An In-Depth Analysis of Behavioral Data Science

In the world of data science, you will come across new technologies and terminologies every once in a while. Modern data science can be utilized better in other industries such as medicine, psychology, healthcare, retail, marketing, transport, and telecommunication. So, you may ask how it affects the society. Well, data is an integral aspect of many industries and if data science is not integrated to get accurate results from the data, these industries won’t function and our livelihood will be hampered. Behavioral data science is one aspect that has its roots in psychology and is considered equally important to society. This article enumerates on this topic.

Firstly, Let Us Look at the Definition of Data Science

The term ‘data science’ is interdisciplinary and can be applied to several industries with the right tools, processes, and techniques. It uses your knowledge and expertise in programming, statistics, machine learning, and algorithms to combine or examine larger data sets.

The primary function of data science is to help data scientists read into the data they collect and uncover actionable insights hidden within it.

The insights that are gathered would play an active role in driving strategic planning and decision-making within an organization.

Some Examples of Data Science in the Context of Modern Society Are as Follows:

• Data science is convenient when organizations are advertising online. Collecting user data and applying it to customize the advertisements which they see, is a major revolution in the advertising industry and is much superior to the ways of traditional advertising. Top brands like Amazon, Google, Netflix, and Instagram utilize data science technologies to present their customers with personalized ads.
• In the healthcare sector, companies have introduced AI-powered mobile applications like chatbots or AI assistants who are available every second and can address queries from patients at a much faster rate. Some applications enable you to get an update on your health status based on a large network of clinical symptoms or signs.
• In the case of transportation and live location, you can get a better example of data science techniques. Companies like Uber, Ola, and In-Drive optimize cost as well as routes by combining different elements like customer behavior, location, logistic providers, and economic data.

How Can You Define Behavioral Data Science?

The term ‘behavioral data science’ combines several disciplines and combines into something more futuristic and innovative. It is a field that focuses on studying human behavior and infuses it with algorithms or frameworks that expand amounts of information.

Behavioral sciences like sociology, psychology, and economics work together to present you with a plethora of computational approaches from computer sciences to statistics.

It is more psychological because the approach of this field tries to understand human nature and systematic behavior regarding increasing quantities of data.

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How is Behavioral Data Science Different From the Data Science Industry?

As a fellow data scientist, it is important to know what separates data science from other fields it can be applied to. In the modern age where almost everyone leaves behind a certain amount of digital footprint, data is readily available.

With data science, you could manipulate this raw data and uncover meaningful insights that directly affect the profitability of a business. So, you can understand the crucial role it has to play for businesses and organizations to entirely depend on it.

The average characteristics of data science include the use of machine learning algorithms to process large amounts of data and make predictions, analyze different patterns from it, and provide recommendations.

You have seen its prominent applications in facial recognition systems where small details of your face are taken into account to paint the whole picture. Moreover, an individual’s buying pattern or general preferences are tracked with algorithms to show them more personalized recommendations.

Behavioral data science focuses on this aspect of human behavior, such as why people are more inclined to buy something more than the other. This field uses hybrid deep learning models to try and learn more about human psychology and understand what is driving their general ideas and biases towards certain products in the market.

This helps better predictions to be made as well as accurate patterns to be identified in the future. This discipline lets companies form a closer relationship with their customers by letting them uncover their strengths and weaknesses.

For example, a company can understand what its customers are lacking in their product or service and introduce new changes to the product or service to better suit their needs.

Thus, if data science is something that companies depend upon, then behavioral data science provides it with the means to thrive.

How Do Data Scientists and Behavioral Data Scientists Work?

The day-to-day work done by data scientists includes several steps like data cleaning which involves preparing the data and organizing it, data analysis for performing statistical analysis on data and uncovering patterns or trends and data visualization which helps represent technical data into graphs.

The results that they can uncover can be used to develop data-driven solutions as well as address common challenges across several industries. Data scientists must keep in mind their project goals and specific key performance indicators aligned with business objectives, that help measure their level of performance.

Behavioral data scientists, on the other hand, are inclined towards studying human behavior based on data. Their responsibilities revolve around conducting surveys or research that obtains a deeper understanding of the human mind and what drives its decision-making ability.

This job allows you to get insight into general patterns of behavior enabling the prediction of what someone might do next. Behavioral data scientists would often prepare questionnaires, research models, and focus groups which assist their work process.

Data for this discipline is generally collected from the amount of time you spend browsing web pages or social media apps.

Your data is essential to several big companies and your online presence alongside browsing history is categorized into first-party, second-party, and third-party data, each having a purpose to play.

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What Are the Different Types of Data in Behavioral Data Science?

Just like data science has different types of data, behavioral data science has several types in its data sets from which companies can benefit. Data that is used to analyze human behavior is more readily available than one could imagine.

‘Behavioral data’ is mostly concerned with the information that companies acquire on customer interactions with businesses across channels.

The most popular means for collecting this type of data is none other than online websites or other applications, where views, usage history, user engagement, and online transactions matter.

Its utmost importance is prominent when as a data scientist, you can uncover customer preferences and be able to effectively guide marketing strategies. Similarly, it enhances your chances of reaching out to a wider audience when you’re working on an advertisement campaign for your latest product or service.

The following list contains some of the data types you’ll come across when working in the Behavioral Data Science domain:

• Webpage or Content Views:

Have you ever spent more than a few minutes on an advertisement that happened to catch your attention? Or scroll through several web pages that may or may not be related to a common topic?

Every second you spend on a webpage or any form of online content, whether image or video, would be considered as a view and it is exactly what serves as valuable data.

Your viewing history provides companies with a good understanding of what type of product or service you are most likely to go for next. It provides insights into what topics you are interested in, enabling a more customized browsing experience for you. Moreover, this type of data helps content creators target the right audience.

• Data from Applications:

Applications have a similar process of keeping track of their customers, but the methods involved are rather different. Several tools involved in tracking data for Behavioral data science help you define custom events to keep track of the users. It provides clear insights into what exactly the user is interacting with or not interacting with.

In-app surveys and creating options for users to give their feedback is another way that help you connect with a user’s journey when they eventually stop using the application. You can understand what needs to be changed or improved.

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• Email Tracking:

Since promotional emails are a great way to advertise your brand, email tracking is another source of collecting behavioral data. It also serves as a way for small brands to reach potential customers on a personal level if they are customizing their emails.

But, simply tracking an email does not associate with the customer’s interest. Therefore it is important to analyze a wider list, which provides better clarity on following up the emails with custom messages.

An advertiser also needs to keep track of external factors like time zones or what headlines are likely to be trendy.

• Organic Search Data:

Platforms like Google and Microsoft generally have large volumes of searches every day. Collecting the search data from these platforms can be a great way to understand customer behavior.

Customers are more likely to search about the product before buying it, thus the search provides the seller with information on their customer’s next course of action.

There are free as well as premium tools like Google keyword planner, Semrush, Ahrefs, etc that help you access worldwide or location-based searches. These searches are also quite helpful when identifying what product or service is highly in demand at the time or what customers are more inclined toward.

• Product Usage and Reviews:

Another great way to tap into the customer’s mindset is to follow up on product reviews or track the usage of a certain product. In behavioral data science, reviews and feedback play an important role.

You get to understand what exactly they liked about a product, what they didn’t like, or the challenges they had with the product. This paves the way for competitor analysis to help you get a better understanding of your position in the market.

Although you can begin from anywhere, the best starting website for accessing product reviews is Amazon and other shopping sites.

• Paid Advertisements and Ad-clicks:

Working on paid Ad campaigns and running an advertisement on platforms like LinkedIn, Facebook, Google, Instagram or Twitter (X) provides you with massive amounts of behavioral data.

The number of clicks on your Ad or the number of times it has been viewed helps you understand your customer better. Moreover, you can check what type of Ads or messages people usually respond to compared to what appeals to them.

You can test out various possibilities with your Advertisement, to settle for the one that converts to action and drives sales.

• Purchase or Transaction History:

Customer’s purchase history lets you know what their needs and wants comprise. It also tells you how much someone is likely to spend on a given day. This type of behavioral data makes it possible for you to send targeted offers to selected individuals and identify cross-selling opportunities.

For a more generalized approach, you may access anonymous transaction histories which let you understand the spending habits of an individual while keeping the products they buy hidden from you.

This lets you focus on the more obvious behavioral data. Analyzing customer purchases helps you forecast the demand for certain services or products.

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What is the Career Path in Behavioral Data Science?

Behavioural data as a career is fairly new considering the existence of data science and other fields that contribute to behavioural sciences. The career trajectory for this field helps you focus on new trends and build your skill sets.

This discipline lies at the interface of the other disciplines since it’s only interested in combining deep knowledge about the questions centering around systems behavior, algorithms, and human behavior.

It lets you know how one’s well-being can be measured or improved, how the supply chain in the industry can produce something in demand, and understand algorithmic behavior in a better way.

If you are interested in taking up this discipline seriously in the future, the following list will guide you:

Education: Enhancing your knowledge with further studies is always recommended when it comes to gaining exposure to a particular field. It is the technique that inevitably opens up several doors for you.

Today’s top professionals have followed this path to success because it almost has no negative side to it. Most higher-level education programs are equipped with extensive curricula on the topic and sessions guided by experts.

This gives you an upper hand when it comes to networking. For any education program, the ways of learning and research are crucial stepping stones.

Applied Behavioural Science Career Path: You may choose to go down the path of applied behavioral science, which is not similar to behavioral data science but leads you to several career options.

To achieve this, the course of study you need to undertake may include the basics of psychology, sociology, neurobiology, child development, community health and development, etc.

If you are an aspiring professional in this field, you might find a degree in applied behavioral science more helpful for building a career.

Working in the Government Sector: the availability of data and behavioral insights can be found in government sectors of every country. These government sectors are more likely to give you exposure to the appropriate use of data and how it is converted to behavioral data.

Modern behavioural sciences are inclined towards the use of artificial intelligence technologies and automated software for progressing with work because there is a clear priority development of ethical strategies by governments.

Working in the public sector provides you with sufficient data to understand the general behavior patterns of people when it comes to preventing crime or predicting criminal behavior.

Non-Profit Organisations: applications of behavioral data science into the work processes of non-profit organizations and the impact they bring forward have had the possibility of emerging.

Now that these organizations can invest in setting up behavioral science teams, they can seek to pursue innovative approaches that have a greater impact on society.

Examples from research conducted in 2019 state that, some non-profit initiatives on sending out texts to parents of preschoolers and informing them about child development led to better educational approaches on the part of the parent and helped children raise their literacy scores.

Working in Tech Companies: Exposure to the mainstream applications of behavioral science can be learned from the majority of the tech companies in the market. Tech industries are always dynamic and require in-depth research of the customer’s equally dynamic preferences to keep up with the needs of the hour.

However, some of the severe work schedules have been eased out by the introduction of machine learning and related AI-based technologies. The vast amounts of behavioral data that is collected can be utilized in understanding customer patterns such as page views and interactions to convert them into better service.

What Are the Benefits of Working With Behavioral Data Science?

Up until now, you have gained an insight into what this particular industry is like and how it impacts the product market we have today. This field has immense potential for growth and nurturing your skills can get you closer to your ultimate goal.

Moreover, behavioral data has a role to play for every business or organization as well as creating an impact on the population or individual lives. Some of the benefits you can obtain from involving yourself with this discipline are as follows:

Ability to Make Data-driven Decisions: Businesses need to keep large data sets at their disposal to enhance their company’s general performance. Without customer behavior analysis many of its future goals would not have existed, because its products or services are aimed toward specific customers.

Behavioral data enables you to get into the mindset of potential customers and ‘see’ from their perspective. Many big brands like Amazon depend on this type of data because decisions about product development, pricing, and marketing are heavily based on analyzing an individual’s buying behavior. It will eventually help you form a better judgment and achieve improved economic outcomes.

Enhancing Customer Experience: As previously stated, behavioral data science helps you get insights into what the customer is looking for in a product or service.

It can benefit the company if it spends a portion of its time surveying or collecting customer feedback on product usage. So, developers can work on introducing new features or launch a product that meets the current demand.

Behavioral analytics is one aspect that aids such businesses in personalizing marketing campaigns, identifying customer journey friction points, and boosting overall engagement.

Data Security or Cybersecurity: Collecting behavioral insights from individuals can detect chances of fraud or other criminal activities. Applications of this discipline in regular business settings provide better cybersecurity and data protection. There are also increased chances of identifying insider threats and increased regulatory compliance.

Better Prediction Models and Algorithms: Behavioural data also help researchers in this field create prediction models that focus on human emotions based on the data. It explores aspects of psychology, rather than generic data science practices.

If data science predicts that demand for a certain product is low at a given time, then behavioral data tells you what is the reason for such behavior patterns. The Development of hybrid models like anthropomorphic learning has helped research by providing insights into people’s preferences.

FAQs

Q) What is the Salary of Behavioural Data Scientists in India?

Working with behavioral data and excelling in your domain in India presents you with an average salary of 2-3 Lakhs per year, according to Glassdoor. Although it has not earned enough popularity as data science, this field gives you sufficient exposure to the domain.

Q) Is Working With Behavioral Data Science Lucrative?

This sub-field of data science is not as lucrative as data science itself. However, it gives insights into several industries as well as presents a new opportunity for researchers to tap into human behavior patterns.

Q) What Skills Do I Need for Processing Behavioral Data Science?

Some of the skills that you can use to work with behavioral data are similar to what you would use in processing data for data science. You need exceptional communication and presentation skills, collaboration, predictive modeling, critical thinking, machine learning, and more.

Conclusion

Data science is one such discipline that can be combined with several other fields, which equips it with the possibility of branching out and introducing new disciplines. The current job market deems data science as a fairly lucrative career option and related subjects like behavioral data science have scope for evolving into high-earning careers. Through this article, we have presented you with an overview of behavioral sciences and what a future in this career path could bring you. We hope that it answers some of your queries and guides you closer to your goals.