Solving the Real-World Puzzle of People-Based Marketing

Companies are seeking to create a better customer experience by breaking down marketing silos and shifting to people-based marketing.

By Wayne St. Amand

There’s a lot of buzz around the term “people-based marketing.” Since Facebook introduced the concept in 2014, marketers and advertisers have embraced it, with varying degrees of success.

According to Forbes, “People-based marketing represents an industry shift from targeting devices to connecting with the right people at the right time, with the right message.”

For marketers, the concept of ‘right person, right time, right message’ is nothing new. As consumers increasingly experience their lives online and through mobile devices, the opportunity to use data to provide tailored messaging across channels and devices and deliver optimal customer experiences has never been greater.

Yet capitalizing on this opportunity remains a key challenge for most brands. According to Experian’s 2016 Digital Marketing Report, 56 percent of C-level executives cite orchestrating and managing cross-channel customer interactions as a top priority. Another 33 percent name delivering relevant and contextual content as a top challenge to providing great customer experiences.

>> Check out our session at the Attribution Accelerator “Marketing Intelligence: Solving the Real-World Puzzle of People-Based Marketing” presented by Visual IQ CMO Wayne St. Amand at 11:45 a.m. on the Mainstage <<

Identifying Consumers As Individuals

People-based marketing means identifying your customers and prospects as individuals, not just devices or cookies. It’s a shift in thinking. Instead of viewing consumer behavior in separate silos — display, email, search, social, etc. — you place the individual at the center of marketing activity.

With people-based marketing, you have greater confidence that your message is reaching your best customer and driving measurable results. When you can track and measure consumer behavior across channels and devices, you can understand how they’re interacting with your brand and which interactions are generating activity (an online conversion or an in-store purchase, for example).

Reaching Today’s Empowered Consumers

Today’s consumers have more choices and control than ever before, and they expect highly relevant experiences, regardless of when or where they are taking place.

  • More than 37 percent of consumers own a combination of smartphones, laptops/desktops, and tablets.
  • 87 percent of consumers use more than one device at a time.

Managing marketing and advertising independently, using siloed, channel-specific strategies, tactics, and metrics doesn’t produce the results we need. Yet most brands today analyze the attributes of their customers and prospects separately from marketing performance, with little to no intersection.

Marketers have access to more performance and audience data than ever before, but it’s scattered across multiple martech and adtech systems and analyzed leveraging outdated measurement techniques. As a result, teams are unable to gain a unified view of each consumer and the channels, devices and tactics that are most effective in driving sales, repeat purchases, loyalty program enrollments and other desired business outcomes.

To deliver relevant and coordinated communications that enhance the customer experience, the division between audience and attribution must come to an end. People-based marketing helps you “connect the dots” between multiple consumer interactions by creating a single view of customers and prospects.

Creating Actionable Consumer Profiles

People-based marketing is made possible by the creation of a persistent identifier (or ID) that links a person to his or her devices and browsers.

Today, individuals are assigned different user ID’s by every entity they interact with,  making it challenging for marketers to recognize the same user across multiple audience segments, marketing platforms, devices and digital vs. offline environments. Without a persistent ID, you must rely on a soup of CRM and other data, as well as cookies, which don’t work on mobile devices.

A persistent ID is created by reconciling the information a brand collects about their customers and prospects (first-party data) with information gathered by external organizations (third-party data).

This process de-duplicates users across multiple devices (desktop, tablets, smartphones, etc.) and synchronizes it with deep demographic, transactional, and behavioral insight (age, household income, purchase intent, etc.) to create robust consumer profiles.

With a persistent ID, it’s possible to identity a person across his or her smartphone, desktop, laptop and other connected devices (such as addressable TVs), which allows you to deliver personalized, relevant messages. It’s the arrival of the sought-after right person, right time, right message triumvirate.

The tremendous power of people-based marketing is its ability to target real people rather than generic buyer personas. Understanding who your customers and prospects are, what they are like, and how they behave, is key to delivering tailored messages and experiences that meet their unique needs and preferences.

By improving the overall consumer experience, marketers can boost engagement and conversions, increase lifetime value, improve ROI and, ultimately, gain a competitive advantage.

Implementing a People-Based Approach

People-based marketing requires shifting away from traditional advertising and marketing silos. Most companies rely on a structure in which display, social, print, radio, TV and other channels are managed independently, each with their own teams and budgets. Each team optimizes their budget to meet their metrics, independently of the other channels.

With people-based marketing, organizations move toward a cross-functional team. This approach allows teams to track, measure and optimize strategies and tactics across digital, mobile and physical spaces using a shared set of success metrics.

People-based marketing also requires collecting and consolidating audience and behavioral data from separate systems into a single repository, such as a data management platform (DMP).

The best solutions combine data from both online and offline sources (web, mobile, call center, in-store, etc.), as well as demographic, intent, interest, and other audience attribute data from first- and third-party data sources.

By synthesizing all of this data in one place, marketers can develop a more complete, people-based view of their customers and prospects.

A New Era of Marketing

It’s time for marketers to move beyond the world of cookies as consumers come to expect a more relevant, personalized experience. When you can identify your customers and prospects as people, not just devices, you can achieve one-to-one people-based marketing in ways that haven’t been possible before.

Don’t miss our Attribution Accelerator Session
Marketing Intelligence: Solving the Real-World Puzzle of People-Based Marketing
Wayne St. Amand, CMO, Visual IQ
11:45 a.m.

For more information about people-based marketing, download a copy of the new ebook People-Based Marketing: Intelligence for a New Age from Visual IQ.

Monthly Dose of Design: Improve Your Discussion Guides with Visual Design

Learn how to apply design principals to discussion guides in the latest edition of Monthly Dose of Design.

By Nicholas Lee and Emma Galvin

In last month’s Monthly Dose of Design, we identified design fundamentals for researchers.

However, at Northstar, we believe that design can influence the whole research process – not just the final output! Therefore, this month we will tell you how you can easily apply design principals to discussion guides to aid legibility and ease of reading. By doing so, your clients will better understand this vital research document when you send it to them and you will be able to better conduct conversations with your research participants.

Below are two examples of a discussion guide. One which uses design principals and one which doesn’t.

By using the design principals illustrated on the left, here is what you can hope to achieve with your discussion guides:

Firstly, it is vital to make sure your reader can clearly read the guide while understanding what’s important within it…

A Clear Reading Path

A clear reading path is the most important visual design consideration to make when designing a discussion guide. Losing your client within a sea of text will harm their understanding of what you intend to discuss and how you are going to meet their objectives. Equally, not being able to identify your next discussion point in a focus group or interview will harm the quality of engagement you have with your participants. Reading a discussion guide should be a journey aided with visual cues such as numbers, colours and shapes. These design assets can help you and your client read the guide more easily.

Hierarchy of Importance

It is essential to visually signpost important points within your guide’s content. This will ensure your client can easily see what your discussion points are, and you can make sure you emphasise these in your focus group or interview. You can do this by making important elements bigger and bolder than a less important element which might be smaller and fainter. Scale is often used to help communicate hierarchy by drawing attention towards and away from certain points. This signifies their importance within the guide – so make sure this is reflected in the font sizes you are using.

Secondly, the following design mechanisms can help enhance clarity of the reader path and content importance…

Avoid Long Lines of Text

The optimum words per line of text usually ranges around 13 and is best not to go beyond 18 words. Long lines of text can be fatiguing to read. Also, long lines of text increase the chance of getting lost whilst reading, and potentially you could end up re-reading the same line or accidentally skipping a line and losing the idea you’re discussing with participants.

Use Spacing Wisely

Provide enough inter-line spacing, or leading space (vertical space between the lines). This will make it easier for your reader’s eyes. Often to get the optimum line spacing you will need to go beyond the default line spacing your word processor or page layout program suggests. Remember, it will be you and your client reading the guide, not your PC!

Use Colours to Link Content

Just because the default colour of Microsoft Word is black and white, doesn’t mean that your guide should follow suit. Colours are a great way to link relevant content together such as questions to objectives or linking feedback to external references. Using colour to pair this information will make it clear to your client what questions are meeting which objectives and how you will use participant feedback within your discussion.

Highlight Important points

Highlighting key points, actions or questions makes them stand out and prevents you from missing them, and keeps less important notes in the background text.

What’s next…
Our next post will show you how to design research questionnaires so that layout, colour, sizing and interactivity can improve the survey experience for research participants.

It’s time for the GRIT Survey – please participate now!

Please participate in the newest GRIT Survey and help us understand what’s shaping our industry. Your participation in the GRIT Survey makes the GRIT Report possible.

The GreenBook Research Industry Trends (GRIT) study is the leading global survey of the market research profession and industry. Twice a year we ask insights professionals to help us all understand the trends impacting our work, our businesses, and our jobs via the GRIT Survey.

It’s now time for the for the Q4 2017 wave, and we’d like to ask you to take no more than 15 minutes to share your experience and opinions with us. Want to give back to our industry by taking the survey? Please head over to the survey.

As always, we’re diving deep into many of the most important areas and issues that impact insights professionals. In this wave we’re exploring topics such as the role of research in the organization, who owns the data, time spent on research functions, challenges & opportunities in the future, adoption of emerging methods & technologies, use of traditional methods & technologies, satisfaction levels with suppliers, the financial outlook for the industry, and your take on the buzz topics of the day.

Because many of the GRIT tracking questions included in this edition were developed in the pre-mobile era, it’s challenging to optimize them for a great mobile survey-taking experience while maintaining data consistency. As a result, we recommend completing this survey on a desktop, laptop, or tablet.

All who complete the survey will receive:

  • A PDF copy of the final GRIT Report before it’s released publicly.
  • Access to all survey data via a special GRIT data portal.
  • Priority free access to the GRIT webinar series.

Thank you in advance for sharing your perspective … and for sharing the survey with your colleagues!




Thanks to Our GRIT Partners

Research Partners

Ascribe, AYTM – Ask Your Target Market, Bakamo Social, Consensus Point, CX Network, 3 Translate, Gen2 Advisors, Lightspeed, Michigan State University, MROC Japan – Community Solutions Company, mTAB, Multivariate Solutions, NewMR, OfficeReports, Research NowResearchscape International, Stakeholder Advisory Services, Virtual Incentives

Sample Partners

A.C. Nielsen Center for Marketing Research at The Wisconsin School of Business, AIM, AMAI, American Marketing Association New YorkAsia Pacific Research Committee (APRC), ARIA, Australian Market & Social Research Society (AMSRS), BAQMaR, BVA, MRS, Next Gen Market Research (NGMR), OdinText Inc., Provokers, Qualitative Research Consultants Association, The Research Club, The UTA MSMR Alumni Association, University of Georgia | MRII, Women In Research

Being Relevant Facing the New Argentine Consumer

How are Argentine consumers changing the way their interact with traditional and disruptive brands? Find out LATAM's latest consumer trends in in this blog.

By Sebastián Corzo

Extreme rationality?

In Argentina, the recent growth of low-price brands and the explosion in the number of visits to wholesalers might make us think that the Argentine consumers have broken their bond with the traditional brands and that decisions are based purely on price.

Although it is true that this new consumer is more experienced savvy, and it is implementing new defensive strategies, the new purchase habits do not imply that people are resigning the quality, the experiences and the symbolic and emotional benefits that traditional brands promise.

Those known as “A brands” are struggling for the minds, hearts and pockets of the consumers, and they keep leading most of the FMCG categories in our market.

What are consumers looking for?

After the primary elections, economic perspectives (measured by Kantar TNS) have improved significantly, and consumers are more optimistic and willing to make important decisions. In this context of incipient consumption recovery, the key words to explore are convenience and freedom.

Convenience means that you need more than low prices and B brands to thrive. Consumers want to find what they need, at an adequate format and size, at a fair price, in any accessible channel (that could be online).

Freedom, according to the new consumer dictionary, is translated as the capacity to choose whatever you want at any time. Argentine do not enjoy anymore to be told in which supermarket they should buy, when to do it, which credit cards they should use, and how many bottles they should buy in order to get a minor discount. Consumers are looking for brands that help them to make life easier, they want to avoid over-complexity.

What should brands do? In an era characterized by horizontality in relationships, brands should put themselves on the same level of consumers. They have to start an honest and transparent dialogue, because any attempt to show something not so credible will be quickly identified and punished.

If consumers are willing to keep making an effort in favour of the brands they prefer they have to react similarly. That is why we are increasingly noticing more different kinds of commitments made by large brands, like “Pacto Porrón”, one of the last promotions launched by Quilmes, the leader brand in the beer category. These kinds of initiatives are positively evaluated by consumers as long as they are seen as something genuine and not tricky, since they offer an alternative way to have an experience with the brand.

The permanent challenge that brands have to face is how to remain relevant and attractive to consumers. They have to see the person behind the consumer and understand that people change all the time. Consequently, marketers must be agile in order to catch the emerging trends and seize new opportunities that may arise.

It is crucial to pay close attention to the emergent things: new factors that are starting to happen among adjacent industries, start-ups and academic forums. According to BrandZ global ranking, made by Kantar Millward Brown, over the last decade young and disruptive brands have increased importance. Those disruptors like Google, Apple, Amazon and Facebook, should be observed and followed, because they are going to keep changing the rules and redefining purchase and consumption habits across all the categories of products and services.

In the market research industry we have to be prepared to establish collaborative relationships with these new players that can develop disruptive skills and technologies to our business.

Corporate Researchers Speak

When do market researchers research themselves? Find out about Collaborata's new cost-sharing study to answer the question of how to sell corporate researchers.

By Lenny Murphy

So, here’s a novel concept: researchers investing in research themselves. Think about it.

If you, as a research seller, were to actually purchase a research study yourself, what would be the focus of that study?

Would it be how the industry is trending in terms of the types of new technologies and designs that are gaining traction and solving today’s problems? That’s a logical focus.  But, that’s essentially what we already cover in great detail with the GRIT Report.

So, my guess would be the research that you’d be willing to invest in would need to be tied to revenue. You’d want to see a realistic ROI on whatever research investment you’d make.

So, based on that assumption, I want to tell you about a series of ongoing meetings we’ve had with David Harris of Insight & Measurement and Peter Zollo of Collaborata.

Many of David’s clients are research suppliers. He consults with them on how best to grow their business in today’s zero-based and fast-changing corporate environment. In fact, one of Dave’s clients was ready to commission a deep-dive qualitative study of corporate research buyers to develop an empathetic understanding of what they really want from research sellers. This research supplier specifically wants to better understand how to engage and sell new prospects, so his firm becomes a preferred partner.

Dave, who’s a former corporate research client himself (he ran research for many years at GlaxoSmithKline), loved the clarity and intelligence of this research request. But, he also wanted to address this need with a meaningful solution, which wouldn’t be too expensive for a single researcher supplier. So, he went to Peter with the idea of Collaborata helping to launch this study by bringing in co-sponsors to share the costs and the results.

That’s where we came in. At IIeX in Atlanta, Dave and Peter approached us with their concept. We loved it and immediately said, “we’re in!”.  To the best of our knowledge, there has never been a proper study conducted about how to actually sell MR clients — from how they first want you to contact them to how they’d like you develop the relationship. And, that’s what this study does. It’s called, “How to Engage and Sell Us to Become a Preferred Partner.” It reveals clients’ pain points and needs throughout their path to purchase (i.e., their path to purchase research!).

GreenBook will be recruiting the corporate researcher respondents for the study, which will consist of two phases: 1) A week of projective exercises — essentially digital ethnographies — on the Aha platform; and 2) In-depth interviews conducted by Dave together with Jim Chastain of RealityCheck.

We hope that you’re a researcher who truly believes in the power of research, so that you’ll invest in this critical study. And, if you become an early co-sponsor, you’ll have the opportunity for input into its design. Dave will be delighted to jump on a call with you.

By any measure, because of Collaborata’s cost-sharing model, this is not an expensive study. The buy-in price to become a co-sponsor is only $7,500.

But, to help you better swallow even that amount, GreenBook is offering a $3,000 credit for banner ads or sponsored post on our new Blog (which debuts the end of October) and two tickets to IIeX in Atlanta, which is a $2,900 value. So, your net investment in the study, taking into account the value of these two offers, is only $1,600. So, think about your ROI on that!

If you can land only one new project — or simply make inroads with an important new client – based on these insights, I’d say it’s a no-brainer. But that’s me. I believe in good, smart, strategic research. Especially research that’s directly tied to revenue.

One last consideration: How would you feel if your key competitors essentially bought this “playbook” on how to sell corporate researchers? Don’t you want to be armed with these insights?

So, let me know what you think. And, please check out the study on Collaborata.  

Singing a New but Familiar Tune

How do people make decisions between the familiar and new and surprising? System1 Research presents a study using Predictive Markets to predict the winners for the 2017 JUNO Awards in Canada.

By Chasson Gracie and Emily Ozer

We tap into our System 1– the fast, instinctive and emotional – part of the brain for more than 95% of our decisions. Our minds are constantly deploying shortcuts and hacks to get from point A to B with as little thinking as possible. When it comes to preferences in music, food, movies, or fashion, we tend to go with what is familiar and comfortable because it’s a fast and easy choice. We call this the familiarity heuristic – when the familiar is favored over novel places, people, or things.

But what happens when the new and surprising is favored as well?

Case in point: back in February 2017, System1 Research and Sklar Wilton collaborated on a study using Predictive Markets to predict the winners for The JUNO Awards that would take place in April 2017. These awards were created to celebrate and promote Canadian music and artists, the likes of which now hold international fame and familiarity more than ever – think Drake, The Weeknd, Grimes, Justin Bieber, Arcade Fire, etc.   

Just how well could a large crowd predict the winner for three major categories: (1) Artist of the Year, (2) Single of the Year, and (3) International Album of the Year? Bigger picture, would Canadians predict what was familiar to them or new and surprising?

Using System1’s Predictive Markets solution, we surveyed a large group of Canadians online (500 people per category) the month before the awards aired.    

How it worked was simple. The participants played a money betting game, where they were asked to imagine betting on the talent which would win that category. Let’s take Artist of the Year, for example, where the crowd had to bet up or down on Shawn Mendes, Drake, Alessia Cara, Leonard Cohen and The Weeknd. They identified a clear – and familiar – winner in each category: (1) Drake for Artist of the Year, (2) Shawn Mendes’ Treat You Better for Single of the Year, and (3) Coldplay’s Head Full of Dreams for International Album of the Year.

In awards chosen by juries, though, the familiar pick doesn’t always carry home the prize. So the study picked up on some new and surprising bets, too – The Strumbellas’ Spirits for Single of the Year (new) and Leonard Cohen for Artist of the Year (surprising). The Strumbellas only formed in 2008, getting their start playing in farmers’ markets around Toronto. The band had not experienced much international fame until the release of Spirits off their fourth studio album, Hope, which earned them a JUNO nod. The surprising bet was Leonard Cohen, who was a posthumous nominee with a career spanning nearly 50 years ending with the release of his 14th and final studio album You Want It Darker in October 2016.

The reactions to these two nominees got us thinking: Could a posthumous nominee and a scrappy indie folk band win over the likes of familiar and popular Drake and Shawn Mendes?

The awards aired on April 2, 2017, and we eagerly tuned in to see if our predictions lined up. Coldplay’s Head Full of Dreams took the prize for International Album of the Year, just like the crowd predicted. For Artist of the Year, Leonard Cohen’s legacy was enough to pull him above international superstar Drake, and Cohen was posthumously awarded Artist of the Year. And in the case of Single of the Year, up against hard hitters like The Weeknd and Shawn Mendes, scrappy indie folk band The Strumbellas pulled it off and won big for their hit single Spirits. In those categories, our pick for the new and surprising winner claimed victory.

Let’s dig a little deeper into why. The music of The Strumbellas gives people familiar feelings of uplift and joy, similar to the sentiments we heard from the crowd about established bands like Coldplay, but in a new, fresh, and youthful way. In the case of Cohen, his fifty-year career had helped him build great familiarity, and his death had brought him back into people’s minds, with an album themed around mortality providing an element of surprise and distinctiveness. So while The Strumbellas and Cohen both brought an element of familiarity to the table, it was their distinctiveness from other nominees that elevated them.  
In close, the three JUNO category winners were not only the most familiar but a blend of familiar and also new and surprising talent. And this tallies with what psychologists are finding out about innovation itself. As humans we have a “gut liking for the familiar”, so when something new and surprising is offered to us, it needs to be wrapped in familiarity. It’s what product designers call “Most Advanced Yet Acceptable” design, and what marketers call “Fluent Innovation” – making something new feel immediately familiar. According to System1 and Sklar Wilton, the sweet spot for this kind of success is 80% familiar, 20% new. Hit that target and your audience is more likely to accept the surprising novelty – and just as with The Strumbellas and Leonard Cohen, they may well choose it over more established options.

Automatically Write and Email Reports with R, SendGrid, & Displayr

Posted by Tim Ali Tuesday, September 26, 2017, 7:00 am
Get up to date with this week's edition of Data Visualization Best Practices with Tim Bock.

By Tim Bock

This post explains how to use R to automatically write and send emails based on automatically computed analyses (yep, everything automated). This means that when analysis changes or is updated, the email body text changes as well. The email can then be automatically sent to clients based on a trigger event (e.g., only when results are interesting) or periodically. All of this is can be done by using R code in Displayr, as illustrated in this post.

The tools: R, Displayr, and SendGrid

To automatically write and send email reports we need to have three tools:

  • A programming language. If the analysis is non-trivial, R is usually the best way forward.
  • An app that can automatically run the analyses at specified times. I’ve used Displayr. Of course, if you have the time you can avoid this commercial product and set up your own servers. (Disclaimer, I work for Displayr.) You can read this post to see how to get your data into Displayr and sign up to Displayr here if you do not already have an account.
  • An app to actually send the emails. I’ve chosen an email delivery application called SendGrid because R can work with its API.

Step 1: Set up the analysis to automatically update

The first step is to perform the analysis. Presumably, you want to set this up so that you have a live feed of data with the analysis updating automatically. See Automatically Updating Data and Dashboards in Displayr for more about this.

Step 2: Create a SendGrid account so you can send emails

Go to the Sendgrid account signup page to create your account. Enter a username, password and email address and select the 30-day free trial option which allows you to send up to 40,000 emails. Click the Create Account button and then complete the additional fields on the next page (your role, company size, etc.) to complete the account setup process.

sendgrid account setup

Step 3: Create a SendGrid API key

Once your SendGrid account has been set up, you can now create a SendGrid API key. The API key is a code that will enable your own R code to ask SendGrid to send emails. From your SendGrid account dashboard:

sendgrid settings

  1. Select Settings > API Keys
  2. Click the blue Create API Key button in the top right corner of your screen.
  3. On the Create API Key screen, enter an API Key Name (for example, Displayr_APIKey).
  4. Select the Full Access option.
  5. Click the Create & View button to generate and display the API Key.
  6. Click on the displayed API key to copy it.
  7. Paste the key into a text editor, and save it to a text file on your hard-drive for safe-keeping. Note that for security reasons, SendGrid will not display the API key again.automatically write and email reports

Step 4: Write the email body

The next step to automatically write and email reports is to write the email body. The message text for the email needs a string, stored in Displayr in an R Output. To create an R output, open Displayr and select Insert > Analysis > R Output. You then type in completely standard R code, referring to the data in your Displayr document.

In the rest of this post, I assume that the R Output that contains the email content is called body.

For example, a simple document may contain a set of NPS scores for different brands, like those shown in the table below.

Using R, I can pull out the highest and lowest results from the table (which in this case are for Google and IBM), and I can construct the following rather messy-looking piece of text:

If you sign in to Displayr you can look at the example code that I used to build this message from the table above.

It may look messy now, but when the email is created, the \n tags will be converted into line breaks, and it will produce an email that looks like this:

Automatically write and email reports

Additionally, you can include the URL of your published Displayr document in the message. To obtain the URL, first, export your document using Export > Web Page, and then copy and paste the URL of the resulting page.

Step 5: Generate the automated email by creating an R output in Displayr

Next, to generate the automated email, you will need to create an R Output in Displayr.

Add the following to the R CODE box which loads the R libraries needed to create and send the email.


The next line will determine how frequently to run the code and therefore send the email. This line ensures that the code is re-run every 24 hours and that the dashboard is automatically updated to show the latest results.

UpdateEvery(24, "hours", options = "snapshot")

Add the next line with your SendGrid the API Key entered in the quotes.

key1 = "your_api_key" #enter your API Key here

Specify the email parameters and construct the automated message

Next, the email parameters are specified and the email message is constructed. To do this, enter the recipient’s email address in the first line ( It is a good idea to first enter your own email address here so you can test if the script is working as expected. The sender’s email address is entered in the second line and can be any email address you choose ( You can also specify the email subject and message body here. In the previous step, I described how to automatically write the content of the body. Alternatively, you could replace body with a static message in the fourth line of code below (e.g., message.body= “Hello here.”).

11 = "" = ""
subject = "Testing Sendgrid on Displayr"
message.body = body
msg = sprintf('{\"personalizations\":
        [{\"to\": [{\"email\": \"%s\"}]}],
          \"from\": {\"email\": \"%s\"},
          \"subject\": \"%s",
          \"content\": [{\"type\": \"text/plain\",
          \"value\": \"%s\"}]}',,, subject, message.body)

The final bit of code is the actual SendGrid API call which sends the email.

Note, if you want to limit emails sends only to a specific trigger event, it is as simple as adding a plain-old if statement before this code.

        body = msg,
        config = add_headers("Authorization" = sprintf("Bearer %s", key1),
                        "Content-Type" = "application/json"),

Check the Automatic check box next to the  Calculate button to run the code. You should receive an email at the recipient email address you specified in the code.

Step 6: Customize formatting using HTML (Optional)  

You may want to apply some custom formatting to your emails rather than just sending them as plain text. To do this, you only need to change the content parameter line in the R code above from “text/plain” to “text/html”.

\"content\": [{\"type\": \"text/html\",

You can now use standard HTML formatting tags in your message body text. For example, you can replace the body variable above with the following to generate an HTML-styled email.

body = paste(“<p>Dear Tim,</p>”,
“<p>Here are the latest results from your NPS survey:</p>”,
“<ul><li>The highest NPS score this month was <strong>”, max.value, “</strong> for <strong>”, max.label, “</strong>.</li>”,
“<li>The lowest NPS score this month was <strong>”, min.value, “</strong> for <strong>”, min.label,”</strong></a>.</ul>”,
“<p>Click <a href=’′>here</a> for the full report.</p>”,
“<p>Kind regards,<br />Tim</p>”)

The following email will be generated.

r generate email html

You can find more information on basic HTML styling options at

How a Human Insights Approach Can Transform Routine Market Research

How do you find interesting insights? Change the focus from consumer insights to human insights and take into account life experiences and aspirational identity of the whole person.

By Jim White

I used to have a boss in the market research business who would ask, “How do you get interesting insights?” To which he’d provide the answer “Ask interesting questions!”

One way to guarantee interesting questions in market research is to stop pursuing Consumer Insights and start pursuing Human Insights.

In recent blog posts, we’ve argued that Human Insights have huge advantages over Consumer Insights. One reason is that a human perspective — one that takes into account the life experiences and aspirational identity of the whole person — allows you to ask more interesting questions.

But how does a Human Insights approach change how we go about the routine marketing research projects we do all the time?

Here are three types of routine insights projects that we do frequently and how the shift from a consumer perspective to a human perspective affects each.

Understanding Segments

From questions of consumption to questions of identity

We do a lot of work each year on segments. We conduct ethnographic and psychological deep dives to follow-up quantitative segmentation studies. Brand teams want to understand their segments on a “deeper level” so they can find “white space” for innovation and “core insights” to inspire messaging.

A Consumer Insights approach to these studies typically begins with a narrow focus on brands and consumption. Such projects explore people’s beliefs and attitudes about brands in the category and their shopping, purchase and brand usage behavior.

Such studies are limited from the outset because they start with a narrow focus on the consumer part of people, rather than a broad curiosity about what matters to the whole human being.

A Human Insights approach to segment analysis focuses on identity rather than consumption. A Human Insights approach to segments asks “Who do these people want to be?” Once we have a thorough understanding of this question, then (and only then) we ask, “How can our brand help them realize this aspirational identity?”

Human Insights tip: The next time you want to understand a segment, ask them to tell or write a story about two alternative futures for themselves — one positive and one negative. Then, after their stories are written, ask them to describe how your brand might help them achieve the positive future and avoid the negative one.

Optimizing Advertising/Packaging

From questions of evaluation to questions of association

Whether we like to admit it or not, people filter and deconstruct our ads and package designs and recreate them in their minds to serve their own purposes. If a creative message connects with someone, it is because they find it useful in helping them create their own personal story.

Most Consumer Insights approaches to creative development are evaluative. We often hear clients say they need to “test” creative, essentially asking “consumers” the question, “What do you think of this idea?” But this question doesn’t accurately represent how people process and use messaging. It also requires something of respondents they simply are not qualified to do (that is, evaluative advertising and design).

A Human Insights approach explores a profoundly different question. It asks, “What does this idea make you think of?” This is a question about the cognitive and emotional associations the idea evokes in people.

The difference between these two questions is immense. The latter question sends us on a journey to understand what, if anything, a creative message brings to mind from a person’s own life, experiences, memories and aspirations. People don’t care what the intended message of your advertising or packaging is. They only care how they can use it to help tell themselves a story about who they want to be. The creative messages that people want to incorporate into their own narrative identities is the message that is most relevant, meaningful and motivating.

Human Insights tip: The next time you’re doing qualitative research on advertising or package design, start by asking people, “What does this idea make you think of from your own life or experiences? What does it bring to mind for you? What memories does it trigger?” The ultimate measure of relevance is whether an ad or design connects with someone’s own life experience and aspirations in a meaningful way.

Decision Journey/Shopper Insights

From questions of transaction to questions of context

Many Decision Journey and Shopper Insights studies are intensely transactional. They focus like a laser beam on those thoughts, feelings and actions related to shopping and buying. In doing so, they often misrepresent the process as being more conscious and linear than it really is.

A Human Insights approach recognizes that real-life decision making is often messy, irrational, nonlinear and nonconscious. It asks “What is the broader life context in which this decision takes place?” It explores the pressures, distractions and emotions that shape how decisions are made in real life. It considers the ways people hope to transform themselves and their lives through the shopping experience. And it considers the myriad ways people simplify decision-making to deal with the complexities of daily life.

Human Insights tip. The next time you do Shop Alongs, meet the respondent at their home first. Spend some time getting to know them — who they are and who they want to be. Get to know a little about their daily life before you go shopping. You’ll begin to understand a bit more about the real-life context in which the shopping journey takes place and how that human being might hope to be transformed — even if only momentarily — by the experience.

So there you have it. Three types of routine market research projects and how a Human Insights approach can make them more interesting. Let me know what you think. And please, share with me the ways you’ve applied a human perspective to the insights work you do!

Dave McCaughan joins GreenBook as Strategic Advisor: Asia Pac

GreenBook is proud to announce that Dave McCaughan has been appointed to the role of Strategic Advisor, Asia Pac.



GreenBook, the premier platform for thought leadership and business connections in the marketing insights industry, is proud to announce that Dave McCaughan has been appointed to the role of Strategic Advisor, Asia Pac. In this role Dave will function in several important ways: as an ambassador for all GreenBook initiatives in the Asia Pacific region, as Chairman of the IIeX Asia Pac event, as a Regional Commenter for the GRIT report and as a member of the Global Advisory Council helping to define GreenBook’s evolving offerings for the global industry.

Lukas Pospichal, Managing Director of GreenBook, commented “Dave is a legend in the industry and one of the most influential thought leaders in the Asia Pacific region. There is no one better to help offer guidance on how GreenBook can best serve this all-important market and serve as an emissary as we develop the relationships needed to effectively help the industry grow there.”

Dave joins Ray Poynter as Strategic Advisor- Europe and Rafael Cespedes as Strategic Advisor – LatAm in similar roles and a growing list of Advisory Council members and global partners who work with GreenBook on bringing their leading platform to the world. Working closely with Leonard Murphy, Executive Editor of GreenBook this team is helping to redefine the industry for the 21st century.

Dave commented “I have been friends and collaborators with the GreenBook team for several years now and believe the platform they have built is an important part of the insights industry is Asia Pac. I’m thrilled to have the opportunity to play a more substantive role to help bring their vision to life here and on a global basis.”

Dave will be making his debut in his new role at the upcoming APRC conference and is already hard at work on working with the advisory council for the IIeX Asia Pac conference in Bangkok, Thailand in December.

About Dave McCaughan:

Currently based in Bangkok Dave has spent most of the last three decades in Asia Pacific leading strategy planning and in senior management roles with McCann, one of the world’s largest advertising and communication companies.

Dave joined McCann in 1986 in his native Sydney where he built the Strategic Planning function and subsequently since 1995 has been based in Bangkok, Hong Kong and Tokyo leading regional strategy and communication campaign development for clients including Coca-Cola , MasterCard, Nestle, Cathay Pacific, Sunstar, Hitachi, Johnson & Johnson and many others’.

Dave has talked at over 500 conferences globally and has been a regular columnist for journals like Advertising Age, Japan Close-Up, Research World. In 2016 he and co-host Kevin Gray began their audio podcast MR Realities.

In 2015 Dave initiated BIBLIOSEXUAL, a consultancy that brings together his long-term passion for understanding the interaction of people and media with brands and stories. He describes a bibliosexual as “someone who understands the relationship between form and content and that for different people one may be more relevant than the other”. In 2016 he joined as Chief Strategy Officer, a consultancy that works with SignificanceSystems and their machine learning platform to discover, explore and track narratives for brands and companies.


About GreenBook:

GreenBook connects marketers and market researchers with people, information, and ideas that generate results. Through research, events and training, blog, the talent marketplace and market research directory, GreenBook provides the learning and inspiration insights professionals need to succeed. GreenBook offers targeted marketing opportunities for providers of market research services. To learn more about how GreenBook can meet your insights and marketing needs, visit GreenBook Marketing Services online.

Personal Data: The Ultimate Commodity?

Personal data has been described as the “new oil” that will drive the economy of tomorrow, but it’s currently being treated as a commodity rather than a precious resource. We need to start developing models that both incentivize and reward individuals for contributing to the data economy — and here’s how. 



Recently, John Thornhill wrote an interesting article in the Financial Times on the role platforms like Facebook can play in establishing a universal basic income via data. Here is the crux of his argument:

“The most valuable asset that Facebook possesses is the data that its users, often unwittingly, hand over for free before they are in effect sold to advertisers. It seems only fair that Facebook makes a bigger social contribution for profiting from this massively valuable, collectively generated resource.

His shareholders would hate the idea. But from Facebook’s earliest years, Mr. Zuckerberg has said his purpose has been to make an impact rather than build a company. Besides, such a philanthropic gesture might even prove to be the marketing coup of the century. Facebook users could continue to swap cat pictures knowing that every click was contributing to a greater social good. “

In 2011 The World Economic Forum classified personal data as a new Asset Class along with property, investments, cash, etc. This laid the foundation to rethink how data can be utilized to deliver value to the owners and originators, not just the users. In the original report issued by WEF and Bain, they call out both the technical and philosophical challenge:

“At its core, personal data represents a post-industrial opportunity. It has unprecedented complexity, velocity and global reach. Utilizing a ubiquitous communications infrastructure, the personal data opportunity will emerge in a world where nearly everyone and everything are connected in real time. That will require a highly reliable, secure and available infrastructure at its core and robust innovation at the edge. Stakeholders will need to embrace the uncertainty, ambiguity and risk of an emerging ecosystem. In many ways, this opportunity will resemble a living entity and will require new ways of adapting and responding. Most importantly, it will demand a new way of thinking about individuals. Indeed, rethinking the central importance of the individual is fundamental to the transformational nature of this opportunity because that will spur solutions and insights.”

We have come far in developing the technologies that can enable the management of personal data in a trading environment. In fact, Blockchain shows great promise as the underlying architecture to power the trading of data as a type of cryptocurrency and is rapidly evolving as a transformative model for transactions. AI and “Big Data” models have largely addressed the type of analytical frameworks needed to combine data sources, and the marketing world advances in attribution, single-source, and programmatic ads have proven we have the systems to use personal data to deliver highly targeted content (in the form of ads and recommendations) in almost real time based on the digital treasure trove of data available.

However, and as John Thornhill pointed out, today consumers’ data is simply used without direct reward to the consumer. It’s a barter system: “let us use your data so we can try to sell you more stuff, and in return you get access to these nifty technology platforms.” That has been fine, but it’s a far cry from treating data as an asset class that can generate real financial gains for consumers — not just value.

What is missing is not just a shift in thinking, but also a fundamental reshaping of the value exchange. In short, we need to stop treating data as an easily accessible commodity and start paying for it as a precious resource. We need incentives and rewards to help kick-start a new system.

Fundamentally, people do things because they get something out of it: we take action because it fulfills a need, whether it’s conscious or unconscious. This core motivation is central to every school and application of behavioral science. Game Theory and Behavioral Economics specifically have taught us that a system of incentives and rewards are necessary to engage humans. In general, this system can be boiled down to a few key categories:

  1. Social: Connects us to others for fun and social interactions. Think of all the games on Facebook or online game networks.
  2. Financial: Delivers a direct financial reward such as research incentives, discount or deal networks, personal data lockers or recommendation systems.
  3. Values: Altruism, charitable causes, political or social campaigns and anything else that is aligned to our values.

The ideal system combines all of these. The market research industry has actually pioneered quite a few examples in action via the advent of online communities, and there is much from that model that could be applied throughout the research industry in support of a personal data economy. This system looks something like the example below:

  1. A brand wants to engage in a long-term dialogue with a subset of consumers to explore new product ideas.
  2. Participants are identified via profiles established in panels or in social media.
  3. Targeted consumers are recruited and paid a financial reward for engaging.
  4. Exercises are “gamified” and participants are sent on missions, earn badges/rewards and discuss their ideas and the ideas of others in forums within the community.
  5. Results are shared back so participants can see how their contributions help create new solutions to issues that impact their lives.

This approach to creating a real, engaging motivational framework for consumers to share their data is a good example of how we can rethink the value of personal data and how people can gain more than just access to apps for its use. That model of value-exchange is proven and has created value for all parties involved — but it has limitations.

A multi-dimensional system that has real incentives and rewards that pay consumers for their participation in an accretive way is not only more fair — it also drives the shift in necessary thinking to support the emergence of the personal data economy. Whether it’s getting a “data access annuity” from Facebook or Google, direct compensation for participating in research or data analysis initiatives or receiving goods and/or services as a “lease” on consumer data access, each model has incentives at their core.

No longer a tactical afterthought, consumer rewards are the tip of the spear in leading a transformation in how consumers use their data for their own benefit vs. others using it for personal gain. Direct reciprocity simply changes the game.

Incentives solution providers today are inherently “fintech” companies. My friends at Virtual Incentives for example use a robust enterprise API system to deliver real time, customized reward options from scores of partners through multiple consumer channels. They are a combination e-tailer, bank and stock exchange, processing millions of transactions at scale — all driven by consumer demand. That kind of technology is a vital key component of building the personal data economy, and the thought leaders behind it need to be part of the debate on what the future should look like.

The debate around personal data ownership and value, alternative and universal income schemes and the role of technology in making it all happen will continue to be important topics over the next few decades. However, incentives and rewards won’t just be a big part of that dialogue; they have already gone far in solving many practical issues.

Building on their firm foundations, the future of the personal data economy looks bright indeed.