How to Be a Good Data Scientist

I guess no one wants to be a plain “Analyst” anymore; now “Data Scientist” is the title of the day. Then again, I never thought that there was anything wrong with titles like “Secretary,” “Stewardess” or “Janitor,” either. But somehow, someone decided “Administrative Assistant” should replace “Secretary” completely, and that someone was very successful in that endeavor. So much so that, people actually get offended when they are called “Secretaries.” The same goes for “Flight Attendants.” If you want an extra bag of peanuts or the whole can of soda with ice on the side, do not dare to call any service personnel by the outdated title. The verdict is still out for the title “Janitor,” as it could be replaced by “Custodial Engineer,” “Sanitary Engineer,” “Maintenance Technician,” or anything that gives an impression that the job requirement includes a degree in engineering. No matter. When the inflation-adjusted income of salaried workers is decreasing, I guess the number of words in the job title should go up instead. Something’s got to give, right?

I guess no one wants to be a plain “Analyst” anymore; now “Data Scientist” is the title of the day. Then again, I never thought that there was anything wrong with titles like “Secretary,” “Stewardess” or “Janitor,” either. But somehow, someone decided “Administrative Assistant” should replace “Secretary” completely, and that someone was very successful in that endeavor. So much so that, people actually get offended when they are called “Secretaries.” The same goes for “Flight Attendants.” If you want an extra bag of peanuts or the whole can of soda with ice on the side, do not dare to call any service personnel by the outdated title. The verdict is still out for the title “Janitor,” as it could be replaced by “Custodial Engineer,” “Sanitary Engineer,” “Maintenance Technician,” or anything that gives an impression that the job requirement includes a degree in engineering. No matter. When the inflation-adjusted income of salaried workers is decreasing, I guess the number of words in the job title should go up instead. Something’s got to give, right?

Please do not ask me to be politically correct here. As an openly Asian person in America, I am not even sure why I should be offended when someone addresses me as an “Oriental.” Someone explained it to me a long time ago. The word is reserved for “things,” not for people. OK, then. I will be offended when someone knowingly addresses me as an Oriental, now that the memo has been out for a while. So, do me this favor and do not call me an Oriental (at least in front of my face), and I promise that I will not call anyone an “Occidental” in return.

In any case, anyone who touches data for living now wants to be called a Data Scientist. Well, the title is longer than one word, and that is a good start. Did anyone get a raise along with that title inflation? I highly doubt it. But I’ve noticed the qualifications got much longer and more complicated.

I have seen some job requirements for data scientists that call for “all” of the following qualifications:

  • A master’s degree in statistics or mathematics; able to build statistical models proficiently using R or SAS
  • Strong analytical and storytelling skills
  • Hands-on knowledge in technologies such as Hadoop, Java, Python, C++, NoSQL, etc., being able to manipulate the data any which way, independently
  • Deep knowledge in ETL (extract, transform and load) to handle data from all sources
  • Proven experience in data modeling and database design
  • Data visualization skills using whatever tools that are considered to be cool this month
  • Deep business/industry/domain knowledge
  • Superb written and verbal communication skills, being able to explain complex technical concepts in plain English
  • Etc. etc…

I actually cut this list short, as it is already becoming ridiculous. I just want to see the face of a recruiter who got the order to find super-duper candidates based on this list—at the same salary level as a Senior Statistician (another fine title). Heck, while we’re at it, why don’t we add that the candidate must look like Brad Pitt and be able to tap-dance, too? The long and the short of it is maybe some executive wanted to hire just “1” data scientist with all these skillsets, hoping to God that this mad scientist will be able to make sense out of mounds of unstructured and unorganized data all on her own, and provide business answers without even knowing what the question was in the first place.

Over the years, I have worked with many statisticians, analysts and programmers (notice that they are all one-word titles), dealing with large, small, clean, dirty and, at times, really dirty data (hence the title of this series, “Big Data, Small Data, Clean Data, Messy Data”). And navigating through all those data has always been a team effort.

Yes, there are some exceptional musicians who can write music and lyrics, sing really well, play all instruments, program sequencers, record, mix, produce and sell music—all on their own. But if you insist that only such geniuses can produce music, there won’t be much to listen to in this world. Even Stevie Wonder, who can write and sing, and play keyboards, drums and harmonicas, had close to 100 names on the album credits in his heyday. Yes, the digital revolution changed the music scene as much as the data industry in terms of team sizes, but both aren’t and shouldn’t be one-man shows.

So, if being a “Data Scientist” means being a super businessman/analyst/statistician who can program, build models, write, present and sell, we should all just give up searching for one in the near future within your budget. Literally, we may be able to find a few qualified candidates in the job market on a national level. Too bad that every industry report says we need tens of thousands of them, right now.

Conversely, if it is just a bloated new title for good old data analysts with some knowledge in statistical applications and the ability to understand business needs—yeah, sure. Why not? I know plenty of those people, and we can groom more of them. And I don’t even mind giving them new long-winded titles that are suitable for the modern business world and peer groups.

I have been in the data business for a long time. And even before the datasets became really large, I have always maintained the following division of labor when dealing with complex data projects involving advanced analytics:

  • Business Analysts
  • Programmers/Developers
  • Statistical Analysts

The reason is very simple: It is extremely difficult to be a master-level expert in just one of these areas. Out of hundreds of statisticians who I’ve worked with, I can count only a handful of people who even “tried” to venture into the business side. Of those, even fewer successfully transformed themselves into businesspeople, and they are now business owners of consulting practices or in positions with “Chief” in their titles (Chief Data Officer or Chief Analytics Officer being the title du jour).

On the other side of the spectrum, less than a 10th of decent statisticians are also good at coding to manipulate complex data. But even they are mostly not good enough to be completely independent from professional programmers or developers. The reality is, most statisticians are not very good at setting up workable samples out of really messy data. Simply put, handling data and developing analytical frameworks or models call for different mindsets on a professional level.

The Business Analysts, I think, are the closest to the modern-day Data Scientists; albeit that the ones in the past were less so technicians, due to available toolsets back then. Nevertheless, granted that it is much easier to teach business aspects to statisticians or developers than to convert businesspeople or marketers into coders (no offense, but true), many of these “in-between” people—between the marketing world and technology world, for example—are rooted in the technology world (myself included) or at least have a deep understanding of it.

At times labeled as Research Analysts, they are the folks who would:

  • Understand the business requirements and issues at hand
  • Prescribe suitable solutions
  • Develop tangible analytical projects
  • Perform data audits
  • Procure data from various sources
  • Translate business requirements into technical specifications
  • Oversee the progress as project managers
  • Create reports and visual presentations
  • Interpret the results and create “stories”
  • And present the findings and recommended next steps to decision-makers

Sounds complex? You bet it is. And I didn’t even list all the job functions here. And to do this job effectively, these Business/Research Analysts (or Data Scientists) must understand the technical limitations of all related areas, including database, statistics, and general analytics, as well as industry verticals, uniqueness of business models and campaign/transaction channels. But they do not have to be full-blown statisticians or coders; they just have to know what they want and how to ask for it clearly. If they know how to code as well, great. All the more power to them. But that would be like a cherry on top, as the business mindset should be in front of everything.

So, now that the data are bigger and more complex than ever in human history, are we about to combine all aspects of data and analytics business and find people who are good at absolutely everything? Yes, various toolsets made some aspects of analysts’ lives easier and simpler, but not enough to get rid of the partitions between positions completely. Some third basemen may be able to pitch, too. But they wouldn’t go on the mound as starting pitchers—not on a professional level. And yes, analysts who advance up through the corporate and socioeconomic ladder are the ones who successfully crossed the boundaries. But we shouldn’t wait for the ones who are masters of everything. Like I said, even Stevie Wonder needs great sound engineers.

Then, what would be a good path to find Data Scientists in the existing pool of talent? I have been using the following four evaluation criteria to identify individuals with upward mobility in the technology world for a long time. Like I said, it is a lot simpler and easier to teach business aspects to people with technical backgrounds than the other way around.

So let’s start with the techies. These are the qualities we need to look for:

1. Skills: When it comes to the technical aspect of it, the skillset is the most important criterion. Generally a person has it, or doesn’t have it. If we are talking about a developer, how good is he? Can he develop a database without wasting time? A good coder is not just a little faster than mediocre ones; he can be 10 to 20 times faster. I am talking about the ones who don’t have to look through some manual or the Internet every five minutes, but the ones who just know all the shortcuts and options. The same goes for statistical analysts. How well is she versed in all the statistical techniques? Or is she a one-trick pony? How is her track record? Are her models performing in the market for a prolonged time? The thing about statistical work is that time is the ultimate test; we eventually get to find out how well the prediction holds up in the real world.

2. Attitude: This is a very important aspect, as many techies are locked up in their own little world. Many are socially awkward, like characters in Dilbert or “Big Bang Theory,” and most much prefer to deal with the machines (where things are clean-cut binary) than people (well, humans can be really annoying). Some do not work well with others and do not know how to compromise at all, as they do not know how to look at the world from a different perspective. And there are a lot of lazy ones. Yes, lazy programmers are the ones who are more motivated to automate processes (primarily to support their laissez faire lifestyle), but the ones who blow the deadlines all the time are just too much trouble for the team. In short, a genius with a really bad attitude won’t be able to move to the business or the management side, regardless of the IQ score.

3. Communication: Many technical folks are not good at written or verbal communications. I am not talking about just the ones who are foreign-born (like me), even though most technically oriented departments are full of them. The issue is many technical people (yes, even the ones who were born and raised in the U.S., speaking English) do not communicate with the rest of the world very well. Many can’t explain anything without using technical jargon, nor can they summarize messages to decision-makers. Businesspeople don’t need to hear the life story about how complex the project was or how messy the data sets were. Conversely, many techies do not understand marketers or businesspeople who speak plain English. Some fail to grasp the concept that human beings are not robots, and most mortals often fail to communicate every sentence as a logical expression. When a marketer says “Omit customers in New York and New Jersey from the next campaign,” the coder on the receiving end shouldn’t take that as a proper Boolean logic. Yes, obviously a state cannot be New York “and” New Jersey at the same time. But most humans don’t (or can’t) distinguish such differences. Seriously, I’ve seen some developers who refuse to work with people whose command of logical expressions aren’t at the level of Mr. Spock. That’s the primary reason we need business analysts or project managers who work as translators between these two worlds. And obviously, the translators should be able to speak both languages fluently.

4. Business Understanding: Granted, the candidates in question are qualified in terms of criteria one through three. Their eagerness to understand the ultimate business goals behind analytical projects would truly set them apart from the rest on the path to become a data scientist. As I mentioned previously, many technically oriented people do not really care much about the business side of the deal, or even have slight curiosity about it. What is the business model of the company for which they are working? How do they make money? What are the major business concerns? What are the long- and short-term business goals of their clients? Why do they lose sleep at night? Before complaining about incomplete data, why are the databases so messy? How are the data being collected? What does all this data mean for their bottom line? Can you bring up the “So what?” question after a great scientific finding? And ultimately, how will we make our clients look good in front of “their” bosses? When we deal with technical issues, we often find ourselves at a crossroad. Picking the right path (or a path with the least amount of downsides) is not just an IT decision, but more of a business decision. The person who has a more holistic view of the world, without a doubt, would make a better decision—even for a minor difference in a small feature, in terms of programming. Unfortunately, it is very difficult to find such IT people who have a balanced view.

And that is the punchline. We want data scientists who have the right balance of business and technical acumen—not just jacks of all trades who can do all the IT and analytical work all by themselves. Just like business strategy isn’t solely set by a data strategist, data projects aren’t done by one super techie. What we need are business analysts or data scientists who truly “get” the business goals and who will be able to translate them into functional technical specifications, with an understanding of all the limitations of each technology piece that is to be employed—which is quite different from being able to do it all.

If the career path for a data scientist ultimately leads to Chief Data Officer or Chief Analytics Officer, it is important for the candidates to understand that such “chief” titles are all about the business, not the IT. As soon as a CDO, CAO or CTO start representing technology before business, that organization is doomed. They should be executives who understand the technology and employ it to increase profit and efficiency for the whole company. Movie directors don’t necessarily write scripts, hold the cameras, develop special effects or act out scenes. But they understand all aspects of the movie-making process and put all the resources together to create films that they envision. As soon as a director falls too deep into just one aspect, such as special effects, the resultant movie quickly becomes an unwatchable bore. Data business is the same way.

So what is my advice for young and upcoming data scientists? Master the basics and be a specialist first. Pick a field that fits your aptitude, whether it be programming, software development, mathematics or statistics, and try to be really good at it. But remain curious about other related IT fields.

Then travel the world. Watch lots of movies. Read a variety of books. Not just technical books, but books about psychology, sociology, philosophy, science, economics and marketing, as well. This data business is inevitably related to activities that generate revenue for some organization. Try to understand the business ecosystem, not just technical systems. As marketing will always be a big part of the Big Data phenomenon, be an educated consumer first. Then look at advertisements and marketing campaigns from the promotor’s point of view, not just from an annoyed consumer’s view. Be an informed buyer through all available channels, online or offline. Then imagine how the world will be different in the future, and how a simple concept of a monetary transaction will transform along with other technical advances, which will certainly not stop at ApplePay. All of those changes will turn into business opportunities for people who understand data. If you see some real opportunities, try to imagine how you would create a startup company around them. You will quickly realize answering technical challenges is not even the half of building a viable business model.

If you are already one of those data scientists, live up to that title and be solution-oriented, not technology-oriented. Don’t be a slave to technologies, or be whom we sometimes address as a “data plumber” (who just moves data from one place to another). Be a master who wields data and technology to provide useful answers. And most importantly, don’t be evil (like Google says), and never do things just because you can. Always think about the social consequences, as actions based on data and technology affect real people, often negatively (more on this subject in future article). If you want to ride this Big Data wave for the foreseeable future, try not to annoy people who may not understand all the ins and outs of the data business. Don’t be the guy who spoils it for everyone else in the industry.

A while back, I started to see the unemployment rate as a rate of people who are being left behind during the progress (if we consider technical innovations as progress). Every evolutionary stage since the Industrial Revolution created gaps between supply and demand of new skillsets required for the new world. And this wave is not going to be an exception. It is unfortunate that, in this age of a high unemployment rate, we have such hard times finding good candidates for high tech positions. On one side, there are too many people who were educated under the old paradigm. And on the other side, there are too few people who can wield new technologies and apply them to satisfy business needs. If this new title “Data Scientist” means the latter, then yes. We need more of them, for sure. But we all need to be more realistic about how to groom them, as it would take a village to do so. And if we can’t even agree on what the job description for a data scientist should be, we will need lots of luck developing armies of them.

Direct Mail Design: Color

Designing for direct mail can be broken up into three segments: layout, color/images and copy. Since these can all be real challenges, we will take on each section in depth in separate posts to give you a better understanding and some ideas, as well as tips to get you started on the path to a great direct mail piece. Now let’s look at Section 2: Color.

Designing for direct mail can be broken up into three segments: layout, color/images and copy. Since these can all be real challenges, we will take on each section in depth in separate posts to give you a better understanding and some ideas, as well as tips to get you started on the path to a great direct mail piece.

Section 2: Color
Color, imagery and texture can greatly enhance the mail piece experience. Sometimes picking colors and images can be a challenge as well. How do you know what colors to choose? How should you pick the right images?

Here are eight colors and some of the meanings behind them:

  1. Red: Commands attention, alerts us, creates sense of urgency, risk, danger and aggressiveness.
  2. Yellow: Sunshine hue, spiritual color, represents warning, happiness, warmth, bright shades can be irritable to the eye in large quantities, often used to highlight or draw attention.
  3. Green: Money, nature, environmental concerns, freedom, healing and tranquility, is calming, refreshing, easy on the eyes.
  4. Blue: Suggests fiscal responsibility, inspires confidence, darker shades are authoritative, dark and bright shades represent trust, security, dignity, paler shades imply freshness and cleanliness.
  5. Orange: Warmth, instills sense of fun and excitement, implies health, cheer, makes product seem more affordable.
  6. White: Associated with innocence, purity, peace and contentment, considered clean and sterile, cool and refreshing, can have a calming, stabilizing influence.
  7. Black: Ultimate power color, suggests strength, authority, boldness, seriousness, stability and elegance, distinguished and classic, too much can be ominous.
  8. Brown: Associated with nature and the earth, associated with warmth and coziness, suggests richness, politeness, helpfulness and effectiveness, solid, credible.

Now that you have a basic idea of what the colors can mean, sit down and decide which colors and combinations are going to add impact to your layout. We discussed the layout in section one, feel free to review that again by clicking here.

After picking your colors, you need to decide on your images. Carefully consider your message as you approach design. The images you choose should not conflict with your message or your brand. Make sure to show the images to people outside the organization to see if they make the same associations you do.

Here are five things to consider when selecting images:

  1. Do not use images of just the product. Include people and real settings for a more realistic and connected approach.
  2. Match the emotional tone of the design to the emotion conveyed in the image.
  3. Images should not conflict with your color scheme.
  4. Select images that convey your message so that you can use less text.
  5. Include your logo. You need to always reaffirm the brand by using the logo.

So by making color and image choices that complement each other you are on your way to a great mail piece. When conflicts arise between different elements in the design of direct mail it can be a confusing message for the recipient. This ultimately means you mail is going in the trash and you wasted your money. Clear and concise elements that work together to for your message are key to getting the increase in your ROI.

Direct Mail Design: Layout

Designing for direct mail can be broken up into three segments: layout, color/images and copy. Since this can be a real challenge, we will take on each section in depth to give you a better understanding and some ideas as well as tips to get you started on the path to a great direct mail piece. To start, let’s talk about the layout.

Designing for direct mail can be broken up into three segments: layout, color/images and copy. Since these can all be real challenges, we will take on each section in depth in separate posts to give you a better understanding and some ideas, as well as tips to get you started on the path to a great direct mail piece.

Section One: Layout
So you need to design your next direct mail campaign and are having trouble with ideas. Sometimes the best ideas in direct mail design have already been used.

The first thing you can do is look at the mail that comes to your home or business (or check out some mailpieces at WhosMailingWhat.com). Are there examples that stand out to you? There is no shame in taking a direct mail piece that you received and making it your own. Of course, sometimes the opposite is true and you get inspired by a really horrible piece.

Here are eight questions to ask yourself as you are contemplating design layout:

  1. What pieces do you like best? What about co-workers and family?
    This base will provide you with enough information and perspectives to start.
  2. Does a certain design function better than another?
    Practicality and mail ability are both big factors here. Making sure ahead of time what will work for the post office and what won’t is a real time and money saver.
  3. How were images or color used to draw your attention?
    Note each one and how you feel or interpret what they are trying to convey. Does it compliment the message or detract from it and why?
  4. What language was used to get you curious?
    Analyzing the word structure and your reaction to it is a great way to identify what your word choices should be.
  5. Was the offer compelling?
    Sometimes the offer may be compelling, but if it is not what you are interested or already have it, you will not buy it. Targeting your messaging to the correct audience is key.
  6. Were the important points and call to action organized and clear?
    This is very important, you can really learn what to do and not to do by looking at the offer you receive.
  7. What types of response mechanisms were available?
    The more the better. Include as many as you can and make sure some of them are mobile. People are using tablets and phones for most of their search and buying needs. Plus, you will benefit from instant gratification. They want it now!
  8. How can you make this piece better?
    Make a list of all the things you would change and why. Have others do the same and compare notes. You will gain insight into how your piece should look.

When designing your mail piece, are you taking all of these factors into consideration? Have you looked at your piece through the eyes of your recipient? Remember there needs to be a very strong “what’s in it for me?” for your prospects/customers.

Have someone outside of your organization look at your layout to make sure the message you are trying to convey is coming through. Direct mail is very visual and tactile; you need to capitalize on that.

7 Tasty Copywriting Languages

How tasty is your copywriting? Taste-related words and figurative language can be more deliciously persuasive and sumptuously effective than literal words with the same meaning. Words that stimulate taste-activated areas in the brain are known to be associated with emotional processing. Language that frequently uses physical sensations or objects that refer to abstract domains, such as time, understanding or emotion, actually

How tasty is your copywriting? Taste-related words and figurative language can be more deliciously persuasive and sumptuously effective than literal words with the same meaning. Words that stimulate taste-activated areas in the brain are known to be associated with emotional processing. Language that frequently uses physical sensations or objects that refer to abstract domains, such as time, understanding or emotion, actually requires more brainpower, resulting in more engagement and comprehension.

To illustrate the point, the sentence, “She looked at him sweetly,” sparks more brain activity in emotion-based regions, like the amygdala, than, “She looked at him kindly.” Why? Because “sweet” amplifies a more physical experience, according to new research from Princeton University and the Free University of Berlin.

Figurative language can be more persuasive and effective in copywriting because your message is more imaginable in the reader’s mind.

For direct response copy, when practical (and without going overboard), a few tasty, figurative language uses can create more emotional reaction from your prospective customers. Figurative language works because the copy goes beyond the actual meanings of words. This way, the reader gains new insights into the objects or subjects in the work. Here are seven types of figurative language to consider using in copy and messaging.

1. Simile
A simile compares two things using the words “like” and “as.” Examples include:

  • Clean as a whistle
  • Brave as a lion
  • Stand out like a sore thumb

2. Metaphor
When you use a metaphor, you make a statement that doesn’t make literal sense, like “time is a thief.” It only makes sense when the similarities between the two things become apparent or someone understands the connection. Examples include:

  • Time is money
  • He has a heart of stone
  • America is a melting pot

3. Personification
Personification gives human characteristics to inanimate objects, animals or ideas. This can affect the way your customer imagines things. Examples include:

  • Opportunity knocked on the door
  • The sun can greet you tomorrow morning
  • The sky was full of dancing stars

4. Hyperbole
Hyperbole is an outrageous exaggeration that emphasizes a point, and can be ridiculous or funny. Hyperbole is useful in fiction to add color, but should be used sparingly and with caution in marketing copy. Examples are:

  • You snore louder than a freight train.
  • It’s a slow burg. I spent a couple of weeks there one day.
  • You could have knocked me over with a feather.

5. Symbolism
Symbolism occurs when a word which has meaning in itself, but it’s used to represent something entirely different. In this case, work with your graphics team, as images can express symbolism powerfully. Examples are:

  • Using an image of a flag to represent patriotism and a love for one’s country.
  • Using an apple pie to represent an American lifestyle.
  • Using an apple to represent education.

6. Alliteration. Alliteration is a repetition of the first consonant sounds in several words. An example:

  • Wide-eyed and wondering while we wait for the other ones to waken

7. Onomatopoeia. Onomatopoeia is the use of words that sound like their meaning, or mimic sounds. They add a level of fun and reality to writing. Here are some examples:

  • The burning wood hissed and crackled
  • The words: beep, boom, bong, click, clang, click, crunch, gobble, hum, meow, munch, oink, pow, quack, smash, swish, tweet, wham, whoosh, zap and zing.

Regardless of the type of words used, figurative language can help people visualize your product or service more instinctively. With tasty copy, you heighten senses that immerse prospects and customers to more powerfully see themselves possessing what you have to offer.

Only Trust Professionals – and Other Lessons From the NFL

I’m not even a big football fan, but I could certainly relate to the pain felt by the Saints when that last minute touchdown call was ruled against them. Of course the problem was with the inexperienced referees, called in when the professionals went out on strike. The same blame game is used when a direct marketing campaign goes awry. The client’s pointing its finger at the agency for its work/ideas, while the agency’s pointing its finger at the client for its direction/changes.

I’m not even a big football fan, but I could certainly relate to the pain felt by the Saints when that last minute touchdown call was ruled against them. Of course the problem was with the inexperienced referees, called in when the professionals went out on strike.

The same blame game is used when a direct marketing campaign goes awry. The client’s pointing its finger at the agency for its work/ideas, while the agency’s pointing its finger at the client for its direction/changes.

A successful direct marketing campaign is comprised of many complex facets—and it takes knowledge, experience and expertise to execute it flawlessly.

Despite the fact that many agencies claim complete integration and global knowledge, the reality is they often talk a good strategic game, but when handed a DM assignment, the executional details are left to the inexperienced.

I’ve received several calls recently from colleagues who want me to “help their agency” with the direct mail portion of a campaign. Not the strategy or the creative (their agency won’t let anyone touch that golden egg), but the list. It seems the agency doesn’t know the first thing about lists … and had been trying to sell the client something found on the internet from an unknown supplier.

That’s like asking the NFL referee to make the call on the Saints interference, but not on the Seahawks touchdown. The two are inexplicably entwined.

So I am asking, no begging, that clients identify and leverage agency partners based on their specialty. Spend your time understanding what skills are truly in the agency’s wheelhouse—and not a “sure, we can do that too!” skill. If the agency specializes in branding, then that’s what they’re probably very, very good at … and if it specializes in digital marketing (kind of a broad skill, but whatever), then ask them for help with your digital needs.

Good direct marketing agencies understand how to step back and think about your marketing needs based on your business goals and objectives. They delve deep into target audience research, trying to understand the audience mindset and identify key messages that will resonate and motivate a response. They may, in fact, recommend that you don’t use email (horrors!) or direct mail (gasp!) in your campaign mix for a variety of reasons, including the inability to find blue-eyed, left handed crane operators in any meaningful quantity that would make sense.

Good direct marketing agencies know how to source lists that are compiled from reputable sources. And they know how to evaluate those lists, identify the potential winners, and set up an unbiased test matrix to test and learn from a statistically valid sample size.

Good direct marketing agencies know how to design a campaign that will yield the desired response from the target. They’ll have solid rationale as to why a #10 package makes sense instead of a postcard, or why a three-panel self-mailer doesn’t make sense—even though your brand agency designed one that was “cool.” Or why an email shouldn’t consist of product images, or have a Subject line that’s longer than 40 characters.

Good direct marketing agencies know how to write compelling teasers, headlines, subheads, Johnson Boxes, P.S.’s and body copy based on years of testing and experience. They know how to leverage customer quotes, and the difference between a brochure, a buckslip, and a lift note.

Good direct marketing agencies don’t pick an offer because it sounds like fun, or because the client wants to get rid of the pile of chachkies in the warehouse. Their recommendations for offers is based on a deep understanding of what can motivate a target, an evaluation of the ROI model, and in-depth experience based on years of testing.

So if you view direct marketing as a skill set that can be handled by the temporary ref, then let your branding agency take charge. But if you want real results, bring in the pros.

3 Ways Rank-and-File Marketers Matter to the C-Suite in a Brave New Marketing World

A couple weeks ago in my post titled “Wanted: Data-Driven, Digital CMOs,” I wrote about the enormous pressure CMOs are finding themselves under as the world digitizes, requiring a new type of leader, one who understands and feels comfortable in the digital space. The result of this changing dynamic has been a dramatic shortening of your average CMO’s tenure. I’m not the first to observe this trend—it’s been covered in many places over the past few months, including this great article from Fast Company. In response to this post, however, many colleagues have asked me “What does this mean for the rank-and-file marketer?” I thought this was an excellent question; one I’ve not seen discussed elsewhere.

A couple weeks ago in my post titled “Wanted: Data-Driven, Digital CMOs,” I wrote about the enormous pressure CMOs are finding themselves under as the world digitizes, requiring a new type of leader, one who understands and feels comfortable in the digital space. The result of this changing dynamic has been a dramatic shortening of your average CMO’s tenure.

I’m not the first to observe this trend—it’s been covered in many places over the past few months, including this great article from Fast Company. In response to this post, however, many colleagues have asked me “What does this mean for the rank-and-file marketer?” I thought this was an excellent question; one I’ve not seen discussed elsewhere.

By any standard, it’s certainly not an easy time to be a marketer. Over the past decade, nearly everything we know has changed, as new technologies have arrived in a dizzying fashion, upending the established order. The result for most firms has ranged from confusion to clarity, from paralysis to paroxysm—very frequently all at the same time! Working in an environment like this is definitely no picnic, as firms flail around like a hurt animal trying to figure out what to do, reducing head count, hiring, outsourcing, in-sourcing, you name it.

It may not be an easy time to be a marketer, but I think it’s a good time. The reason why is that marketing has evolved in four very important ways:

1. Marketing has become data driven—in the digital age, information is power. Contemporary marketing requires learning about who your customers are, what they look like, what attributes and affinities they share, and so on. Success means becoming fluent in the new language of the digital age—understanding what terms like “impressions,” “clicks,” “likes” and “followers” mean. But that’s not all: Success requires a deep understanding of and familiarity with campaign analytics, what they mean and signify, and how to interpret and improve upon them.

2. Marketing is technology-focused—it’s no secret that a large portion of marketers’ budgets are now being allocated to digital. Anyone who’s worked in the digital marketing arena knows that success in the space means understanding the new technology ecosystem. The other major technology trend is the fragmentation of the IT infrastructure as the SaaS/Cloud model gains traction. In this new service model, it’s marketing that’s mostly responsible for buying, using and maintaining these new tools.

3. Marketing is highly operational in nature—unlike the brand strategists of yesteryear, today’s marketing department is almost entirely focused on operations, with a heavy emphasis being placed on creating, testing and launching, tracking and optimizing numerous marketing campaigns across various channels using different tools.

In this new environment, the DNA of the rank-and-file marketer has changed radically, morphing from that of a brand steward into, well, something else entirely. Any way you look at it, today’s marketers are highly trained and qualified specialists, possessing a wide range of skills and knowledge, which can take months, if not years, to master.

Moreover, success in any given marketing role requires a deep understanding of various marketing program details, familiarity with firm’s marketing technology, systems and tools, not to mention the prevailing corporate culture. All in all, it’s a tall order.

Over the years, I’ve consulted with dozens of large firms, and I can tell you firsthand that most marketing leadership stakeholders are not digital people. In other words, the only people in the firm who really “get” what the firm’s marketing department is actually doing are the marketers themselves. Interesting, huh?

So what does this all mean? Well, in coming years I foresee a shift in the balance of power as the old generation of marketers gives way to a new generation of younger digital specialists. Now, of course, one generation passing the mantle to the next is the natural order of things. But, based on what’s going on, I see this trend accelerating dramatically in coming months and years, as those who don’t get it are replaced by those who do.

If you’re a marketer, all if this is undoubtedly good news, meaning you’re not only much more important than you think, but your trip up the proverbial corporate ladder is that much shorter. So go forth, young man (or woman), it’s a brave new world!

Any questions or feedback? As usual, I’d love to hear it.

—Rio