Using company data is an excellent method to cut costs and run your business more smoothly. You can evaluate the processes that are working for you, analyse the need for employees, eliminate unnecessary processes and more. Understanding and analysing the necessities and removing the unrequired process can help in downsizing them leading to cost saving.
3. Improve Efficiency
Data analytics can increase a business’s efficiency by helping in identifying inefficient areas.
Large volumes of data can be collected by firms using data analytics, which can then be analysed to find flaws in the business model. Companies frequently overlook inefficiency as a problem because they are preoccupied with other issues. However, inefficiency can significantly reduce profitability and possibly result in the failure of the company.
Efficiency is crucial, but pinpointing inefficiencies isn’t always simple. Data analytics can help with it.
4. Increase Business Revenue
Businesses can improve income by using data analytics to gain insights on how to decide more effectively on pricing and product offerings. For instance, data research may show that the majority of customers who purchase one product also purchase a specific brand of another product. The company can then choose to combine these two things and sell them for less than if they were purchased separately.
5. Gives an Edge Ahead of Competitors
Businesses have an opportunity to outperform their competitors by the correct use of data analytics in business to have a better understanding of their customer base and how to connect with them.
Additionally, it can help businesses in figuring out what they are doing incorrectly and how to fix it. Once they have the hold of their processes, they can outperform themselves in various areas which will eventually give them a lead way ahead of their competitors.
Along with the data, researching is also a powerful way of getting ahead of your competitors. Various businesses can take advantage of research services and understand their customer base. Insights Opinion has helped various companies from all verticals with research and analysis to ensure unparalleled success and business growth. With our team of 4 million+ panellists and CATI research centre, we provide an array of research services including data analytics for business.
6. Use it for Artificial Intelligence and Machine Learning
Both the AI and ML are technologies of the future that learn from customer behaviour and data. Having structured data can also be fed into the systems for and be integrated with AI and ML to produce better results in lesser time.
Use Cases of Data Analytics in Business
Data analytics are being used in business now more than ever. No vertical is untouched by the use of data analytics in business. Here are some typical data analytics use cases that have been implemented in different business functions.
1. Marketing and sales
Marketing managers can make decisions that are highly accurate because of data analytics. They gather information from a variety of sources, including social media, email, and other platforms, in order to engage with their clients and better understand their needs and preferences. The data is then examined by marketing experts in order to enhance the marketing plan and increase sales.
Salespeople can sell more successfully with the use of data analytics by determining the products that are more in demand by specific target groups and concentrate on selling them to boost their success.
2. Human Resources
Although there are many applications for data analytics in business, the human resources sector stands out as a promising one. Data analytics in human resources helps in examining employee behaviour, attrition trends, and retention risks, analyse the performance of training initiatives, analyse how internal promotions affect employee morale, identify the need for training and development and more.
3. Data analytics in Customer Service
Customers are king, and most businesses strive to comprehend what they want. They can now gain deeper insights into client behaviour through data analytics and artificial intelligence. In one way or another, most firms use data analytics in customer service. It could be as simple as keeping track of statistics like call volume or hold time. Companies can utilise data analytics to better understand the demands, preferences, satisfaction levels, and other aspects of their customers.
4. Data Analytics in Supply Chain management
Data analytics may help any firm that has a supply chain or operations component. Consider the scenario where you produce widgets and those widgets need components made by vendors. So that you don’t run out of parts before they can be delivered, you should be aware of when your inventory is going low. Data analytics can be used to optimise personnel and production schedules.
Integrating Data Analytics in Business with Research
Data analytics in business is a vital part of growth. However, when combined with research and the derived data, it can produce excellent results for the company’s growth. Qualitative data, quantitative data, survey audits, online community building are all a part of business research which will eventually need analysing the produced data for business needs.
At Insights Opinion, we bring together the right blend of data analytics and research to ensure that no stone remains unturned. With the correct research methodologies and data processing, every business can achieve excellent insights, customer psyche, and behaviour.
Take Home Message
Research requires the collection of primary data, and with data analysis in business, you can complete the investigation and get the necessary insight from the research. At Insights Opinion, we can assist you with the data processing and research through our team of passionate, fast-paced and experienced professionals with years of experience in research.
Our experts will assist you with gathering, digitising, and processing raw data from various sources so that you can turn it into information that will be valuable for making better business decisions. Our objective is to provide affordable data processing services to global consumers using our years of experience. To know more about our data processing services, get in touch with us today.