Monthly Archives: November, 2016

Black Friday & Cyber Monday

November 24th, 2016 Posted by Analytics 0 thoughts on “Black Friday & Cyber Monday”

While retailers lick their chops over the hordes they will attract on Black Friday, there’s a small PSA I must make.

Scrap Black Friday. No, I mean it. Burn it like that first turkey you made 20 years ago that your family will never let you live down. Just throw it all away, like what you want to do with the dull green bean casserole that your cousin insisted on bringing this year, just like he has every previous year. Heck, if I were you I would even do away with cyber Monday and treat it like the cranberry jelly that really adds nothing to the turkey-and-carbs fest, if we’re being honest.

What I mean by all this is that it doesn’t make sense to pick out one day each year to draw in customers with huge deals. If you have the right data analytics program to monitor what customers are doing every time they visit your website, you can create a Black Friday experience all year long. You can increase your conversion rates both online and in-stores, 24 hours a day, 365 days a year.

You see, a customer 360 data app allows companies to tailor how their website responds to each incoming user, based on their prior behavior on the website. That gives you the ability to influence the outcome of each visit. The algorithmic nature of today’s data apps is very powerful and it will automatically recommend the next best action that needs to be taken. You won’t even need to create gigantic sales to improve your retention rate and overall sales results.

So for this year, scrap Black Friday. And instead of stuffing your data into static analytics programs, start using dynamic behavioral analytics tools to make the most of each customer’s visit.

If you would like to find out how you can make every day of the year a Black Friday kind of day, feel free to reach out to me.

How Syntasa Came To Be

November 14th, 2016 Posted by Analytics 0 thoughts on “How Syntasa Came To Be”

Syntasa’s story began on September 11, 2001, when I was working in New York as an executive at American Express. I was only a block away from the World Trade Center when the towers came crashing down. I had witnessed the tragedy of that fateful day unfold in front of my own eyes and it shook me deeply. At the same time, it also motivated me to work in the defense sector in order to help improve the country’s defenses and prevent anything like this from ever happening again.

In 2013, I moved from New York to Washington D.C. to found ABSc, a company that would focus on providing security services to the government. I landed a project with a federal agency to help their cyber infrastructure. I started out recruiting a couple of smart, patriotic minds who had already built a name for themselves within the federal government for their work with advanced analytics. We soon grew to a staff of several hundred people. Due to budget cuts and drawing down from the war starting in 2009, our company saw ups and downs due to a decline in demand. But still, our management team was strong enough to quickly build the company back up again.

Some of our staff has been around since the company was run out of a small closet of an office. Now, we are a well-known partner of the federal agencies.

Still, my entrepreneurial bug was not going away. So, I started Syntasa in 2012, with the hopes of building a product to perform Predictive Behavioral Analytics for large commercial enterprises. This kind of software provides enterprises with insights into their customers’ behaviors, to help improve business outcomes. With behaviors analyzed in real-time, websites can be dynamic in nature so as to change content according to how the customer is interacting with a website, thereby improving the customer experience.

Syntasa’s Predictive Behavioral Analytics is at the forefront of the technological and data revolution, adapting the very latest in machine learning technology to help enterprises identify actions and outcomes. In some cases the software can be used to identify bad guys who could potentially harm our nation. There are plenty of things in the world that I’d like to work hard to solve for, in order to make the world a better place. I also realize that there are intelligent minds already at work solving these things. I just feel fortunate that I was given an opportunity to serve our nation in a small way.

data analytics

The Future of Data Analytics Lies in Predictive Behavioral Analytics

November 10th, 2016 Posted by Analytics 0 thoughts on “The Future of Data Analytics Lies in Predictive Behavioral Analytics”

We’ve come a long way since the days of horse-drawn carriages, haven’t we? Not only do we have fast, powerful cars at our disposal, we can also see glimpses of a time in the not-so-distant future when everyone will be riding in self-driving automobiles.

You can say the same for data analytics. Computers and digital data have done much to revolutionize the processing of information, but artificial intelligence is expected to change the rules of the game in the decades to come.

The cutting edge data analytics tools of today don’t just process static data. Instead, they analyze data in-motion, based on a dynamic model that evolves with each new addition of data, in order to coordinate an immediate and appropriate response. This type of program – what we call Predictive Behavioral Analytics (or PBA) is already being used by businesses in a wide range of industries. Think about websites like Amazon, and how they tailor results and recommendations to a customer’s online behavior.

Predictive Behavioral Analytics is also an important weapon in the arsenal of several government entities seeking to improve intelligence production capabilities and strengthen their cybersecurity. It provides the analytics capability to identify suspicious users based on their immediate behavior on the network, and consequently shut them out instantly.

Just like self-driving cars, Predictive Behavioral Analytics offers traditional data analytics functions with the addition of cutting-edge technologies. The program can make recommendations based on the data accumulated over time, in areas such as internal management, customer-facing applications, and effective information sharing. That means you get the bets of both worlds: traditional data processing and an AI program working for you around the clock.

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