Contemporary Analysis is the Amazon EC2 of the Data Science World

The greatest improvement in the productive powers of labour, and the greatest part of skill, dexterity, and judgment with which it is any where directed, or applied, seem to have been the effects of the division of labour. – Adam Smith
Ever heard of Instagram? How about Reddit, Urbanspoon, Pinterest, Spotify, Dropbox, Tumblr, Netflix, or Yelp? These companies, and many others, owe their existence to a young technology quietly advancing the web.  The technology is Amazon Web Services (AWS).  The impact has been enormous.  Amazon Web Services (AWS), an umbrella for a handful of cloud computing platforms, has democratized super computing for anyone with a visa credit card.  Now, companies can get their websites and products delivered faster and cheaper than ever before, because they only pay for what they use and when they use it.
Technologies like elastic load balancing and auto scaling allow anyone to use, and pay for, only what they need of the processing or storage capabilities of AWS. Rates start at $0.06 per hour. Security, maintenance, and backups are also taken care of so you can rest easy knowing that the nominal rate of pennies-per-hour also buys you peace of mind you wouldn’t have with the massive overhead of running your own computing platform. These benefits have made AWS the go-to-standard for things like modeling DNA, aerospace research, jumpstarting web companies with between 0 and 1,000,000+ users, and countless other uses.
Contemporary Analysis brings the same ethos to data science. How would your business change if you had the ability to immediately solve the most mission critical problems, predict future scenarios, or run a few experiments without worrying about the nightmare of setting up an expensive, massive, in-house data analytics team?
With Contempory Analysis, you have on-demand access to some of the brightest minds in data science with backgrounds in economics, engineering, finance, law, philosophy, and neuroscience on a monthly, quarterly, or yearly basis to help solve your most pressing business questions. And we start right away.
Most of our solutions start at prices that don’t require an OK from upper management. So pull out that Visa and we’ll show you what we can do.
Additional Reading:
The Economics of AWS vs Owned Infrastructure

How Much Data Do I Need For Predictive Analytics?

Before beginning any predictive analytics project, its essential to investigate the breadth and depth of data available. However, at what point is it acceptable to say you have enough data to start?
The politically correct answer to this question is that it depends. Depends on what though?
Well for starters, certain types of data science and predictive analysis projects require more specific data requirements. In an extreme case, predicting survival rates of people or machines may require data spanning their entire lifespan. However, in most cases, data requirements are less stringent.
In most cases taking a snapshot of 3 to 5 years worth of data can yield a breadth of patterns surrounding consumer and business behavior. Why? (more…)

Analyzing the Future: Predictive Analytics

Contemporary Analysis was featured in the Greater Omaha Chamber’s 2012 issue of Omaha: Extraordinary Opportunities magazine. The articles contained in the magazine are written to highlight the strengths and growing opportunities in the Omaha area. The publication shows businesses that are deeply invested in the future of Omaha. Contemporary Analysis is a big player in the up-and-coming predictive analytics market. (more…)

The Predictive Analytics Revolution – Are you sitting on the sidelines?

Predictive analytics (or Big Data) is here to stay. You may not understand it. You may not believe that it really works. But the reality is this: your competitors (and it may be just one or two of them) are using predictive analytics to chew up market space as you remain on the sidelines.
Don’t believe me? (more…)

5 ways to improve your customer experience

To CAN, servicing smart means helping create a smart customer experience. Its not just us though. More and more companies are realizing customers value a great customer experience and that they are no longer making decisions based solely on “is it cheap?”.

To succeed in this new world, companies have to do things to make their company stand out. They have to make their company the one that customers want to do business with again and again. A good place to get started improving your customer experience is creating a set of standards for your customer service.

What does it take to have a “great customer experience”?

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The Best Ways to Secure Your Personal Data

A few weeks ago the entire tech world was up in arms over an unfortunate breach of digital security for Wired blogger Mat Honan.
An explanation directly from Honan himself: “In the space of one hour, my entire digital life was destroyed. First my Google account was taken over, then deleted. Next my Twitter account was compromised, and used as a platform to broadcast racist and homophobic messages. And worst of all, my AppleID account was broken into, and my hackers used it to remotely erase all of the data on my iPhone, iPad, and MacBook.”
This and the recent hacking of Yahoo passwords got me thinking about how many have brought old-school security techniques to a brand new tech party where the scope and magnitude of our computing habits have a much tighter link to our real lives.  So I did some research about the best ways to secure your personal data.  It is also very pertinent to the work we do at Contemporary Analysis.
There’s little you can do about a service you use getting compromised, but there are things you can do to minimize the risk of people taking over your accounts or stealing your personal data if it does happen. (more…)

Examples of How to Improve Your Customer Experience

What do you do with customers once you get them?  Many times customers are only contacted again at a yearly review or if they have had a problem.  This passive customer experience doesn’t help you improve sales.  Your customers end up with a relationship with a customer service representative instead of you, their salesperson.  Why is that?  Why do we let customers that took blood, sweat, and tears to find and sell, be pushed to the back of our subconscious, never to reemerge? There needs to be a different way. Sales people need to inject themselves into the customer experience.
Predictive analytics allows you to use your data to find hidden patterns inside your customer experience cycle.  Using these patterns you can work smart to reengage current clients at the right time with the right products/services.  This will allow you to close more sales, more profitable sales, and even keep them from going to a competitor. (more…)

Customer Experience Metrics

How can you measure the effectiveness of your customer experience? What impact does it have on profitability, loyalty and purchasing activity?  Companies are increasing relying on their customer experience to differentiate themselves in increasingly competitive markets. In 2008, 64% of companies listed Customer Experience as having a critical role in their strategy (Forrester Research 2008).
Creating a smart customer experience can be hard enough.  Measuring your customers’s experience can be even more challenging.  Customer Experience Metrics have to go beyond traditional call center metrics to capture customer loyalty, satisfaction.  They have to measure intangible concepts, complex interactions, over large amounts of time.  Need help?
Examples of Customer Experience Metrics Include: (more…)

Rethinking Business Intelligence Software

People don’t care about business intelligence software, they care about what it can do for them.  CAN is built on this idea.  Instead of focusing on business intelligence software, we are focused on providing answers directly to our clients.  We are improving this process by launching the CAN Portal.  The Portal is how we work with our clients.  It will allow you to get better answers faster and more securely.
What are your objectives?
(more…)

How CAN Takes a Different Approach

At Contemporary Analysis (CAN), we take a completely new approach to helping companies and organizations get more out of the information they have access to. At our core is the idea that businesses should be working smart and hard.  At CAN, we are different because we always keep the human element, actionable impact, and added value at the forefront of our development process.

HUMAN ELEMENT:
We start the entire process with keeping the human element in mind. Everyone has gone through the frustrating process of being passed off from one person (if you’re lucky enough to reach a real human) to the next throughout a customer service or sales process. In most of these situations, half the time speaking with a new person is catching him or her up on things you have already said to other members of their organization.
At CAN, we understand the importance of having one contact throughout the entire process. This contact, known as a Navigator, takes the time to understand your specific business and helps you distill problems with big impact solutions. Navigators understand the majority of managers and executives don’t have the time to learn about predictive analytics. Navigators take the time and effort to understand the problem or issue from the end user’s point of view and then strategize to reverse engineer an efficient solution. It is our job to couple your expert knowledge and historical data to give you a solution with impact.
ACTIONABLE INSIGHTS:
At CAN, we understand businesses outsource services for added value. The value of using predictive analytics is only as great as the actions and changes made with the information provided. You could have a GPS system in your car, but if you never turn it on, it doesn’t do you any good. From step one in our customer process, we work on finding helpful insights into areas in which you can TAKE ACTION or MAKE CHANGE, not just look at the report and think “Hmm, that’s interesting.” If the information we provide doesn’t induce change on at least some level, we didn’t properly do our job.
EXTREME VALUE:
At CAN, the solutions we provide make sense financially. We use predictive analytics to answer questions in about 30 days. Think about that for a second. In just 30 days you could have an analytical model which, while not being perfect, will allow you to make much more informed decisions. Whether it’s having a better understanding of up-sell, cross-sell, or customer loyalty. It is important to remember, the goal of predictive analytics is to be LESS WRONG, and models continually become less wrong by using current information to test and re-test.
Compare 30 days with CAN to the alternatives – doing nothing or creating an in-house predictive analytics department. In smaller companies, the alternative to CAN is to do nothing. Smaller companies don’t have the resources to create in-house predictive analytics, but have a lot of the same issues as large companies.
The other alternative is in-house analytics. I believe in-house predictive analytics departments are something every large company should invest in. Properly managed and financed in-house departments can change organizations in ways never thought possible, in ways which only the future will show us. No longer would justifications for decisions be based on gut instinct, or worse yet, “because that’s how we’ve always done it.” This business is your passion, and nothing proves a point faster than quantitative justification. However, what if you’re not a large company?
In-house departments require management, direction, and resources. A company looking to develop the smallest possible in-house predictive analytics department will pay for the following:

  • Find and hire a highly sought after Ph.D. or Masters at a cost of 75-150k.
    • Add half the salary again for employee benefits, taxes (FIFA, FICA, etc.), office space, physical equipment, and HR resources.
  • Purchase a Tableau, SAS, or SPSS license costing 10’s of thousands of dollars for just one year

This cost of 175-250k is just the initial investment. You haven’t solved one problem yet. Taking into account the months of required training and corporate acclimation before any useful insights can be made by this new hire, it can be 12 to 18 months before you have a solution to just one of your smallest problems. 30 days and a cost of at least a zero less sounds much better to me.
Like I said before, I would encourage all large companies to take the plunge into predictive analytics. Even with well developed predictive analytics solutions there is a high possibility the department would suffer the same downfall as some IT departments, the disconnect between who designs or provides the technical knowledge and who actually uses it on a day to day basis.
At CAN, we take your expert knowledge and use your data to provide valuable insights you never thought possible. Throughout the entire process, we never lose track of the importance of the human element. Whether you’re a large company with an in-house analytics department or smaller business with no means for self analysis, we care about your business and can give you value in the form of information from which actions can be taken.

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