Media Outlook 2019: Spell Marketing with a ‘D’

The January marketing calendar in New York has included for the past decade or so a certain can’t-miss event of the Direct Marketing Club of New York. In 60 fly-by minutes, 100-plus advertising and marketing professionals hear a review of the previous year in marketing spend, a media outlook for the current year and macro-economic trends driving both.

The January marketing calendar in New York has included for the past decade or so a certain can’t-miss event of the Direct Marketing Club of New York. In 60 fly-by minutes, 100-plus advertising and marketing professionals hear a review of the previous year in marketing spend, a media outlook for the current year and macro-economic trends driving both.

Bruce Biegel, senior managing director at Winterberry Group, keeps everyone engaged, taking notes and thinking about their own experiences in the mix of statistics regarding digital, mobile, direct mail, TV and programmatic advertising.

“We will be OK if we can manage the Shutdown, Trump, China, Mueller, Congress and Brexit,” he noted, all of which weigh on business confidence.

Suffice it to say, marketing organizations and business, in general must navigate an interesting journey. Biegel reports estimated U.S. Gross Domestic Product (GDP) growth of 2.3 percent in 2019 down from 3 percent in 2018, while total marketing spending growth in 2018 had dipped below its historic level of exceeding two times GDP growth.

In 2019, we are poised for 5.3 percent growth in advertising and marketing spending a slight gain from the 5.2 percent growth of 2018 over 2017.

Watch the Super Bowl, By All Means But Offline Dominance Is Diminishing

Look under the hood, and you see what the big drivers are. Offline spending including sponsorships, linear TV, print, radio, outdoor and direct mail will spot anemic growth, combined, of 0.1 percent in 2019. (Of these, direct mail and sponsorships will each post growth of more than 3 percent, Winterberry Group predicts.)

But online spending growth display, digital video, social, email, digital radio, digital out-of-home, and search will grow by 15.5 percent. Has offline media across all categories finally reached its zenith? Perhaps. (See Figure 1.)

Figure 1.

Credit: Winterberry Group, 2019

Digital media spend achieved 50 percent of offline media spend for the first time in 2018. In 2019, it may reach 60 percent! So who should care?

We do! We are the livers and breathers of data, and data is in the driver’s seat. Biegel sees data spending growing by nearly 6 percent this year totaling $21.27 billion. Of this, $9.66 billion will be offline data spending, primarily direct mail. TV data spending (addressable, OTT) will reach $1.8 billion, digital data $7.85 billion, and email data spend $1.96 billion (see Figure 2.)

Figure 2.

Credit: Winterberry Group, 2019

Tortured CMOs: Unless She’s a Data Believer

Marketing today and tomorrow is not marketing yesterday. If marketing leadership does not recognize and understand data’s contribution to ad measurement, attribution and business objective ROI, then it’s time for a new generation to lead and succeed. Marketing today is spelled with a D: Data-Driven.

Unfortunately we don’t have all the data we need to manage Shutdown, Trump, China, Mueller, Congress and Brexit. That’s where sheer luck and gut instincts may still have a valid role. Sigh.

Why Behavioral Science Is Critical to Marketing and Research

What if we could identify consumers’ underlying emotions or motivations to improve our understanding of whether they were actually going to purchase a product? Over the past few years, marketing and research has been digging into the “why” behind behaviors to get even deeper, below the surface of the insights we deliver. The goal is to help brands better understand the true drivers of consumers’ behavior — and it all starts with behavioral science.

What if we could identify consumers’ underlying emotions or motivations to improve our understanding of whether they were actually going to purchase a product? Over the past few years, marketing and research has been digging into the “why” behind behaviors to get even deeper, below the surface of the insights we deliver. The goal is to help brands better understand the true drivers of consumers’ behavior — and it all starts with behavioral science.

What Is Behavioral Science?

Behavioral science isn’t a new industry, but within the past few years is something of an emerging topic in marketing and research. At its core, behavioral science and the research that results from it, seeks to understand the many aspects related to someone’s habits or decision-making. Most importantly, as we noted, it helps to understand why people make certain decisions.

If you think of that in the context of our marketing and product strategies, it’s clear why behavioral science plays a role in market research. There are a variety of methods that can get close to truly understanding consumer behavior, but much of them can fail to capture empirical evidence — sensory information captured through observations and the documentation of behaviors through experimentation.

As a result, the importance and rise of behavioral science in marketing and research is no small subject. Just in the past year, there have already been numerous events discussing behavioral science specific to gathering and analyzing data to understand why consumers make decisions — but marketers and researchers, by and large, are still figuring out how to leverage it.

Leveraging Behavioral Data

Big data can be used as a possible solution for at least two reasons. First, it gives us access to more data than ever before, including data based on actual behavior from purchasing, web analytics, subscriptions, and more. As a result, big data can reduce the struggles we sometimes have with differences between stated versus observed behavior.

Second, there are big data sources that allow us to understand motivations of our consumers by examining the big 5 personality traits for millions and millions of people. By understanding different personalities, we can begin to realize if being “extroverted” or “conscientious” drives consumers’ purchasing. Some suggest that behavioral science and the resulting data on motivations behind decision making will be the new normal for market research. We agree that understanding what people don’t tell us in surveys is as important as what they do. Together, these two types of data give us a more well-rounded picture of consumer behavior, and with the right methodology, you can gain this knowledge quickly.

In a specific use case, a brand was looking to understand their target audience for a new product innovation. They had hypothesis’ about what this audience would look like, and likely could have gained that knowledge through standard quantitative research. However, by incorporating an approach that combines survey data and big data, they were able to understand who their audience was, but also what would motivate them to purchase this particular new product. The moral of the story? Consumers are more than just the people that buy your product.

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.

4 Benefits of Applying Marketing Analytics

Marketing analytics is no small subject in today’s world of business. In fact, according to Transparency Market Research, the marketing analytics industry is set to grow by roughly 14% by 2022. Why such growth? Marketing analytics has a tremendous impact on a marketing organization’s activities, but also on a brand’s overall understanding of their entire company’s success.

Marketing analytics is no small subject in today’s world of business. In fact, according to Transparency Market Research, the marketing analytics industry is set to grow by roughly 14% by 2022. Why such growth? Marketing analytics has a tremendous impact on a marketing organization’s activities, but also on a brand’s overall understanding of their entire company’s success.

There are four unique benefits marketing analytics provides, and combined together, these benefits give a holistic view of an organization’s past, present and future.

But First: What Is Marketing Analytics and Why Is It Important?

Marketing analytics is a result of the technology and influx of data we use as marketers. Early on, marketing analytics was a relatively simple concept. It encompassed the process of evaluating marketing efforts from multiple data sources, processes or technology to understand the effectiveness of marketing activities from a big-picture view — often through the use of metrics. Fundamentally, it’s all about quantifying the results of marketing efforts that take place both online and offline.

Today, marketing analytics has become an entire industry that’s changing the way we work and the type of work we do as marketers. 

It’s important to measure the financial impact of not just marketing but of a variety of efforts from product and sales — which marketing analytics also can provide. As a result, knowing and understanding the different types of analysis and the benefits they provide within marketing analytics, can help to identify what metrics to focus on for what objectives — because objectives can be an endless list of how to understand or increase ROI, monitor trends over time, determine campaign effectiveness, forecast future results, and so on.

The 4 Benefits of Applying Marketing Analytics

1. Learn What Happened

Marketing analytics can first lend insight into what happened in the past and why. This is instrumental to marketing teams in order to avoid making the same mistakes. Through descriptive analysis and the use of customer relationship management and marketing automation platforms, analytics bring to light not only what happened in the past but also provide answers to questions on specific topics. For example, you can ask more about why a specific metric performed the way it did, or what impacted the sales of a specific product.

2. Gauge What’s Happening Now

Marketing analytics can also help you understand what’s currently taking place in regards to your marketing efforts. This helps determine if you need to pivot or quickly make changes in order to avoid mistakes or make improvements. Using dashboards to display current engagements in an email track or the status of new leads are examples of marketing analytics that look to assess the real-time status of marketing efforts. Usually, these dashboards are created by employing business intelligence practices in addition to a marketing automation platform.

3. Predict What Might Happen

Some could say the predictive aspect of marketing analytics is the most important part of it. Through predictive modelings such as regression analysis, clustering, propensity models and collaborative filtering, we can start to anticipate consumer behavior. Web analytics tracking that incorporates probabilities, for example, can be used to foresee when a person may leave a site and when. Marketers can then utilize this information to execute specific marketing tactics at those moments to retain customers.

Or perhaps it’s marketing analytics that assesses lead management processes to prioritize leads based on those similar to current customers. This helps identifies who already has a higher propensity to buy. Either way, the goal of marketing analytics for the future will be to move away from a rear-view strategy to focus on the future. Luckily, the influx of data, machine learning, and improved statistical algorithms mean our ability to accurately predict the likelihood of future outcomes will rise exponentially.

4. Optimize Efforts

This last benefit only comes when you combine your analytics with your market research objectives — but if you do so you could see the greatest impact. In fact, if you’re not ensuring your marketing analytics and market research work together, then you could be missing out on a lot of opportunities. Essentially, it’s about translating marketing analytics findings into market research objectives. A common mistake marketers make in conducting marketing analytics is forgetting to gather real customer feedback. This activity is important to bridge the gap between analytics insights, a marketing strategy and activation.

In addition to the first three benefits or approaches, brands should use marketing research as a tool to push their marketing analytics from just learning about lead generation and sales metrics to actually understand customers in the context of their marketing opportunities.

Don’t Ignore Baby Boomers

Quick quiz: Which generation is huge in size, interested in experiences, loves to travel, owns digital devices and is active in social media? Millennials? No, it’s actually Baby Boomers. Surprised? The Baby Boomer generation tends to be overlooked, but they are an important consumer segment.

Baby BoomersQuick quiz: Which generation is huge in size, interested in experiences, loves to travel, owns digital devices and is active in social media?

Millennials?

No, it’s actually Baby Boomers. Surprised? The Baby Boomer generation tends to be overlooked, but they are an important consumer segment.

This population — born between 1946 and 1964 — are 74 million strong and have more disposable income than any other generation. They are more likely to be in the upper-income group. According to Pew Research, 27 percent of boomers are in the upper income group, which is the highest figure of all generations. Principal economist at Kantar Retail, Doug Hermanson, notes:

“Upper-income Boomers can sustain their pre-recession spending and be a strong driver of the consumer economy over the next five to 10 years. They have the money to spend. It’s a different mindset of saving before and now saying, ‘I’ve got to spend it while I’m here.’”

Let’s dig into these mass affluent Baby Boomers. These are defined as those who have $100,000-$250,000 in household income and over $250,000 in savings. They are an optimistic bunch, with 77 percent saying their goal is to have an interesting life.

Over 80 percent say they live a healthy lifestyle, and they are much more likely to give to charities. Pew Research reports that Boomers are living longer, with an average life expectancy of 80 years old, up from 68 in 1950. Many are now entering their retirement years. While about half of all adults say they feel younger than their actual age, 61 percent of Boomers are feeling more spry than their age would imply.

So what drives spending for this important segment? Quality is important to the mass affluent Boomer, with nine out of 10 saying they are more likely to value quality over brand name. They also like to shop within brands they feel an emotional connection with. And over 70 percent of Boomers across all income levels say the fact that they “like” a retailer is a driver of retail selection.

So, now that we have seen how they like to spend money, let’s take a look at what this generation plans to spend money on. About a quarter of Baby Boomers in the mass affluent category say they will spend more money in general in the coming year. Baby Boomers at the higher income level are more likely to prefer experiences over things: 73 percent of them say they prefer to spend money on experiences, vs. 69 percent of Millennials. Their spend categories emphasize travel, home improvement and charities.

Additionally, Synchrony Financial consumer surveys reveal the following:

  • The highest category of future spend will be travel. About 40 percent of mass affluent Boomers plan to spend more on travel next year. AARP estimates Baby Boomers spend more than $120 billion annually on leisure travel.
  • The second highest spend category is home improvement, with 32 percent of Boomers spending more on home improvement in the coming year, and 22 percent spending more on home furnishings.
  • Boomers are much more likely to say that they give to charitable causes, with 79 percent saying they plan in increase their charitable giving.

The Digital Divide: Boomers and Technology

Let’s take a look at the most talked-about difference between Baby Boomers and younger generations — digital technology. The reality is that the Baby Boomer population is on-par with younger generations when it comes to smartphone ownership, online shopping and social media access. Three out of four Baby Boomers own a smartphone, up 19 percent from a year ago. The generational divide exists in the usage of digital devices. Synchrony Financial’s research studies show that Boomers are much less likely than Millennials to use their smartphone for a multitude of tasks — from shopping to texting to social media postings.

But contrary to what some may think, Boomers have a great deal of access and interaction with social media. Ninety-two percent of Boomers say they have access to a social media channel — mainly Facebook (82 percent of Boomers have access to Facebook, up from 76 percent only a year ago). But they not influenced by social media for purchases. Only one third say they purchased a product after seeing it on social media, which is a significantly lower figure than that of younger generations: For Millennials, that number tops 70 percent.

How well does your business cater to this large and important segment of the population? Generalizations are difficult for any population of this size, but in general, Boomers are optimistic, secure and not done spending. Brands who provide a great shopping experience, high quality and seamless digital technology will go far in attracting this important segment.

Sources: All data is sourced from the following three studies, unless otherwise noted: Synchrony Financial 2016 Loyalty Study, Synchrony Financial 2016 Affluent Survey and Synchrony Financial 2016 Digital Study. All references to consumers and population refer to the survey respondents.

Note: The views expressed in this blog are those of the blogger and not necessarily of Synchrony Financial.