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.

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

Pricing Strategies for SaaS Products

August 18th, 2018|Categories: Data Science and Analytics, Web Development, Marketing, SEO|Tags: , , , |

The Pricing Decision

Your SaaS product is finally ready for market! Hooray! You’ve spent your nights and weekends coding, and have deployed what you think is the production ready version. And now comes one of the hardest decisions you have to make – how do you price the damn thing. Its obviously worth millions (billions?) to you, but how much are your potential customers willing to pay?

For most of your target customers, software is productivity not pleasure. There is no joy in software installation, integration or instruction. Companies undergo the trouble because they have to: the inertia against change is substantial. A lower introductory price might help to work down that resistance, and help keep you on the short list during a long sales cycle. Free beta installations are also part of minimizing the initial implementation resistance.

But once the customer is yours, the situation switches in your favor. The customer is still reluctant to switch to something new, only now they’re afraid to switch from you, and not to you. They would much prefer to add the functionality of your upgrades without having to learn how to use new software. From your perspective, price sensitivity is much lower as comfort and ease factors increase. So we might raise our upgrade price accordingly.

While acquiring new customers is great, you also need to realise that once a price expectation is set it is very difficult to move away from that. So if you price too low to penetrate the market you may end up losing money when you are unable to raise prices later. We will now discuss some of the common strategies adopted by companies in making the right decision.

Pricing Strategies

Pricing strategies fall into one of several categories. While most companies with multiple products will use multiple pricing strategies, each product has a dominant pricing strategy. The common strategies are described below:

Cost Based

Vendors price their products based on the variable cost of goods. They may use rules of thumb like $10 over cost or 3X manufacturing cost. Many hardware manufacturers used to do this. Software distributors often use this method. However, this strategy does not consider the value to the customer. Also, you must be a low cost producer to win.

Value Based

This strategy is based on the performance/price ratio of a product. Vendors using this strategy offer a performance premium at a given price point (e.g. optimized workflows and document storage at lower prices). They can also offer a choice of performance options at different prices (e.g. good, better, best products at three different price points). They do not cut price to raise the value ratio.

Meet the Competition

This is often a promotional ploy and not a long-term strategy. However, many companies will have products that are directly comparable to a competitor’s offering. Competitors or customers will force these companies to play this game. Competitive upgrade and “suite” prices are two examples.

Market Skimming

Market skimming (as in “skimming the cream off the top”) strategy involves a new product in an emerging market setting a high price point to maximize revenues before the competition catches up.This was a common strategy for some engineering software companies and super-minicomputer vendors. Companies that are “first with the most” may be able to do this until a competitor catches up – or catches on.

Market Penetration

This strategy is the opposite of a skim strategy. In this case a vendor offers unheard-of-value at a price point. In the early 80’s, workstation vendors offered $50,000 products that outperformed $250,000 minicomputers. At a time when IBM’s Rational Suite was being sold for thousands of dollars a seat, Atlassian began offering JIRA and related products at tens of dollars or lower. At launch Atlassian’s functionality and performance was significantly lower than the competitions’, but their penetration strategy enabled them to overcome that hurdle. This strategy expands a market by opening new, price sensitive segments. If the price is so low another entrant cannot make money, this is also called pre-emptive pricing.

Follow the Leader

Many companies have a commanding lead in their product category like Oracle in databases, Microsoft in PC operating systems. In any product segment, any direct competitor will be compared with the leader. Many times, direct competitors have to follow what the leader does in pricing. IBM used to be a price leader in mainframes. Other mainframe companies followed their pricing lead and would price somewhat below IBM’s price points. When IBM lost their leadership position in the PC industry, prices collapsed.

What is the Best Pricing Strategy for Your SaaS Product?

In the case of your specific SaaS products, ask yourself the following questions:

  • Is there a dominant player in your market, and therefore does the Follow the Leader strategy apply?
  • Is the product or the concept new or radical enough to justify a market skimming strategy?
  • Are customers price sensitive and therefore is pricing a key factor in market penetration?
  • Can you quantify the value that your SaaS product is adding to the business processes of your customers?
  • Has the established competition already set the price range? This is especially true for relatively mature markets where you have little price flexibility and have to compete primarily on functionality.
  • Are your costs directly correlated to your revenues? Will increasing your base costs (and therefore quality/throughput) increase penetration?

The best pricing strategy for the product will usually to be a combination of diferent strategies based on answers to the questions above. For most products surveyed as part of this study, the strategy was a combination ot Cost Based, Value Based, and Competitive Pricing.

Costs and Value – Considerations for Pricing

Relevant Costs

Strategic pricing is a means of making a profit today, not of recovering costs spent a year ago. Therefore you should not use the cost of developing Version 1 as the basis of the price of Version 1. Instead, you will have to use the cost of developing Version 2 as the basis of the price of Version 1. In other words, the price of your SaaS product should be based on the cost of developing the improvements and enhancements that you can foresee for the next significant upgrade.

The other costs that need to be covered are the manpower costs incurred for actual implementation (customization, development of templates, etc.), training of users and administrators; and the marketing and administrative costs incurred.

Elements of Value

The initial step in establishing a value for the product is to determine whether a software product should be considered as a “tool” or as an “asset” that should be managed according to a dynamic usage metric.

Software products that that fit the “tool” category are usually relatively low cost and/or the product’s value is driven by the ability to solve potential problems at any time rather than actual use. Typical metrics are either node based or named user based.

As value increases, products are viewed more as assets. In order to manage these assets well, dynamic licensing metrics need to be chosen that closely approximate use or “work accomplished”. These software products can be segmented into categories according to functional characteristics and usage characteristics; different licensing metrics may fit each of these segments. The dynamic license metric most commonly chosen is the number of transactions, as this precisely measures the “work accomplished”.


For more interesting strategic discussions about SaaS product development and marketing, contact us at Quantilus.

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