Data Delirium: Why and How You Should Embrace Big Data

Business.com / Technology / Last Modified: February 22, 2017

Big data is here to stay and we need to get used to. Many companies are now using it that they gain an advantage over those who don't.

Big data, big data, big data.

Yes, we are all sick of hearing these words, but let’s stop kidding ourselves. It’s not just the latest buzz phrase, it’s here to stay. Good news is that it’s not all that bad.

In a recent article by Ari Amster on Business.com, it was pointed out that there many misconceptions about big data and that involving yourself in its collection and analyzation is not all that difficult.

“Misinformation tends to run rampant, especially when it comes to advanced technologies,” wrote Amster. “While many big data myths have been addressed, a number seem to be stubbornly hanging onto the public consciousness, refusing to let go and remaining a prevalent fixture of the big data landscape.”

In case you have not already seen the trend, let me point out the Internet is exploding about articles on big data. Everyone is telling us to stop ignoring it and that we need to use it to our benefit. It is being jammed down our throats, but I whole heartedly agree with this sentiment.

Big data is here to stay and we need to get used to it. In fact, so many companies are now using it that they gain an advantage over those who don’t.

How and What to Collect

Have you seen your credit score lately? If you have, then chances are you are familiar with FICO. Founded in 1956, FICO is a software company that provides analytic solutions for companies. One of its most notable products is the FICO Score which is a measure of a person’s credit worthiness.

FICO has been analyzing data longer than anyone else I know. It has mastered data to the point that an entire nation uses its analysis to decide if you can buy a home, purchase a car, or even obtain a credit card.

Andy Flint is the Senior Director of product management at FICO. According to Flint, collecting the information to understand your customer’s purchase decisions is one place to start. “Companies that begin with the decision in mind will find it easier to identify the right analytics, easier to pull together the Big Data they need, and easier to find value in Big Data.”

So, when you start to collect data, have the end result in mind as opposed to collecting everything you can.

Related Article:Hadoop, SQL and ACID, Oh My: Big Data Demystified

Even if you are a small business and only collecting a snippet of information, you can still benefit from big data. “Small businesses can develop successful customer-centric strategies and build more profitable customer relationships through analytics, predictive modeling, and multi-channel communications,” says Flint.

“One way to do this is through cloud based solutions. Cloud solutions enable businesses to quickly get started with analytic solutions. They are also affordable, and they are easy to try and easy to scale as a business grows.”

Collecting data can be done manually or with the help of software like Flint points out. Manual collection of data can be as simple as asking for an email address with a purchase. You can cross reference purchases tied to an email address and know exactly how to target that customer.

Purchasing data is also an option since others are in the business of collecting data you already need. As an example, I used big data when putting together a business plan years ago. I was able to project sales based on the data collected. I found a city with a similar business, similar population, income levels, weather, and everything else I could us to match the city I planned to open the business. I was able to compare apples for apples which turned out to be an asset when presenting the plan.

Flint also points out that you need to leverage the data you have. After all, what good is collecting it if you don’t use it? “There are many ways businesses can leverage big data. They can precisely target offers and programs to customers. They can use Big Data analytics to combat fraud and to enhance security. And lenders use Big Data to manage risk in their lending portfolios.”

In the end, my recommendation is to only collect what you need. And yes, it is as easy as it sounds. If you want to know how much money customers are spending on your website, collect sales figures. Want to know how far people traveled to purchase something from your brick and mortar? Ask for a ZIP code. That simple.

For some reason, people think they need to collect everything in order to use big data. Not necessarily so. You simply need to be able to analyze and use the data that you do collect.

Analyzing and Using Data

As Amster pointed out in the article, you don’t need the perfect data scientist to help you decipher the information you collect. In fact, some data is so simple that little analyzation is needed.

Here is an example:

Let’s say you want to know what percentage of people spend more than $200 at your e-store. Simply get the data from your point-of-sale. Search for how many people spent $200+ compared to how many people made a purchase in total. Very simple.

Some data, however, is a bit more complicated and takes a little more than a simple search and a calculator.

Related Article:Buying In the Cloud: How Cloud Technology is Revolutionizing the Retail Industry

Data used to be very difficult to analyze. Advances in technology allowed us to collect data, but it caused a funnel as there was no easy way to use it. Too many people with the data were inexperienced and there is always a shortage of experts who can analyze it.

Well, with every problem comes a solution and the age of data analyzation was born.

Software companies sprung up overnight, creating a solution to the problem of sorting through massive data. The shift began from manually analyzing data (using spreadsheets and off the shelf software like FileMakerPro) to using customizable software made specifically for the task. In addition to premium solutions offered by these new companies, you could even find free analysis and visualization tools to help with easy data tasks.

According to Jakob Rehermann from datapine, analyzing data does not have to be as difficult as it used to be: “Generally, we see a strong trend towards self-service interfaces that facilitate the analytical process and empower non-technical users to explore their information and visualize it professionally.”

Visualization has now been added into analyzation, allowing novices to collect, analyze and understand the data they have. Dashboarding now allows you to take big data and analyze it by putting it into graphs and charts that break things down visually. Beats the heck out of looking at spreadsheets, huh?

Dashboarding and various other methods of data analyzation have put big data within reach of most business owners. With a little research, you can find the right platform to not only collect, but analyze and store data.

When it comes to applying what you learn from big data, there are many avenues to take. Of course, you really need to understand what you want to accomplish with the data you collect before you even begin to analyze. No sense in putting information into a chart if that is not the information you want to use.

Let’s look at casino marketing as an example of how to apply big data. A casino will collect data on its patrons with the use of a loyalty card. In additional to your personal information, casinos collect such things as the amount of money you spend, times and dates you visit the location, and even your favorite slot machines.

So, how do they use this data? Let’s take a look.

If the marketing department wants to target people who have not been to the casino in a while, it can analyze the data it has to determine people who have not played at the casino in “X” amount of months. It can then target that group for people who spend an average of $200 each visit. Then it drops a mail offer such as “$100 in free play” to come to the casino on a specific date.

From the example above, the casino used a small amount of data for its marketing efforts. While casinos are large operations, even small businesses can use the data they collect for marketing strategies.  

Big Data and Privacy Concerns

There is always a privacy concern when it comes to collecting data. Many people don’t even know that data they provide to companies is being stored, analyzed, and used in the manner it is.

“Data collection is done without real consumer awareness every day,” Says Boston-based health care attorney and consultant David Harlow. “We all download and install smartphone apps and use websites without reading the privacy polices and terms and conditions.”

Getting data from us is pretty easy. As pointed out by Harlow, many of us simply give the information without knowing it. But what are the pitfalls of collecting and storing this information?

You guessed it…data breaches.

Data breaches can be costly. No one knows this better than Target and the 40 million customers whose data wound up stolen in 2013. Costly? Oh yeah. Target ended up paying $67 million to Visa and another $39 million to Master Card over the breach. This figure does not include any loss to customers whose data was used for fraudulent activity. Not to mention a significant drop in profits suffered by Target in the fallout of the ordeal.

Consumer sentiment regarding breaches is changing despite the harm that it can cause. People are no longer as upset as they used to be according to an April 2016 study by the RAND Corporation. Only 11 percent of respondents stated that they will stop doing business with a company due to a data breach.

From my experience, that 11 percent is probably less as many people are simply upset at the time they gave their response, but will change their minds when it comes to doing business with that company in the future.

So who is going to protect your privacy when it comes to data collection and storage? Currently, we must rely on the companies who collect the date to perform its own oversight. Government involvement is slow as it is playing catch up with the technology just like the rest of us.

Government agencies are trying to allow the public and those collecting data to police each other. Harlow adds, “Many of the regulatory agencies profess to prefer education and training to enforcement (fines and other sanctions); while these approaches have certainly increased awareness and compliance over time, there is still a long way to go.”

This type of governance is working so far. According to the RAND Study, “77 percent of respondents were highly satisfied with the company’s post-breach response.” This tells me that consumers expect that breaches will happen, but they trust companies will respond quickly to keep the dam from overflowing.

This type of governance is not the ultimate goal. According to the author of RAND Study, “data breach notification laws empower consumers to take quick action to reduce risk and create incentives for companies to improve data security...our research shows the importance of legislation that requires companies to notify individuals when a breach occurs."

So even though we are doing a good job of policing ourselves, the author is calling for oversight laws almost as a safety net for when we don’t.  

For now, the best type of protection is knowing what information you are giving (and deciding on whether or not to give it) along with companies implementing security measures to prevent data leaks from taking place. It’s about the best that can be done until regulators can catch up.

Related Article:Go Big or Go Home: How to Utilize Big Data for Human Resources

Final Thoughts on Big Data

Don’t be scared of big data. In fact, “big” shouldn’t even be used when discussing the topic. Professor Ari Lightman from the Heinz College at Carnegie Mellon University explained it best in a recent interview I had with him on my podcast. 

“It’s just a marketing term that someone coined because they could not understand the cultural fascination going on with data right now,” Lightman explains. “Our ability to digitize, store, and share data has been exacerbated. When people talk about “big” data, what they really mean is “messy” data.”

Remember that you don’t need to have a “mess” of data in order to be effective at using it. Lightman adds that more than 99% of the data people collect is useless. You need to focus on the small amount of data you do need in order to be effective, not collect as much as you possibly can.   

Finally, don’t ignore it. Big data is here and you will get left behind without it. Your competition is using it, so why shouldn’t you?

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