Data Science for Business

5 min read
Mar 31, 2022 4:54:38 PM

Learn how to use Data to know your customer and boost your business.

If you are unaware of current consumer trends, you will never be able to connect with them.

Brands must understand their users' demographic traits, societal changes, digital behaviors, trends, and expectations to provide the most meaningful content, personalized attention, and deliver the right message.

In this process, Internet data analytics is critical since it enables you to create more targeted offers and campaigns relevant to your audience.

Data science for business allows you to understand your customers, resulting in improved products and services, a superior customer experience, and increased value.

What is Data Science?

Data science is an interdisciplinary field that uses scientific methods, procedures, algorithms, and systems to mine organized and unstructured data for usable information and insights.

Data scientists collect and interpret data to understand customers’ needs and identify new business prospects.

There are algorithms for every requirement; it is a highly academic subject based on mathematics and statistics, and as such, you would want a highly skilled team to do the task at hand.

Occasionally, this is prohibitively expensive or time-consuming for a single job.

How Big is Big Data?

As the term suggests, big data is all about massive volumes of information. But how much information is too much? That is a brief answer: when numerous databases exceed one terabyte in size, we begin to speak of big data.

Big data entails significant technology requirements, particularly when it comes to data science for business.

Typically, these requirements result in technological infrastructures that are too huge and expensive to meet the project's needs.

At the Analytics Forum 2018, hosted at the Universidad de Los Andes, experts concluded that traditional programming (relational models) forces us to seek technological solutions that are significantly bigger.

These types of software can flawlessly process up to 500 million records in two to three minutes (which is an excellent processing time).

Additionally, the tool's ease of use enables an end-user unfamiliar with programming to implement predictive and segmentation models and obtain information effortlessly and efficiently.

First, we must understand the need to implement effective and cost-efficient models. Hence, we interpret the data accordingly.

Before You Consider Starting Using Data Science for business

While Big Data presents itself as a solution for the systematic management and processing of massive volumes of data, its success is contingent on the obstacles that limit its proper application in business.

The growth of the Internet has increased the number of devices that collect and transmit data via their sensors.

This context enables an organization to adopt a data-driven culture.

Still, while Big Data enables its analysis of volume, speed, variation, correctness, and value, sound counsel is vital.

Because the usage of Big Data creates a flood of expectations within businesses, it is critical to be aware of the agents that may cause a delay in the advancement of the processes developed in the first place, such as:

Technology: Businesses are occasionally inexperienced with modern technology regarding specific programs or software.

Cultural change: It is critical to understand how to target each audience, as one motivated by data would differ from one inspired by intuition.

Limited investment: What is the expected return on my investment? This is the typical question companies ask, given the difficulty of obtaining funding for these projects.

Analytical talent shortage: You need mature people in their work, with an analytical mindset, willing to expand their talents using Big Data.

Management opposition: This happens when a company has established KPIs or when management lacks experience with their usage, refusing to learn about their potential and transforming Big Data into something systematic.

These roadblocks can be overcome by understanding the capabilities and possibilities of analytics and by assembling a team with the appropriate skillset and stacks.

Our High-Performance Teams are experts at analyzing current market difficulties through the lens of data science for business. 

We place a premium on offering the most outstanding personnel for each project stage, including creativity, design, implementation, and evolution of technology solutions.

This procedure requires highly qualified individuals, including data scientists, data architects, data engineers, and the assistance of several additional data analysts and researchers.

What Strategies Can You Develop with High-Performing Teams?

To help you better understand the possibilities of data analytics, we will give you a practical example.

Comfama is a Colombian family benefits fund with almost 2,000,000 affiliates in the region.

The use of data science for business allowed Comfama to identify the preferences of its users and reach them with the ideal message to increase conversions.

Usually, Comfama sent mass communications to its users without deep analysis. They noticed the need to reach them with an appropriate message.

Therefore, they decided to create a “Relationship” unit and look for an ally to segment his customers and achieve a high customer loyalty rate.

Teams from Pragma and Comfama analyzed and segmented the users who participated in their education, sports, and culture programs to propose intelligent campaigns based on data analytics to increase the number of people enrolled in Confama’s courses.

The data analytics experts at Pragma received as input a database with 1,997,728 enrollment records of its programs from the last three years using data science for business methodologies. 

Our first approach was to convert that information into unique users. There were 315,627 people left with new variables that we calculated based on the objective we pursued: continuity of users, classifications by age, and topics of interest in the courses.

The research also allowed us to get to know the users, identify combinations of their preferred themes and common patterns.

With the data analysis, Pragma sent 48,168 segmented emails, with an open rate of 32.4% and a click-through rate of 6.5%.

From the opening rate, 43% were from the group of people enrolled in Art. They received the recommendation of joining the Sports program.

Of the 15,000 users who opened the email, 4,531 clicked it. Of those, 3,698 enrolled in Comfama's Sports and Art programs.

This number represents a conversion rate of 81% of a successful emailing campaign.

What Are the Benefits of Big Data Analytics?

Without question, the benefits of Big Data are evident when combined with Business Intelligence and advanced analytics tools and supported by high-performing IT teams.

First, it provides information and benchmarks by allowing you to respond to several inquiries from your company.

Second, due to the resolution of business difficulties that traditionally require additional time and ren short, practical usage of Big Data results in several benefits for your business.

Smart Segmentation

Using Big Data, it is feasible to leverage all of an organization's client data to produce targeted marketing.

Similarly, efficient data managing improves the creation of products and optimizes customer service. You may tailor your products to target specific customer segments.

Automatic Communication Campaigns

Today, with the information provided by Big Data, it is possible to evaluate and forecast a user's behavior on the network, to learn what customers think about a brand or a product, and to ascertain their actual needs when it comes to the acquisition of products or services.

Parameters relating to each user’s unique profile, tastes, trends, or relationship with the business can be analyzed to design highly personalized targeted marketing campaigns.

Sales Forecasts

Data mining and analysis assist in determining client behavior and pricing. As a result, Big Data enables real-time updating, optimization, and refinement of stocks depending on demand and a better understanding of your potential profit.

Contact us for a Data Science for business solution

At Pragma, we digitally transform the largest companies in Colombia and Latin America.

We were able to influence corporate processes and customer experience from a close distance using agile model frameworks and the Nearshoring business model, from which we adapt our teams and specialists to your firm's demands.

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