Big Data: What It Is and How to Analyze It

What really is big data? Big data encompasses extremely large datasets that can be analyzed to reveal more in-depth insights, patterns, trends and even help predict future outcomes. But what actually makes up these “extremely large datasets” can be much more exhaustive, and understanding them can significantly improve our overall knowledge of big data and how to use it.

What really is big data? Big data encompasses extremely large datasets that can be analyzed to reveal more in-depth insights, patterns, trends and even help predict future outcomes. But what actually makes up these “extremely large datasets” can be much more exhaustive, and understanding them can significantly improve our overall knowledge of big data and how to use it.

Big data is just data: The following types of big data can be used to define any data in today’s world. But the goal of understanding the different types of data is to help determine how they might be used together to provide the answers to the questions marketers are asking.

3 Types of Big Data

First and foremost, big data can be defined based on its structure. The structure of data depends on how organizable it is. In other words, whether it can be formatted into tables of rows and columns. There are three types of big data when defining it by the structure:

  1. Structured: Data that is structured is often already stored in a database or other data management platform, and it can be easily accessed and processed to provide an ordered output.
  2. Unstructured: Usually larger datasets — the majority of big data is unstructured, meaning it can’t easily be organized or classified.
  3. Semi-Structured: As the name implies, semi-structured data isn’t inherently organized at the start, but as it is analyzed or digested it can begin to take on a more structured form.

Both structured and unstructured data can be either human-generated or machine-generated. Human-generated, structured data can be contact information or website form details directly collected from an individual. Human-generated unstructured data can be any form of website activity and social data such as video, audio, or social posts shared by a person.

On the other hand, examples of machine-generated, structured data include GPS tracking, inventory tracking, or transaction data. Unstructured forms of machine-generated data include information gathered through satellite such as images or weather sensory information.

Each of these types of data can be analyzed in many different ways. However, there are certain types of analysis that will serve their own purpose depending on the objectives at hand.

4 Types of Analysis

There are many reasons to look to big data for insights. Whether it’s combining big data and survey data for detailed audience intelligence or combing through it to predict purchase data, they all fit into four types of analysis:

  1. Prescriptive Analysis: Data analysis that provides answers to what actions should be taken.
  2. Predictive Analysis: An analysis of data that can be used to predict what situation or number of situations may results.
  3. Diagnostic Analysis: Data analysis that provides insight into what happened in the past and why.
  4. Descriptive Analysis: Data analysis that can be real-time or leveraged to see what is currently happening.

Mapping your analytics and marketing strategy to the type of big data needed and the type of analysis can help understand what tools and solutions may be best to bring it all together. Specifically, the type of data and analysis will lead you to the type of big data analytics required.

Jobs for Everyone — Riding the Data Train to Washington

Positions in digital media and data analysis abound, and we’re still not training them fast enough to meet the demand — domestically. That means support for all aspects of data curricula at colleges and universities, and perhaps secondary education too, as well as retraining programs for displaced workers — something that did not receive nearly enough attention in the general election.

President-elect Donald J. Trump didn’t take long to take credit for an arrangement to keep a Carrier Corporation plant in the U.S. — even if there was some question over just how many jobs were in the balance.

Hanging onto good-paying manufacturing jobs certainly is a well-intended public policy goal, as long as we understand the incurred corporate welfare cost that was just shifted to the taxpayer. Still, a saved private-sector job is better than a lost private-sector job. However, it’s only a bridge or a bandage.

There are plenty of jobs — well paid and in America — that are dear to fill. Perhaps public policy, public and private education, research and development, and maybe even some philanthropy might do a better job preparing (all of) America for the 21st Century. We love STEM majors, but also critical thinking from liberal arts that give strategy to data analysis. AdTech and advertising are booming — we all need better and faster algorithms to help sell things efficiently, and data-informed creative skills to create more engaging and relevant content.

Let’s face it. America needs to re-orient itself for the “Data Train.”marketing dataPositions in digital media and data analysis abound, and we’re still not training them fast enough to meet the demand — domestically. That means support for all aspects of data curricula at colleges and universities, and perhaps secondary education too, as well as retraining programs for displaced workers — something that did not receive nearly enough attention in the general election.

Let the private sector do its work and let innovation grow the marketplace for jobs. Perhaps government can best help by researching and reporting what skills and training are desperately needed. This is not a call for central government planning, but if we can fund corporate incentives to “stay home,” we can certainly fund training and retraining programs for an Information Economy, based on the commercial availability and responsible use of data, that is providing financial well-being for millions of households, with millions more to come.

Hey, I’m all for “shovel-ready” jobs to rebuild American infrastructure — that well could be a bipartisan love affair that helps bolster global standing for “U.S. Open for Business.” But, also, in that same refrain, let’s demand a “jobs” plan that puts an emphasis on education and retraining for the Information Economy. The U.S. leads in this category — are we going to squander it?

Happy Holidays, and as you make your end-of-year giving, please consider our own livelihoods and future talent development in our field. Consider sponsoring a student and donate to Marketing EDGE. Philanthropy, yes, and an investment in a data-driven marketing career, one student at a time.

How Can You Get More Out of Your Direct Mail List?

Everyone knows nowadays that the more information you have on your customers/prospects, the better you can tailor your message. Well, in many cases companies do not have that much information about people. So, what can you do to gather more information?

Everyone knows nowadays that the more information you have on your customers/prospects, the better you can tailor your message. Well, in many cases companies do not have that much information about people. So, what can you do to gather more information? Well, you could ask them to fill out a survey and offer a reward if they do, but what if you could gather information without having to take up someone’s time? There is a way.

Data List Enhancement:
List Profiling helps you model your ideal customers so you optimize campaigns and find prospects with similar characteristics. Data analysis and list segmentation will provide you with valuable insights into consumer behaviors, allowing you to tailor your message to match their needs and interests. This will increase the chances they act on your offer. Here is what you can expect:

  1. Profile the unique characteristics of your best and most profitable customers to find more just like them. Learn their likes, dislikes, education level and so much more.
  2. Target your selling messages to the right audience at the right time. This will allow you to spend less.
  3. Increase your marketing penetration by opening new channels to reach your customers and prospects using the methods they prefer. This is especially important today with so many channel choices. Is direct mail in conjunction with mobile the right choice? Find out.
  4. Boost response rates through more specific, personalized offers (as opposed to generic, one-size-fits-all promotions). When you send an offer that is specific to the person, your response rate can’t help but go up.
  5. Build loyalty programs that increase lifetime value. When you can provide relevant offers to people in a timely manner, you gain respect and loyalty.
  6. Improve your database marketing with more profitable prospecting, through modeling and forecasting. Finding the correct prospects quickly will allow you to move forward with your marketing campaigns and get the responses coming in.
  7. Dramatically improve your ROI, the more responses you get directly effects your return on investment. Since these are better qualified leads, you should also make more money per lead.
  8. Improve multimedia marketing by applying profiles to hit the targets across all media. This allows you to create multiple channel campaigns while still targeting them where they want to see the messages.

Finding well qualified prospects is very difficult. With list profiling, you can pick people who are just like your best customers. It makes the prospecting effort so much easier. For the most part, such profiling is limited to the United States; so if the majority of your customers are foreign, this is not going to work for you. Knowing who your customers are and what prospects you should target gives you a big advantage. You can spend less money on your marketing because you can target it better, and at the same time make more money because you are sending to the right people.

Think of how you can harness the additional information you will gain with list profiling. This will allow you to create more detailed offers to the correct people and send out multiple versions as one campaign. Remember that your list is the first big opportunity in direct mail. A bad list will yield a bad result, no matter how great your design and offer are. A great list has the potential to yield a great result when combined with good design and a good offer. Consult with your direct mail marketing provider to help you enhance your list today!