Analytics, Visualization, Reporting 2018-03-13T16:28:47+00:00
Quantilus Analytics and Visualization

Analytics, Visualization and Reporting – Data Warehousing, Business Intelligence and Big Data

Turn Your Data into Opportunities

Your data is your business. But it’s a challenge to make use of all the unstructured information that’s available to your company—whether it’s internal data such as emails and click streams, or data that originates outside your organization, such as photos and social media content. Quantilus can help you collect, organize, and analyze this trove of information so you can make better business decisions. With a plan in place, you can discover connections among disparate streams of information. From there, you’ll be in a position to:

  • Increase your competitiveness
  • Gain new insights into your customers and industry
  • Adapt more quickly to changing business environments

We’re experts at sifting through large volumes of data to find the hidden connections that you can turn into opportunities. We use our deep industry experience to create models to help you spot trends, identify hidden relationships, and find new insights to create more value for your business.


SA Global - Social Media Popularity Scoring

SA Global – Celebrity Social Media Popularity Scoring

SA Global - Social Media Popularity Scoring
OSU Student Analytics

Ohio State University – Student Performance Analytics

OSU - Student Performance Analytics Dashboard
Market Research Data Visualization

OSG – Market Research Data Visualizations

Market Research Data Visualization
Bed Bath Beyond - Centralized Customer Database and Reporting

Bed Bath and Beyond – Centralized Customer Database and Reporting

Bed Bath Beyond - Centralized Customer Database and Reporting
NYMAGIC - Claims Analytics for Marine Insurance

NYMAGIC – Claims Analytics for Marine Insurance

NYMAGIC - Claims Analytics for Marine Insurance


Some of the frameworks and tools that our development teams have used recently. A list that grows by the day.


Relevant, interesting and current curated research content in the field.

What is the Internet of Behaviors?

January 15th, 2021|Categories: Data Science and Analytics, Emerging Tech - AR, Cloud, Blockchain|

The Internet of Behaviors is one of the top tech trends of 2021. This is partly due to the pandemic shifting how consumers interact with brands, consequently requiring companies to adjust how they engage with consumers. However, before we dive into what the Internet of Behaviors (IoB) is, one must first understand the Internet of Things (IoT). IoT refers to any device that is connected to the internet such as smartphones, virtual assistants like Alexa, fitness wearables, appliances, TVs, and more. To learn more about the Internet of Things, check out our article explaining the technology and how it’s used.

Defining the Internet of Behaviors

In short, the Internet of Behaviors utilizes collected user data to influence behaviors. So, what does that really mean?

Essentially, companies analyze the data collected from a variety of Internet of Things devices. Businesses then use this data to change consumer behavior. Some of the data companies may record include a person’s geographical location, time spent on a particular app, and what time a person wakes up among many other pieces of information.  More often than not, the goal of changing consumer behavior is to get them to buy or engage a particular product or service. However, this technology can also be used to change the behaviors of other stakeholders, including employees to ensure they are following correct procedures.


How is the Data Collected?

Data from consumers can be amassed from numerous sources, including a company’s website, social media profiles, sensors, telematics, beacons, health monitors (ex. Fitbit), and a wide variety of other devices and places.

Each of these sources collects different pieces of data. For example, a website might track the number of times a particular user views a specific webpage or how long they stay on a page. Furthermore, telematics might monitor how hard the driver of a vehicle brakes or the driver’s average speed.


What Happens to the Collected Data?

Businesses collect and analyze the data for a multitude of reasons. These reasons include helping companies make informed business decisions, personalizing marketing tactics, product and service development, driving user experience design, and more.

To help analyze this data, companies set benchmarks in place. Meaning, when a particular action(s) is performed by a user, the company then begins to persuade the user to change their behavior. For example, if the user returns to a company’s page selling men’s skinny jeans more than three times, the digital retailer might serve the user a pop-up ad offering them 25% off a pair of jeans. The digital retailer is aiming to get the consumer to buy the pair of jeans.

Another example is that if a driver regularly brakes too abruptly, telematics can alert the driver to make them aware of a recurring issue. In this example, behavior telematics attempts to change the driver’s braking habits.


Combining Data from Various Sources

An additional aspect of the Internet of Behaviors is combining data from different sources and analyzing it to make a decision. Pulling data from various sources provides companies with the ability to create in-depth, user profiles for each user. These profiles can then be examined to determine the best course of action to take regarding the user.

For example, a consumer named Ted comments on a picture of a new sneaker on brand’s Instagram page. A few days later, Ted then heads to brand’s website and looks at the same shoe. A week passes, and Ted is on YouTube watching a commercial featuring the shoe. Meanwhile, the brand is tracking all the touchpoints Ted makes along the way with the digital content. The brand can then synthesize this data and develop a course of action on how to convert Ted into a customer, since the brand identified that Ted has a high-interest in its shoe. Actions the brand may take include remarketing display ads or emailing Ted a discount code. 

Another example is if a consumer records their workouts on their smartwatch. When the watch is in workout mode, it can track the user’s heart rate. Therefore, when the user’s heart rate reaches or exceeds a certain level, the watch can send a notification to the user reminding them to drink water. This is beneficial for the user because they are reminded to hydrate and cool down, while the company is provided with valuable insight of how the watch is used.


Ethical Implications

The Internet of Behaviors is an innovative technology for businesses; however, the tech does come with ethical concerns. The majority of worries stem from user and consumer privacy.

Controversy surrounds the intrusiveness of the data collected. This is because the data can be obtained from countless locations where consumers may not even realize they are being tracked. Furthermore, the sensitive nature of some of the collected data is also a concern. For example, if a consumer is wearing a smartwatch, the data collected by the wearable technology can be highly private information, such as the consumer’s heart rate. Therefore, users may not be aware of all the data the watch is collecting, nor how the data will be shared (or sold) or will be used to influence their behaviors.

There is also the concern about cybersecurity. Businesses are currently flocking to the cloud to use as their company data warehouse. Consequently, hackers and cybercriminals may attempt to gain access to this data and do with it as they please, including leaking or selling the sensitive data.

Currently, laws regarding the Internet of Behavior vary widely, but we should see more consistency in the coming years.



The Internet of Behaviors provides companies with cutting-edge ways of marketing products and services, along with influencing user and employee behaviors. This technology is extremely beneficial for businesses since they can optimize their relationship with the consumer based on the collected data. Behavioral data technology continues to evolve. However, with the proliferation of new IoT devices, the debate over what constitutes essential data and responsible use is just getting started.

Interested in learning ways to implement data science and analytics in your business? Contact us at for a consultation to learn how we can help.

Implementing Cybersecurity During The Coronavirus Pandemic

June 29th, 2020|Categories: AI, NLP, Machine Learning, Data Science and Analytics, Emerging Tech - AR, Cloud, Blockchain, News and Announcements|Tags: , , |

Quantilus Innovation continually monitors cybersecurity news and developments that could impact companies like ours—and yours. Our team has compiled useful information and resources below to grow awareness of potential threats and prevent any compromise to systems.

Most of the working world continues to be a participant in a massive experiment on distributed, remote work structures. However, the coronavirus pandemic combined with the unprecedented, massive work-from-home shift creates another kind of threat—a breeding ground for cyber criminals to capitalize on vulnerabilities. The public health crisis has sparked a rise in cyber incidents, from phishing scams and malware to VPN DDoS attacks and vulnerabilities with teleconferencing and cloud SaaS applications, so here’s the latest on what you need to know:

Contact us to discuss penetration testing and other assessment options.

The cybersecurity specialists at Quantilus can identify your company’s susceptibility to specific external and internal threats and collaborate to mitigate the short-term and long-term risks. Call 212-768-8900 or email

Using Longitudinal Data Systems to Reexamine Timeless Problems

January 12th, 2018|Categories: Content Mgmt and Publishing Tech, Data Science and Analytics|Tags: , , , |

This is a proposed research approach that attempts to shed light on the cyclical nature of education problems and our inability to adequately address these problems. We continually examine bits and pieces of the education process to understand the whole. This paper suggests that the use of longitudinal data systems be utilized as a holistic approach to reexamine issues regarding the degree of efficiency of our schools. Specifically, addressing the dropout problem through intervention strategies that are implemented at the wrong time will never be successful. Using longitudinal data systems with complementary analysis techniques, such as survival analysis, may help resolve some of the questions that have plagued the American education system for the past century.

Click Here to Download Paper

Using New Data Analysis Techniques to Understand Information Flows

January 12th, 2018|Categories: Data Science and Analytics|Tags: , , |

Information flows motivate key questions in the major social sciences. The movement of social activity to the Internet means that it is now possible to study information flows directly in a much more systematic fashion than before – data on many forms of social interaction is readily available in machine-readable format. This White Paper proposes a two-stage program to develop new tools in conjunction with pilot initiatives studying information flows, and then apply them more broadly. It then outlines how these methods and data might be applied to three major problems spanning different social sciences – collective cognition, frames and mobilization, and political polarization – and concludes by discussing the policy benefits of better analysis.

Click Here to Download Paper