The Deciding Factor

You’ve heard the salary, you have a full understanding of what a data scientist actually does. However, at the end of the day true success and happiness is often found in doing something that you love. Understanding the qualities or characteristics of a data scientist is essential in knowing whether or not that fits your true calling.

Data Scope Analytics defines six qualities necessary of a great Data Scientist. Here is what they found, a Data Scientist is a:

1. Statistical Thinker
2. Technical Acumen
3. Multi-modal communicator
4. Curious
5. Creative
6. Gritty

Are these qualities, qualities you feel you possess? Are they qualities that you can develop further? If so, the role of data scientist may be a calling. If not, and you possess only a few or none of these skills, do not be discouraged. The use of data and analytics is becoming more and more important in Digital Marketing. While you may not be a data scientist, the more you can incorporate data and analytics into your everyday job, the more value you bring to yourself and company.

So You Wanna Be a Data Scientist?

So you’ve decided you want to become a data scientist – congrats. In my previous post I discussed the skills needed to be a data scientist, at this point obviously you believe you have what it takes. If you’re questioning whether you have those skills or it’s worth refining those skills you may want to rethink that when you see what the average salary of a Data Scientist is.

As the popularity for the position of Data Scientist increases, those who are actually Data Scientists holds steady. According to GlassDoor, the national average salary for a data scientist is $113,436! So before you write-off crunching numbers and gathering business intelligence you may want to consider that figure and you consider a job change or further developing your career!

Defining the Wizard a.k.a. a Data Scientist

Keeping up with the recent theme of “The Wizard of Oz,” in this post I have decided to analyze the “wizard” or a data scientist. Big Data, analytics, metrics, business intelligence are all buzz words we constantly hear.

LinkedIn released their top skillsets for 2017 with statistical analysis and data mining at number two on the list. There is no hiding that data scientists and the skills required are growing in importance – but do we have a full understanding of the skills actually needed to be a data scientist?

Everything You Should Know About Data Science: The Century's Hottest Career written by Laurence Bradford, helps us begin to understand this “wizard,” “man behind the curtain,” or more simply put a data scientist.

According to Bradford, “Gautam Tambay, cofounder and CEO of Springboard, believes that ‘Data is the new oil.’” There are some specific things you should know about these wizards:

1.       Early on most data scientists were only PhD’s our those who completed various higher level education courses. With the amount of data only increasing, there is a short in the supply of these data scientists. Today someone with logical thinking and a passion for analytical insights are beginning to do the job once reserved for those with PhDs.

2.       Being a data scientist isn’t strictly numbers. Niraj Sheth a data scientist at Reddit stated, "Fundamentally, it is as much about people -- the users you're building for and the coworkers you're building it with -- as it is about math and engineering. Having a hybrid background myself has definitely helped me understand which parts of data science to leverage at different times."

3.       Tambay further breaks down being a data scientist into five simple steps:

1.       "First of all, you want to learn to break down problems into its constituents. Every time you think about why something’s happening, create a hypothesis. This can apply day to day. When you’re doing anything with your friends. When you see something happening, [ask] ‘why did that happen?’

2.       "[Second], think about, ‘what data would I need to prove or disprove this hypothesis?’ Think about why this would happen, think about a hypothesis, think about what data you would need to prove or disprove the hypothesis, then go find the data and see if the data confirms your hypothesis.

3.       "[Third], think about how to bridge the gap between this simple hypothesis-driven thinking to actually running large experiments. That’s where you need to learn the statistics, that’s where you need to think about how to clean and wrangle data, because often data is messy.

4.       "[Fourth], you think about how to organize the data into analyzable form, and that’s when you need the tools, whether it’s Python programming or a language like R or some people will just even use SQL and Excel for smaller problems. But that’s when you need the tools to actually analyze and conduct your analysis.

5.       "Finally, you need tools to visualize and present your insights -- data storytelling."

If we’ve learned anything from my past posts and the movie The Wizard Of Oz, it’s that anyone can be “the man behind the curtain.” With the right kind of drive, inquisitive nature, and logical thinking anyone can be your data scientist.

Data will play a significant role in the success of companies over the next decade. This will require us to adapt – especially us as marketers. I look back to Sheth’s comment from above, as marketers we have the people skills or understanding necessary for part one, we need to develop ourselves analytically to achieve part two.

Putting people and analytics at the center of defining a data scientist is a logical fit for a marketer. While analytics and data was not the “attractive” part of marketing that got me interested in this field, I am beginning to become more interested in it as I recognize it as the future of this field. 

Defining the Curtain – 17 Predictions of Big Data

Photo: "The Wizard Of Oz" MGM

In my previous post, I reference the Forbes article, 17 Predictions About The Future Of Big Data Everyone Should Read. Here, Bernard Marr, defines 17 predictions to define the curtain and more importantly, the man behind the curtain (reference to previous blog post).

We know that big data is the culmination of all the data produced in the world, understanding how its analyzed is crucial in how we use this data as marketers. In order to gather our thoughts, we need to understand the direction (we believe) big data is taking.

Here are what I believe to be the five most important predictions:

• Data volumes will continue to grow. We’ve seen an unprecedented increase in the amount of information collected on and provided by consumers. There is no reason to believe that his data collection will slow down.

• Ways to analyze data will improve. Pretty straightforward – this includes improvements in current technology as well as new technology.

• All companies are data businesses now, according to Forrester. More companies will attempt to drive value and revenue from their data.

• Businesses using data will see $430 billion in productivity benefits over their competition not using data by 2020, according to International Institute for Analytics.

• “Fast data” and “actionable data” will replace big data, according to some experts. The argument is that big isn’t necessarily better when it comes to data, and that businesses don’t use a fraction of the data they have access too. Instead, the idea suggests companies should focus on asking the right questions and making use of the data they have — big or otherwise.

While these are only predictions, I believe these to be the most likely of all to happen. Data volumes and what we have the ability to collect is changing and growing by the minute. With every agreement we sign or click, we are allowing companies to continually collect data on us.

The final three bullet points are really the most important, with the last being my favorite. When most people think “big data” it is most often attributed to bigger companies. However companies of every size, small and large businesses have access to data. We need to begin changing the way of thinking, and realize that the data we collect and use must be fast and actionable.

Businesses of all size are driven by data, even if it’s as simple as data and analytics provided by Google. We will begin to see companies not only use this information to draw insights but also to drive revenue. It will be imperative that this information be used to further business. Data can be the exception for a business – making it exceptional or leading to its ultimate demise.

When it comes to data, follow the yellow brick road. But make sure the man behind the curtain, building insights from this data is who you really think he is. In my next post, I’ll discuss some skills your data “wizard” should have.

To read the full article and all 17 predications, click here.

“Pay no attention to the man behind the curtain!”

Photo: "The Wizard Of Oz" MGM

An ever-famous quote, “Pay no attention to the main behind the curtain!” has a nostalgic effect for most who hear or read it; it, of course from The Wonderful Wizard of Oz. But now, this quote may begin to take on new meaning as it relates to big data.

What’s big data? The Advanced Performance Institute, an organization that basically lives and breathes big data, defines big data as, “the term used to describe our ability to make sense of the ever-increasing volumes of data in the world.”

Big Data, its ability to be analyzed and its relation to privacy all seem to be on a crash-course with each other… this eminent interaction looms large in its future. So again, what is big data? Where does it go? Who is the man behind the curtain collecting it?

A recent Forbes article lays out 17 Predictions about the future of Big Data and whether there really is a wizard behind that curtain. Until then, I’ll keep you on the edge of your seat until my next post where expand on these predictions and the one’s I believe are the most key.

Can You Measure ROI of Digital Analytics?

If I may say so myself, I’ve done a pretty decent job setting the stage for this showdown of past vs. future when it comes to measuring the return on investment (ROI) of digital analytics. The former, can best be defined as investment in marketing and investment in the customer.

If you missed out on my first two posts, you can view them here, or to get a better understanding of the Harvard Business Review, case study I am referencing, click here. The HBR Case Study planted the seed, here’s my take:

At the end of the day your ROI should be measured on investment that impacts the bottom dollar – what can you do that will have the greatest impact on sales and profits. Today, this is strictly by the numbers, the future will take us to greater more grey areas in ROI.

Everything we do in our lives today is relationship-oriented. Customers no longer want to simply purchase a brand, from a store, they want to have a relationship with that entity. A sale is no longer a simple profit or “win” for a business but rather the birth of an organism – the birth of a relationship.

Businesses today are called to extreme lengths to meet the wants and needs of their customers through constant interaction and engagement. This change has caused a change in the way we measure success and investment – analytics is no longer the way it used to be.

And that’s, O.K.

The new wave of measuring ROI will be captured in investment in the customer and represented in key performance indicators (KPI), such as:

• ·         Brand Engagement
• ·         Educational Posts
• ·         User-Generated Content

Your accountant will point to your “books” as the most valuable part of your business. 

STOP THAT WAY OF THINKING. 

Businesses don’t go out of business or experience bankruptcy because of a slow year (for the most part). Businesses experience difficulties and failures because of a lack of customers. A way to keep customers coming back, is to build a relationship, foster the organism you’ve created at your first sale. Invest in your customers.

Social Media and Digital Marketing tools are a cost-effective way to keep your customers engaged in your business. Let’s face it, when they’re not in your shop, they’re a target for other businesses.

Using social media and digital marketing channels does not automatically mean that marketers working for you are off the hook. There are several analytical tools that can be used to gauge the successes of marketing campaigns. This new age of measuring ROI does not mean that standard metrics are not useful, such as:

• ·         Number of Followers/Likes/Fans
• ·         Impressions
• ·         Likes, Comments, Shares, Retweets

I’m not here to completely throw hard numbered-metrics out the window. I’m just saying, measuring ROI via investment of the customer requires a more full-bodied approach than ever before.

Trial social media platforms, see what sticks – see where true value is generated from. Successes in the digital channels and properly analyzed metrics will have you blowing by competition in terms of sales and customer satisfaction.

What’s nice about customers is - when you invest in them – they return the favor.

…and Measuring ROI

In my last post, I set the stage for a showdown… the old ways of measuring ROI strictly through numbers and the effect on bottom dollar and this so-called new-age that will turn your thinking upside down. In the Harvard Business Review previously mentioned, the idea of measuring ROI centers on investing in consumer investments, rather than concentrating on marketing investments. Blogs, Facebooks, Twitters – social media in general has taken marketing by storm. The new age of measuring this type of marketing is still developing. However, we can begin to define the calculation of ROI as in customer investments rather than marketing investments.

The future of digital marketing analytics depends entirely on this new way of measuring ROI. Popular metrics are likes, post reach, or shares but these are not the key performance indicators (KPI) that are hard to measure or lead to a positive ROI or investment in the customer. Meaningful KPIs are the concepts of brand engagement, product education, or user generated content. When a business utilizes social media to build these KPIs they are investing in the customer. Investing in the customer this way, is the business hoping to build a customer experience or customer-to-business relationship that will impact sales in the short- and long-term.

With this new idea of ROI in mind, we have some thinking to do. The question remains, what will lead to the most value for your business – investing in marketing investments or consumer investments. I’ll deliver a verdict in my final post of the week.

To Social or Not to Social, and Measuring ROI

To social, or not to social – that’s the question many business owners ask themselves. One side of the aisle says your fifteen-year old nephew can handle a Facebook or Twitter handle, the other has you spending hundreds of dollars a month. The real question, what will provide your business the most value? The harder question – how is that value measured?

In a Harvard Business Review case study, the idea of measuring the return on investment (ROI) of digital analytics is defined simply as, “turning your thinking upside down.” That’s right, not only are the traditional methods of marketing a way of the past, but ways of measuring ROI through analytics and key performance indicators (KPI) are changing.

This new age and the future of digital marketing analytics say good bye to the cold hard numbers – for better or worse. While tracking numbers and being able to allocate marketing-related expenses directly to the bottom line is monumentally important at the end of the day, it is imperative that, that measurement is not the “live or die” factor in measuring your ROI or success when it comes to social media marketing or general digital marketing analytics.

Interest peaked? Let’s see if your fifteen-year old nephew can accomplish that in 200 words or less. Stay tuned for my next post, we’ll go more in-depth on this new age of digital marketing analytics. If numbers are the way of the past – you’ll need to know what the future holds.