• Data Rapidly Takes Over the Earth
• The Science and Art of Data
• The Customer is Sooooo Right
• Listening with Apps and People
• Big Data Magic Tricks

Data Rapidly Takes Over the Earth

These days, the data is large and in charge. It grows and grows, and it can certainly give us extraordinarily valuable insights. Big data is allowing for more intelligent choices, better efficiency, stronger interaction with customers, disease prevention, and stockmarket predictive models. Some day big data analytics could replace us behind the steering wheel, and it can already trump us in the Daily Double.

Business now has an extraordinary amount of information. Data is prevalent to the extent that it is almost overwhelming. Look at it this way: the rate at which data will be created in 2020 is expected to be 44 times what it was in 2009. How do we turn all the data into meaningful insights?

The Science and Art of Data

Analytic tools are becoming more sophisticated, but skilled data scientists should open their safes and get ready to start dumping in some dough. Actually, you need more than insight; you also need the ability to explain it succinctly and engagingly. That’s why, small businesses with smart technology and human capital tend to Get data. Get insights. With the right analytics platform. Adverity (or a similar data analytics firm) help them assess various market trends and patterns.

McKinsey forecasts that in just three years, “the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”

Is your office looking for a data scientist? The Oval Office already did. Early in 2015, the Obama administration welcomed the newly appointed US Chief Data Scientist. Also this year, the University of Rochester created its own Institute for Data Science. A poll by recruitment agency Burtch Works reveals the obvious, that more people want data scientists than ever before and that they’re willing to pay big bucks to get them.

The first place that you want a data scientist to specialize is marketing, argues Brian Kardon, CMO of marketing analytics company Lattice Engines: “In marketing,” he says, “effectively using data to understand customers and predict buying behavior can make the difference between a winning customer experience and a failing one that lives forever on social channels.”

The Customer is Always Right

Okay, customers are often wrong. However, increasingly sophisticated digital environments mean that they are more empowered than ever before to find solutions that match their expectations:

• 57% of buying is individual research
• 70% of the sales funnel precedes the salesperson

It’s all about the content, and it’s critical that the content is customized (as proven repeatedly by research). Data analytics will allow you to find the most ideal prospects and customize them in the best possible ways. which is why tools similar to data driven marketing tools and digital information collection tools could be seen as vital to an e-commerce website in understanding and catering to the possible needs of their customer.

“Big data is perhaps the most important way to create a user experience that treats customers in the way that they want to be treated – like individuals,” says Distilled outreach director Adria Saracino. “[I]f you listen properly, your data will tell you vital information about your customers and clients.”

Listening with Apps and People

Clearly, you want to leverage automation with predictive apps and some DXP (Digital Experience Platform). While a software helps to filter your leads and gives you immediate intelligence, DXP can help track and analyze consumer behavior at every touchpoint. To know more about DXPs and how they can be helpful to analyse big data, one can refer to online resources. However, that data needs to be dealt by expert staffs in order to be used efficiently.

A well-trained and thoughtful data scientist can straddle the line between IT and business. They should be grounded in math, of course, so that they are aware of all elements of the analytic algorithms. Their background should help them tweak equations to fine-tune campaigns and build sales.

Data scientists live in the land of intent data, behavioral data, and fit data:

• Intent data – keywords and website tracking
• Behavioral data – content and emails users access
• Fit data – characteristics of company and credit score

By combining these three elements, you can create incredible customer profiles. Taking behavioral analytics as an example, monitoring user behavior assists companies in identifying potential challenges users may encounter when using their products. It also assists them in understanding each user journey, eliminating any guesswork, and focusing on granular user segmentation to optimize their product for growth. If you want to learn more about how to improve user experience with behavioral analytics, you can go on websites like trychameleon to gain more info.

Data scientists can also devise and interpret strong split testing for better results.

Again, according to Kardon, you need both the software and the human touch to create marketing magic. “Without technology, we would lack the clouds of data that inform outreach decisions,” he says. “Without data science, we would lack the insights that escape algorithmic automation, and the ability to translate data insights into effective decisions.”

Big Data Magic Tricks

As big data tricks become more fundamental to business success, you need to hire a guy with a cape and magic wand: a data scientist (data magician?). You also need the technology to set the stage for that individual to perform.

Our cloud stage offers major performance and reliability (true 100% HA) differences over others using mainframe-era/style centralized storage and inferior,
Ethernet-based networking technology.

By Kent Roberts