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Top 7 Benefits of Data Science in Digital Marketing


Trinh Nguyen

Jul 17, 2023

Businesses always struggle to stay ahead of the curve in today’s fast-paced digital environment, where competition is severe and client tastes continuously change.

Data science has become a crucial ally in this endeavor, completely altering how digital marketing strategies are created and implemented. Businesses can improve client experiences, enhance consumer experiences, optimize marketing strategies, and promote growth by utilizing the power of data.

Imagine if energy sources are needed for the operation of engines, and so is data science for digital marketing. In other words, in this era of explosive digital technology development, data science is the essential beacon illuminating the path for successful digital marketing endeavors.

But what exactly is data science, and how does it intersect with the dynamic world of digital marketing? Why has it become the go-to approach for businesses seeking to unlock the full potential of their marketing efforts?

Join us on a journey as we unravel the transformative benefits that data science brings to the realm of digital marketing strategies!

What is Data Science in Digital Marketing Today?


Digital Marketing encompasses a wide range of techniques developed on the Internet to persuade users to purchase products or services effectively.

Companies rely on various strategies to navigate the online realm in today’s digital landscape. These include Search Engine Optimization (SEO) and Search Engine Marketing (SEM) or programmatic advertising. The former involves optimizing search results on major search engines, while the latter entails sponsoring ads in search engines or website banners.

Additionally, Social Media Marketing (SMM) is crucial in allowing businesses to engage with users on social networks through social ads (Lies, 2019; Palos-Sanchez et al., 2019).

Applying data science techniques can significantly enhance the effectiveness of digital marketing. It can augment the impact of digital marketing strategies by:

  • Addressing issues such as managing user-collected information.
  • Refining data types and sources within a company’s datasets.
  • Utilizing novel data analysis and innovative techniques to generate knowledge.

Numerous studies have demonstrated the pivotal role of data science in this industry, showcasing its ability to drive results.

To increase the likelihood of success on digital and social media platforms, companies should leverage Artificial Intelligence (AI) or Machine Learning (ML) techniques to identify unforeseen patterns. Consequently, the digital marketing industry has witnessed growing influence from research domains like Information Science (IS) and Computer Science (CS), as well as other areas that facilitate data collection, organization, and management. These interdisciplinary efforts collectively contribute to the advancement and efficacy of digital marketing practices.

The Growth of Digital Marketing

In 2023, businesses do not need many data analysts and data scientists to generate information about their target audience. It takes a very short time to analyze a large amount of data with abundant automation and machine learning algorithms. Applying data analytics in marketing is no longer a futuristic dream. Let’s score impressive numbers:

  • The global Digital Advertising and Marketing market, estimated at US$350 billion in 2020, is projected to reach a revised size of US$786.2 billion by 2026.
  • Just this past year, 63% of firms boosted their budgets for digital marketing.
  • Fluid Management Systems, estimated at US$11.1 Billion for the global market in 2022, is predicted to reach a revised size of US$18.5 Billion by 2026, growing at a CAGR of 13.2% over the analysis period.
  • 49% of digital marketers report that organic search has the best ROI of any marketing channel (Search Engine Journal).
  • 55% of marketing is digital. Total digital advertising spend in 2021 was $436 billion versus offline advertising at $196 billion.

From the above numbers, we can see that the dominance of digital marketing and data science on businesses is very large, and that influence is increasing.

Why is Data Science Necessary for Đigital Marketing?

Why is Data Science Necessary for Marketing?

The market size for data science platforms got 96.3 billion U.S. dollars in 2021, and it is anticipated to reach around 378.7 billion U.S. dollars by 2030. This represents a compound yearly growth rate (CAGR) of 16.43% from 2022 to 2030.

Modern digital marketing relies heavily on data. And There’s no secret that data analytics is reshaping the sector. It has a stronger impact on the future to help firms develop more intelligent and efficient marketing strategies, better understand customers, and, more precisely, target their audiences.

Machine learning and artificial intelligence are two important areas where data science influences digital marketing. By gathering, processing, and analyzing vast amounts of data, these technologies enable businesses to spot patterns and trends that would otherwise go unnoticed by the naked eye. Businesses and digital marketers can use this data to make the right decisions, enhance marketing tactics, and raise ROI.

Predictive analytics uses historical data and machine learning algorithms to forecast future customer behavior and trends. After targeting their audience with individualized information and offers that are more likely to resonate, digital marketers can make well-informed decisions.

The evaluation of the efficacy of digital marketing efforts also heavily relies on data evaluation. Digital marketers will identify which strategies are effective and which need improvement. They can monitor crucial indicators like website traffic, conversion rates, and engagement to improve search engine capabilities. This enables them to continuously optimize and decide how to devote resources for upcoming initiatives with knowledge.

Reasons to Use Data Science in Digital Marketing

Here are several reasons why data science is necessary for marketing strategies:

  • Machine learning’s expanding usage enables the creation, training, scaling, and deployment of models for diverse marketing applications. Data science platforms offer tools for natural language processing algorithms, aiding sentiment analysis and customer engagement comprehension. Moreover, these platforms empower marketers to leverage machine learning’s potential in digital marketing strategies.
  • The growth of big data technologies and the importance of acquiring and using data for decision-making will fuel the data science platform market over the forecast period. Furthermore, the market will predictively expand throughout the projection period. It’s because of the demand to adopt cloud-based products and services and target developing and untapped markets for data science platforms.
  • Data science is no longer an optional expense for businesses undergoing digital transformation. It’s now essential, as many companies are being assessed to use a data-driven approach in their operational environment.

For instance, companies have been employing predictive models every three months to disseminate marketing offers to about 10% of their customer base for the past ten years. And they have been pleased with the operational outcomes.

But in the current market context, firms must offer real-time guidance to 100% of their customers, not simply 10%. Additionally, across several of their functional divisions, including sales, operations, manufacturing, and human resources, companies publicly state their desire to undertake model-driven campaigns regularly.

Top 7 Benefits of Data Science in Digital Marketing

Top 7 Benefits of Data Science in Digital Marketing

#1 Enhance Targeting and Personalization

Enhancing targeting and personalization is one of data science’s main benefits in digital marketing strategy. A digital marketer can segment customers based on demographics, behavior, and preferences by thoroughly understanding their target audience via enormous amounts of customer data. The digital marketer can design highly focused ads that are suited to particular client categories thanks to segmentation.

Regarding AI in content marketing, marketers typically use word clouds to analyze social conversations. Word clouds, still, were useful when there was a lot of social interaction.

When there was less social interaction, marketers tended to use irrelevant keywords. They can go beyond word clouds using data science and natural language processing algorithms, contextualizing word usage, and presenting appropriate information to entice clients.

According to a Google marketing survey, 90% of seasoned marketers believe that targeted marketing leads to higher company earnings. You can produce highly targeted materials using extensive information about clients. Based on their profiles, purchase histories, and surfing patterns, analytics software may predict customers’ desires, improving the customer experience.

#2 Improve Customer Insights and Analytics

Businesses may analyze enormous amounts of data using data science to acquire deeper customer insights.

Digital marketers may develop a thorough understanding of their consumers’ journey and behavior by utilizing various data sources and incorporating data science, including website analytics, social media metrics, and transactional data. Thanks to this intelligence, they can recognize patterns, trends, and customer service issues and develop successful marketing campaigns.

For instance, by analyzing customer feedback and sentiment data, a hospitality brand can identify areas of improvement and implement changes to enhance guest satisfaction, resulting in positive reviews, increased loyalty, and referrals.

#3 Recognize Relevant Channels

Data science enables marketers to identify the appropriate channels for their marketing initiatives. A digital marketer may identify which channels and touchpoints that have the greatest impact on conversions by looking at historical data and performing attribution modeling. This knowledge enables them to manage resources wisely and optimize their marketing mix.

For example, a software-as-a-service (SaaS) company may discover through data evaluation that their target audience engages more on social media platforms like LinkedIn rather than Twitter. By shifting their focus and investing in LinkedIn ads, they can generate higher-quality leads and achieve better conversion rates.

#4 Predict Analytics and Forecasting

Digital marketers can use predictive analytics and forecasting methods to foresee customer patterns and behavior with the help of data science. Data science methods let marketers make a predictive lead rating system. This technique assists your data scientist in calculating the probability of conversion and segmenting your lead list accordingly.

Businesses can also spot trends in historical data and create models that predict future results. This aids digital marketers in decision-making, marketing optimization, and resource allocation.

Digital marketing data analytics gives businesses a competitive edge. Digital marketers can comprehend the company and consumers and the setting in which they operate. The insights can create marketing plans, draw in new clients, retain current ones, identify underwhelming marketing initiatives, and concentrate on your best-selling products.

To keep business current on the market and better prepare for upcoming difficulties and market sentiment, you can also utilize web analytics tools to acquire information about your competition.

#5 Optimize Advertising and Campaigns

In digital advertising and campaigns, data science puts optimization at the forefront. Digital marketers may maximize the effect and reach of their advertising campaigns with actionable insights to enhance their efforts across various platforms.

Your organization will be more agile when adjusting tactics and optimizing campaigns if you use the correct data science analytics tools to track the performance of your marketing initiatives in real time.

Due to its ability to help you maximize your ad expenditure, this is particularly significant for sponsored marketing activities. You can examine the effects of different marketing channels on consumer behavior, such as the web, mobile, social media, etc. Then, link marketing campaigns directly to crucial KPIs like the volume of website traffic for your business. This will help future plans and increases effectiveness.

In the marketing sector, return on investment is vital. Marketing analytics validates the marketing budget by connecting a company’s marketing endeavors to ROI.

#6 Optimize Marketing Budget

Budgetary restrictions are the main issue for digital marketers. Every marketing team aims to make the most of the return on investment from the allocated budget. But this is frequently difficult to accomplish. Effective budget consumption can be challenging because data occasionally don’t match the plan.

Data science enables digital marketers to optimize their marketing budget allocation by providing detailed visibility into the performance and ROI of each marketing channel. Through data analysis and attribution modeling, marketers can understand the contribution of each channel to conversions and revenue.

This knowledge gives them a helping hand in allocating resources strategically, investing more in channels that deliver higher returns, and adjusting or eliminating underperforming channels.

#7 Enhanced Customer Experience

Data science is necessary to improve the customer experience because it enables companies to provide relevant, tailored interactions at every touchpoint. Marketing professionals can design customized experiences that appeal to specific customers by combining data from numerous sources. For instance, website interactions, social media, and customer feedback.

To attract customers, you must recognize and anticipate consumer behavior trends to tailor your marketing and advertising efforts to meet their requirements. Take email marketing tools as an example. They provide marketing data to monitor subscriber responses, such as social media likes and shares. This results in improved and engaged customers.

In the case of a hotel chain, they can utilize data science to customize offers based on past reservations, customer preferences, and information from loyalty programs, giving customers a seamless and enjoyable experience.

How Leading Brands Incorporated Data Science in Digital Marketing

#1 Netflix

A content subscription service such as Netflix is to encourage repeat viewership by providing compelling programming that compels users to keep coming back for more.

Netflix uses a recommendation engine to suggest new movies and television shows based on users’ watching habits. The ultimate objective is to maintain the user’s subscription on a month-to-month basis, regardless of how enriching, helpful, and personally relevant the service may be for the user in the short term.

#2 Facebook

Facebook’s advertising strategies incorporate a complex data science methodology. They employ unique marketing tactics on a number of other channels. However, they have also been giving advice and marketing resources to the numerous companies that advertise on their platform.

Because these customers are so important to Facebook, it has machine learning models that can examine the success of these online marketing operations and how to make them more effective. The Facebook data scientist team continually develops new insights and solutions to serve its clients better and increase income for these businesses.

#3 Spotify

When looking for new music that meets your tastes, it’s challenging to sift through the enormous volume of music available on Spotify from around the globe, right?

Finding decent music manually is time-consuming, for sure. Understanding this, Spotify has some excellent algorithms to propose new songs to users based on their listening patterns and the tastes of other users.

The Discover Weekly playlist is one effort to address this issue. Every Monday, a custom playlist will be created for each user, relying on their listening preferences.

Equally, the Daily Mix combines songs the user already listens to with new music that will entice them to explore more. At the same time, the Release Radar keeps users informed of new releases from the artists Spotify is aware of them enjoying. These concepts keep each user’s account current, exciting, and fresh without requiring input.

#4 Google

Google wants to provide its business clients with a fantastic return on their investment. Many small, medium-sized, and large businesses use Google as a marketing platform. Smaller companies might not be able to afford to employ a data scientist. Therefore, they must rely on Google to fulfill their needs.

Most small businesses that rely on Google for their marketing analytics requirements won’t have an inside data scientist. Thus, they will take advantage of Google to handle those tasks behind the scenes. The goal is to simplify and make the metrics as easily read as feasible.

Its marketing staff works on delivering adverts to customers who are most likely to make a purchase. In the meanwhile, Google only offers company owners the most valuable tools to build the foundation of their marketing strategy and measure the outcome.

 #5 Coca-Cola

Due to the operation size, Coca-Cola produces a huge amount of data from all points along the value chain, including sourcing, production, distribution, sales, and customer feedback. Over the years, the company has used big data to inform its overall marketing strategy.

Coca-Cola has millions of followers on social media and numerous other channels through which it can collect client information. To ensure that business gains as much insight as possible from the data, Coca-Cola has substantially invested in artificial intelligence (AI) research and development.

The data explains who is consuming their products, where their customers are, and why they talk about their brand under certain circumstances.

The company utilizes algorithms to determine the best method to display advertisements to photographs of its products or those of competitors that are posted online and AI-driven image recognition technology to find them. It claims that ads targeted in this way have a four times better chance of being clicked than ads targeted in other ways.

Final Thoughts

The incorporation of data science in digital marketing has altered how organizations interact with their target audience and achieve extraordinary growth.

Data science empowers marketers to make knowledgeable decisions, personalize experiences, optimize campaigns, and increase returns on investment. To achieve that, it leverages the power of sophisticated analytics, machine learning, and artificial intelligence.

In this pursuit, Neurond, a leading AI development company, stands out as a reliable partner that can help businesses leverage the immense potential of data science in digital marketing efforts.

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” Geoffrey Moore, an American Management Consultant and Author.

Apart from digital marketing, data science does wonders for other industries. Check out how data analytics revolutionizes transportation and the way data science transforms eCommerce.