How to be successful at business analytics

business analytics

Businesses have to manage an array of chaotic figures daily. These numbers are called data and only make sense once analyzed. Companies can transform this data into insights using the correct methods and processes. This transformation process is called business analytics.

What is business analytics?

Business analytics refers to the techniques that companies use to measure their business performance. It includes qualitative methods applicable to projects, products and processes. This information is needed to evaluate specific and general aspects of the business. There’s no limit to how valuable this data can be. For instance, it is also helpful in determining the weakness of a current process and suggests better ones to replace it with. The most familiar reason for using business analytics is that it helps companies make smarter decisions. While decision-making is crucial to business growth, timeliness is also essential.

Do you own a business or have an interest in business analytics? If so, read on for more information. Or perhaps you are interested in furthering your education around this subject. If so, the SBU online business analytics master’s degree is an excellent option. The program is designed to prepare you for high-demand roles working with big data, even without business analytics experience. The best part of this degree is that you are exposed to technologies such as SQL, Python, Tableau and SPSS.

Benefits of using business analytics


Below are the benefits of using business analytics. 

  • Performance enhancement

Every business aims to make a profit. This is only possible if a company stays ahead ofits competitors. One way to stay unique in any industry is to use business analytics to identify strengths and weaknesses. This will help expose redundant aspects of operations that could be holding back a business back. It also helps you find what drives your business forward, enabling you to invest more in improving and maintaining these aspects. Remember that your business is run by humans who interface with customers directly or indirectly. These people must always be at their best to give customers the best. What happens when your staff don’tgive their best? The management must investigate to understand why. Business analytics can help to monitor performance and identify lapses. If the results show that the staff are underpaid or that your business is understaffed, the management can consider increasing salaries while employing more people.


  • Increased operational efficiency


While companies aim to improve their services, they also hope to lower costs. Business analytics provides the necessary metrics to measure productivity and compare it against the company’s finances. It is more effective than the manual approach because it pulls data from various sources in real time.Therefore, you can monitor relevant indicators to know what needs improvement or trimming. Imagine what would happen if a company automated most of its processes and increased profit. The company would pay fewer people but have enough profit to invest in other areas. This may be disadvantageous for the workforce, but it leaves room for people to learn new skills.


  • Risk mitigation


Business analytics allows you to analyze and understand everything related to trends, customer behavior and performance. When a business goes ‘in the red’, it stands on a thin line. The chances are that it may fall off. Aside from that, business analytics also helps to automate various data-related processes. Employees can now focus on their jobs of finding anomalies in their business. A typical example is an insurance policy provider experiencing fraud that causes about 10% annual revenue loss. The management can activate a business analytics solution that automates scrutinizing claims without affecting customer service. Auditors can also look closely into the books to find signs of fraud.


  • Better customer relationship


Every business that wants to stand the test of time must understand its customers. This is possible only when the data is carefully studied, and the results are used. This analysis helps to understand what the customer loves and what they detest. Consequently, the company can optimize its service to cater to the needs of the consumers. You should be worried if you get too many customer churns within a period, andyou should want to know why this is the case. Analytics helps to expose the possible reasons for the lapses. After finding these reasons, the business can make possible adjustments.


  • Leads management


Business analytics helps you grade your leads to focus on good ones. Raw data is laced with helpful information that points toward new customers. The results help to determine the leads with greater potential so that you can invest more time in them. Imagine selling a product to a group of young adults who you think would be interested. However, there are thousands of them, and you can’t tell who has a higher chance of purchasing them. Business analytics helps to identify prospective buyers so that you channel your marketing to them. This means that your efforts are more efficient and yield results. You can infuse aspects of digital marketing to reach prospective buyers easily without sounding too forceful.

Now that you understand the importance of business analytics, you want to know how to go about it correctly. It starts with identifying the right population and dealing with them accordingly. It would help if you had a representative sample to help you understand a larger group. 

What is a representative sample?

A representative sample is a subset of data from a larger group with similar characteristics. It helps you identify and analyze the behavior of the larger group. We see this style of analysis outside the business realm, such asin politics, to help identify which candidate is getting more support. Representative sampling saves money for the individual and business. If done correctly, the result doesn’t differ from analyzing the larger population. While this may seem like a shortcut for analyzing data, it is important to be careful to get accurate results. The knowledge of how it works helps to avoid certain pitfalls. Armed with the requisite knowledge, youcan gain better insights into customers and how to enhance their experience.


Let’s say that you introduced a new product into the market. It has been one month, and you need feedback about the product. So far, over 3,000 people have used it, and you cannot get to them individually for their feedback. However, you can get across to 30 people who reflect their thoughts. Ask them your questions and receive their answers with an open mind. After getting their responses, you can analyze the results to gain insights that represent the opinions of the larger group.


Before constructing a representative sample, researchers must keep the following in mind.


  1. Consistency


Business analysts must understand the population they intend to study on a case-by-case basis and test the sample for consistency before continuing the survey. This is crucial for surveys that track changes across time and space. You also need to be confident that the changes in the data reflect the actual situation. It would help if you aimed at consistency from start to finish.


  1. Diversity


As earlier stated, the population is sometimes diverse – that is, people from different religions, age groups, social classes and locations. While representative sampling considers a few people, it should be cut across various population groups. Reaching some portions of the population and convincing them to participate in the survey could be difficult, but it has to be done. The sample population must be as diverse as possible so that the results are accurate.


  1. Transparent


Several factors determine the size and structure of your sample population. Regardless of what it is, researchers must be transparent about their selection. It is imperative to discuss the limitations of this research and be transparent about the procedures followed while selecting the sample. This ensures that the results are not looked down on.


Now that you understand the need to choose a suitable sample for your survey, you can experiment with some representative sample styles depending on your research type.


Here are the four common ways to get an accurate representative sample.


  1. Probability sampling


As the name implies, this type of sampling works with probability. This technique allows you to choose

samples from a larger population using the probability theory. Using this technique, participants must be chosenthrough random selection. This means that everyone in the population under study has a known and equal chance of being selected. So, if there are 1,000 people in the population, every person has odds of 1 in 1,000 of being selected.


Because businesses cannot pick only the best people available, probability sampling gives the best chance to capture a sample that truly represents the population. It also eliminates the potential for human bias or sampling error. This method relies on statistical theory to randomly select a small group from a wider one and predict that their responses would match the larger population.


  1. Simple random sampling


It is never outdated to keep things short and simple. Simple random sampling offers a straightforward path to reaching a viable sample group. This type of sampling assigns numbers to each individual in the group and randomly chooses those numbers through an automated process to determine who should be included in the sample.


The numbers are chosen through a number-generating software or a lottery system. This method also helps to avoid sampling bias. Sample bias occurs when some population members are systematically more likely to be selected in a sample than others. That is, a particular group is underrepresented or overrepresented. The results obtained from this study are one-sided and support only a particular viewpoint. Of course, the results are false. Simple random sampling provides equal odds for every member of the population to be chosen as a participant.


  1. Non-probability sampling


Unlike simple random sampling, non-probability sampling is not random. In this technique, researchers select samples based on subjective judgment rather than random selection. Subjective judgment is not driven by statistical analysis or established formulas. Instead, it relies on expert opinion or experience to identify respondents whowould be part of the sample. In this sampling type, not all population members have an equal chance of participating in the study. This means that each member has a known chance of being selected. The non-probability method is less stringent because it relies on human judgment. It is also prone to sampling bias and human errors. It is sometimes more efficient, but it is only advisable to use it sometimes. It is effective in exploratory studies and in cases where random probability sampling is impossible due to time limits.


  1. Quota sampling


Quota sampling helps organizations make data-driven decisions about a specific subset of data. It is used by businesses that have a small budget for business analytics. This sampling method allows researchers to create a sample of individuals representing a specific population. It also ensures that your survey results closely resemble your target population. This way, you get results that reflect the actual state of things. Quota sampling carries the same risk and reward as nonprobability sampling, but it is a more effective way to capture actionable data from a specific audience.


Importance of representative sampling


Representative sampling remains the best method for analyzing a larger population because it ensures that only relevant people are included in your sample. In cases where you need humans to be interviewed, only qualified persons make it to the shortlist. Here are other benefits of representative sampling.


  • It is credible


Because representative sampling methods are established across academic, scientific and market research, you are confident that the results are credible. The methodologies are not mere guesswork and have been proven to work over time.


  • It is easy and efficient


Representative sampling is one of the easiest ways to conduct market research. Results obtained from the study help businesses gain actionable insights into their customers’ likes and dislikes. All of these can bedone with a tight budget. You spend little but get so much profit in the end. Many startups prefer this type of research method.


  • Actionable results


With representative sampling, you can dive deeper into specific audience segments. A clearer view of the people helps you compare and draw conclusions based on your analysis. This can also serve as a foundation for a customer experience program asit is detailed. You also make data-driven decisions that bring you closer to your audience, especially those who think your products are not impactful.


How to avoid sampling bias


A lot has been said about sampling bias and the need to avoid it. This section explores the most familiar types and the best ways to avoid them.


  • Undercoverage


Undercoverage or exclusion bias occurs when a section of the population is not represented in the sample. Either deliberately or not, researchers can exclude these people. For instance, you’re surveying 5,000 people across urban and rural areas. Because those in the villages have limited access to the internet, the chances are that they would not participate in the survey. If you depend on the results from the cities alone, the outcome would be inaccurate. The best way to avoid this bias is to create an easy and accessible survey. This way, those in the villages can participate even without an internet connection.


  • Non-responsive bias


In a non-responsive bias, respondents refuse to participate in a study. Even when they do, they drop halfway into it. This could be due to the questions’ structure or the survey’s length. Most often, the respondents do not feel comfortable divulging sensitive information regarding their gender identity, marital status, age, income and other personal details. Others are not interested in questions due to insufficient time to attend to them. A survey into drug use in a particular area will likely have respondents unwilling to reveal certain ‘secrets’ about drug use. Defining your target audience helps to create survey questions that are not too intrusive. However, the questions must still be relevant to the overall goal of the analysis.


  • Observer bias


Sometimes, researchers consciously or subconsciously influence the interpretation of data. It takes two forms – focusing on a specific dataset or influencing participants during data collection. A researcher’s presence during the survey can affect the results. A researcher may also misinterpret data so that the results suit their expectation. Establishing what you want to accomplish with your survey helps you determine the best methodology. It gives you a better understanding of who should participate and how best to communicate with them.




The survey aims to get accurate results that the business needs to succeed. If this isn’t achieved, there’s a problem. With the tips in this article, you can take on any business analysis challenge and see actionable results in due course.

Leave a Reply

Your email address will not be published. Required fields are marked *