We know how poorly the future has been predicted via traditional approaches.  David Cameron’s return in 2015 as Prime Minister of Great Britain was considered to be a surprise, as he easily picked up 328 House of Common Seats.  Brexit was considered to be a no-brainer that it would be turned down as an option, yet 51.9% of voters voted yes.  Donald Trump was dismissed by many as a candidate, yet he picked up 306 votes or 36 more than he needed.

The good news is that what happens in politics often represents the tip of the spear for innovation. So we ask “why” and before you know it, we innovate.  Here is what our panel explored today.

I focused on five key drivers of change:

#1 — Subconscious behavior is more important to measure in highly emotional/partisan issues.  We won’t tell the truth if you ask us in a highly emotional setting, but our actions will tell the truth.

#2 — The “non-behavior” e.g. silence, apathy or a decrease in intensity is often more important than what we say.  If an important constituency starts to decrease its intensity or perhaps go silent, this may be far more telling than what we are reading or what people are saying.

#3 — Narrowcasting is leading to overinterpretation of what real trends actually are.  We are increasingly getting our information from the sources that are most comfortable for us

#4 — Highly partisan and/or even fake news has a cumulative impact even if we think it does not.  Advertising models taught us long ago that frequency matters.

#5 — A new set of peers are emerging as influencers (the interpreters).  As the 9% in the 1,9,90 model matures into a media force, what they do and say is often far more powerful than any set of media outlets.

Rebecca Haller, who leads audience insight for Politico, informed us that Politico just created a new department dedicated to understanding our audience two weeks ago.  This team is is focusing on what they can learn from their readers, subscribers and event goers, who are also their sources and advertisers.

Rebecca also said that “we are combining the best of first and third party insights to understand our audience’s lives outside of the Politico ecosystem.  We are looking at more ethnograpic research and combining the best of pyschographics with our basic knowledge of our audience, all to provide a better experience”.

This is real innovation at a major media outlet and is one to pay attention to in the months and years ahead.

Mark Stouse, founder of Proof said that “analytics is hard enough….predictive is fraught with peril”. He went on to describe seven key learnings:

We don’t first understand the past and present
We know what we want and that drives bias
We trust ourselves when we should not
We assume consistency v. inconsistency
We don’t understand the role of time
We like pretty pictures too much
We like large speculation v. small certainty

Dr. Alexander Krasnikov, assistant professor of marketing for Loyola University in Chicago focused on the value of brands and made several interesting points, such as:

We need to conduct continuous segmentation in real time. Continuous being the key word.

If we do this well, we start to uncover the customer’s hidden needs and preferences.  We see early warning signs.  And with time, we can start to become predictive of responses likely to occur in specific scenarios.

Just as important, finding “alike” consumers does not imply correct segmentation

We are entering a time where our ability to innovate in data science and behavioral models has never been more important.

I’ll conclude with the key message overall.  Major change leads to breakthroughs.  Yes, its often fun, even therapeutic to discuss what happened, but it is much more productive to evolve and change how we do business as a result of what we are learning.

Here is one example of what we are doing to get a better view of what is actually happening in the market place.

We have realized that we will now build multi-dimensional algorithms so you can get the full and real perspective for any market, avoid false positives and see how trends or movements or apathy is really occurring.

Here is an example of how we are approaching it.

We are building a new “Trump algorithm” that has six dimensions.  The first is the “brand”, in this case Trump and all of his followers.  Second, we look at his appointees and surrogates (the army). Third, we look at Congress and staffers.  Fourth, a wide range of normative data sets (the real secret sauce) ranging from normative sets of 1MM people are more per channel who represent the “average” to NGOs for a specific issue to all African American pastors who discuss politics in public to key journalists and more.  The fifth is time and motion related.  What is the duration for successful momentum and when do you know that a new idea or protest is taking hold for real? And the sixth relates to sensitization and desensitization to a topic.  We often forget to look at the rates of burnout for things we are passionate about or fail to see an ember turning into a fire early enough.

The result is a new way to look at how an audience is truly being built, shaped or redefined.  Not surprisingly, it is important to point out that a single group often does not automatically impact the audiences that matter.  They might…..they might not….and that goes for any one group.  Said another way, just because any group is vocal on a topic doesn’t mean that will ever correlate with success. You still have to win the hearts and minds of the right people.  In that respect, nothing has changed….but our ability to understand the psychology of the market via technology and how it is shaping our world is becoming a top priority for brands, companies and anyone in the world of politics.

Thank you to our leaders on today’s panel. Best, Bob

We are witnessing a new style of media with the ascendancy of President Trump.  The simple way to describe his style of media is to say that he chooses to speak direct to the world via Twitter.  That’s true, but it sells short what is actually happening.

President Trump and his team understand the value of driving a narrative to shape our behaviors, whether it is pro or con.  Inherent in this approach is the ability to reach us emotionally, distract us and motivate us to action, depending on the circumstances.   As a result, it is not just that we have the first president who is using direct media.  We have the first president who will shape our thinking on a daily basis, as he pursues short, mid and long-term objectives.

What we know about ourselves, as individuals, and for communities and groups, overall, is that when our emotions are triggered, we are often thinking of what is short-term … in fact, only what is short-term.   This side-effect of thinking emotionally allows us to be distracted or misdirected by the way a story is told.  It’s a bit like a magician who gets us to concentrate on the wrong thing as they get ready to unveil a card.  You can do this now by going direct to the world via social media in ways never possible before via journalists.

And this is why we are building a new algorithm that provides a four-dimensional view of what is really going on.  Our data science team is using a combo of algorithmic and machine learning knowledge to create an approach that centers on key variables, such as how to analyze Trump’s following (his own, his appointees and his wider team), all members of Congress and key staffers, the media and other important audiences.  We compare this against normative data sets.  In the case of twitter, we’re talking about normative panels that are 1 million people or more and other normative data sets that give us a great insight into what is truly resonating.

The result is an approach that allows us to see what is a distraction vs. what is the Trump team is interested in truly pursuing vs. what is resonating with key target audiences.  As an example, we may now see that key target audiences deeply care about a topic President Trump is discussing, but it is not being pushed or discussed by the majority of his team.  Or his team is clearly pushing a certain message … we can see that federal and state officials are also interested in it, yet the general public is not.   There are many variations that can show us when a topic is truly gaining traction with the people who can either support or stop the momentum of an idea.  In other cases, we’ll be able to see quite quickly what is falling with a thud … not by examining the mainstream media … but by understanding what voters and those with influence to create or support legislation think.   Tracking the right people, knowing exactly who really drives influence and understanding how support is evolving, either way, will become increasingly obvious over time.

Inherent in this model is also a deep understanding of subconscious behavior.  Just looking at what everyone says or retweets is interesting, but insights become powerful when we look at the meaning of silence for certain groups or apathy and withdrawal from a topic.  It is equally important to look at the intensity of protagonism or antagonism to understand what is true passion that may move the needle and what is really just slacktivism or people kind of going through the motions.  Subconscious behavior and looking into psychological changes are keys in the algorithms we now build.

It’s interesting that new models like this will certainly include mainstream media, but they are not at all dependent on them to draw conclusions that will accurately inform companies of what reality is forming for their reputation or brand.  In fact, in many cases in the political arena, they are actually a false positive.  Whether it was this past election or BREXIT or other recent campaigns, this is borne out over and over again.

We’ll be sharing some of our initial work at the Holmes Report’s IN2 Summit in Chicago on Feb 16th.   And for our clients, we’ll be ready to ensure that every tweet or new idea is met with a system to judge its real impact, now or in the future, as it relates to their actual business objectives.

Best, Bob

We have seen many elections and referendums get it wrong in the last 18 months, whether it was the Brexit vote or this week’s U.S. Presidential election.   We are all wondering why.

There is a good reason why these polls are inaccurate and an even better reason to be optimistic about the future of polling.

A poll today often asks us questions that we answer via our short-term memory.  If we are lucky, we can remember an average of seven items per topic and that’s it.  We’re tapped out.  That’s not a problem when you are asked simple questions.

The bigger issue relates to how we effectively utilize big data to understand what is really happening inside our heads.

If a topic is safe and positive, we answer accurately.  However, if we are worried about how we will be judged or if we are filled with negative emotions, our judgement changes and we start to act differently.  Here are a few actions we take as a result.

We give the answer we think others want to hear, since we do not want to be judged negatively.  And that leads us into a new set of metrics for polling that will revolutionize how we measure an election or public opinion of any type. In a highly emotional and partisan situation, we’ll consider the following:

We will evaluate subconscious behavior.  For example, what are we searching for vs. what we are retweeting vs. which sites we visit.  We will start to see that the same group of people who are saying they will vote for candidate X are actually increasing their searches for topics that are more positive for candidate Y or they say they like candidate X, but never show their support online.   We will see the differences in what we say verbally vs. what we do when no one is watching.

We will measure passion.  As a result, “events” will be redefined as “moments where the voter can express their support”.  It could be a physical event like a rally or a photo you can like on Instagram or a video you can watch for five minutes or a speech that you reviewed and shared.  By looking closely at dozens and ultimately hundreds of “events”, we can see if passion is building or waning and then zero in on who, why, where and when.    We’ll be measuring every place an impact can be made or a sign of respect or disrespect can be shown.

We will measure silence.  Imagine having a normative data set of all voters for your party and you start to see that 500,000 of these potential voters have stopped participating in any form of support, yet they have shown support in prior elections or for other relevant political causes.  These may be silent voters who judge the price of being public as too high, but they will still vote.  We could also start to see if we are losing voters to another candidate, as well.

We will measure apathy.  If we look over the course of a campaign, where is interest non-existent or where has it decreased significantly?  What is happening that is causing an entire area of people to shift their views?  Why are less people in Detroit interested in candidate X over the last six months?  We’ll be able to see what is happening at the neighborhood level, which will impact our choice of content and location so we can regain interest in the candidate.

We will measure the importance of a key topic by town by influencer.  In today’s world, you can see which topic matters by town by candidate and which people have the most influence online.  So, if you are visiting a key city in Ohio, you know you should talk about manufacturing first and health second, you know who to invite to your event and you know what other towns in Ohio care about this exact topic.  You will know that 97 cities/towns matter for your candidate in Ohio and 130 in Texas and so on.  You won’t guess at all.   You will also know which towns and cities do not rate these topics as a priority, so you can streamline where you visit.  We can see this, of course, by analyzing what content people consume at the local level.

The list goes on.  The result will be a renaissance moment for polling.  We will have completely new pools of people to choose from to define where an election is heading.   We will understand better how to look at historical data and subconscious behavior and other data points to know what questions we need to ask, when to ask them and where to ask them.

The art of polling will increase in value as researchers, pollsters and those they serve learn how to look at all “data inflection points” and master the art of understanding the subconscious behavior of all of us, particularly in these highly partisan times.   Those who figure out how to leverage this influx of new data points will continue to find that “edge” in each election until this becomes standard business.


This article originally was published on O’Dwyer’s PR.

More times than we can recall, we’ve counseled clients on earned media strategy (e.g., which reporter and outlet should be approached with “the story” and why).

As sound as we believe our counsel has been over the years, it was based largely on previous experience and relationships. And while these are valuable considerations to be sure, we both knew — let’s be honest, all of us have always known — that these are highly subjective filters, particularly for business. In response, we’ve been developing a capability designed to find more data-driven, quantified answers to these and other questions facing tech CMOs and CCOs every day.

We started with a simple, relevant question: “What media do CIOs engage with the most?” What followed was three years of developing the necessary technology, talent and process to create the first in a series of technology “tribes” — nerd slang for databases that are focused on capturing and analyzing the online behaviors of specific audiences.

The more formal term for this is “audience-based analytics” and it’s a field that W2O Group has pioneered.

What started as a skunk works project is today a database of more than 20,000 IT Decision Makers, including thousands of CIOs. By capturing publicly available posts, shares and likes from ITDM handles across Twitter, Facebook, Instagram and other online sources we are able to amass statistically valid data sets across industry, title, geography.

We then use proprietary algorithms developed by our data scientists to understand not just media consumption, but trends related to topics, content, conferences, thought leaders, fellow ITDM behaviors and more. Our most recent analysis illustrates how this works.

ITDMs are very active in social media channels, but not always in ways a PR professional would expect. In our analysis of over 5.3 million social media posts from ITDMs over the past 12 months, over a third (35 percent) of the posts are actually about IT. This content covers many IT topics but is increasingly focused on IT security, especially new malware, hacker threats, and the various updates and patches required to keep these threats at bay.

Another 20 percent of their social media posts are about the “ITDM Lifestyle” that goes along with the considerable travel required of ITDMs at mid- to enterprise-sized companies. This content tends to be the most original and engaging to their peers and friends and is often written with the dry and sardonic wit stereotypical of IT professionals.

Popular themes here include the trials and tribulations of air travel, the food they eat while travelling for work and a range of nature and architecture photography taken while traveling. The latter two are of particular interest because they demonstrate something that seems obvious but is often overlooked when communicating with IT professionals: they are surrounded by technology all day every day. This is not how they want to spend their free time.

In many respects ITDMs engage with and produce social content typical of educated, professional, usually male audiences. They tend to discuss sports, politics, business news and, unsurprisingly, “Star Wars.” There are a few areas of interest that are especially unique to ITDMs, though, including the role of technology in higher education and space exploration. And — in case you were wondering — if ITDMs elected the next POTUS, her name would be Hillary.

Sometimes an audience’s dislikes are as informative as their likes. In the case of ITDMs, the big dislike is the types of inspirational quotes that are typical of LinkedIn newsfeeds (e.g., Steve Jobs’ mantra to “Stay Hungry. Stay Foolish.”). We found that ITDMs are less than half as likely to post an inspirational quote in one of their social feeds than the general population.

So, if you’re a community manager that’s responsible for producing content that’s relevant to ITDMs, we recommend that you avoid sharing these bite-sized universal wisdoms.

A good portion of your ITDM audience will find it cliché. Unless, of course, you are posting them with a deep sense of irony.

For all the advances in digital marketing, conference-base d marketing remains a large share of most tech CMOs budgets. But budget beware: Not all tech conferences are created equal in the Seth Duncan eyes of the almighty IT buyer.

Although Gartner’s IT Symposium continues to reign supreme, some may be surprised to learn that Microsoft Ignite isn’t too far behind VMworld and is actually ahead of Dreamforce, Cisco Live Rob Cronin and Oracle OpenWorld.

And how do you like that: we buried the lead! When it comes to media consumption trends, we tend to look at two data sets. The first uses link sharing as a proxy for what ITDMs are reading. The second analyzes who ITDMs are following compared to a normative sample. For the purposes of our analysis we remained topic-neutral.

So what pearls of wisdom can we offer? First, for all of the tech PR folks out there deciding between the Wall Street Journal and New York Times for your next exclusive, we would offer the following advice: you will reach roughly the same number of ITDMs, but the network effect will be far greater with The Gray Lady.

Second, ITDMs have an outsized appetite for Slashdot, NPR programs and The Onion. And finally, some of the many questions inspired by our data include: Have you embraced Medium as a platform? What’s your HBR strategy? How often are you engaging with the Washington Post?

Interested in learning more? We’d love to chat

sethduncanThis article was co-authored by W2O Group’s Chief Analytics Officer, Seth Duncan. His analytics and research expertise span advanced statistics, social, digital and web analytics, as well as traditional media and primary research. He has extensive experience applying these analytics approaches to a broad set of use-cases, including product development and design, branding, creative/content execution, messaging, social and web optimization, as well as influencer and media relations. 


California voters will decide tomorrow the fate of a drug price control initiative, ending a contentious and expensive campaign that, according to the latest poll, has the state evenly split. At issue is whether to require that pharmaceutical prices for state programs such as Medi-Cal and the state’s prison system be the same as what the Veterans Administration pays. The initiative’s actual impact on overall drug prices is unclear, according to a nonpartisan legislative analysis, but for both supporters and opponents it is likely to be a measurement of just how upset voters are about pharmaceutical prices and whether the industry can convince them that price controls are the wrong way to go. As is typical in California – consultant Bob Shrum once said that in the state “a campaign rally is three people around a television set” – the campaign is being fought out mostly on the television airwaves.


The “Yes” campaign is backed by AIDS Healthcare Foundation chief Michael Weinstein and has the support of Democratic Sen. Bernie Sanders of Vermont, whose failed presidential campaign energized much of the left-leaning primary electorate in California. The California Nurses Association is the most prominent healthcare-oriented group to back the measure, though it also has the support of other high-profile progressive activists. The lead consultant is Garry South, a prominent political adviser who helped engineer Gray Davis’ 1998 gubernatorial win. The campaign focuses its message not on the initiative’s pricing details but on attacking the pharmaceutical industry – its website features unflattering photos of pharma CEOs in FBI-like “Wanted” posters.

The “No” campaign is, unsurprisingly, backed by the pharmaceutical industry, but many medical groups in the state, including the California Medical Association and the California Pharmacists Association, also oppose the measure. Veterans groups, who have expressed concern that the measure might actually lead to increased costs for prescriptions at the VA, are also lined up with the “No” campaign. Television ads against the initiative have featured doctors and veterans.


Much of the coverage about the initiative – in the state as well nationally – has focused on the money pharma companies have put into the campaign to defeat it. Sanders did receive significant coverage for his endorsement of the initiative and his recent visit to the state, but otherwise, much of the coverage focuses either on the politics of the campaign or the television advertisements.


California’s major newspaper editorial boards, despite their varying ideological views, are united against Prop 61. Many cite the unknown consequences of the measure’s passage.


A new public poll released last Friday showed a virtual deadlock for the ballot initiative, with 47 percent saying they would vote for the initiative, 47 percent against and 6 percent undecided. That’s a change from earlier polls, even from earlier last week, when a different public poll showed 51 percent backing Prop 61. In August and September, public polls showed much stronger support for the measure, but those came before the onslaught of commercials, videos and direct mail pieces


The topic of Proposition 61 came up on this week’s earnings calls for at least two manufacturers, Merck and Eli Lilly.

Ken Frazier, Merck

I will say, as an overall comment, we have very serious concerns about this measure and its potential impact on patients. And that’s why we’re part of a growing coalition of groups that are actively opposing that ballot measure in California, because we think it will negatively impact millions of California patients.

John Lechleiter, Eli Lilly

Prop 61, we’re fighting that tooth-and-nail in California. It’s not only bad legislation, it’s bad for your health. And we’re trying to impress that on the voters. What we’ve found is that the more people become aware of what’s at stake here and what’s the likely outcomes of Proposition 61, the more they’re prone to vote against it and vote it down.


If drug prices are the number one health issue in the election (see Kaiser poll below in “Pricing Politics” section), and California is the no. 1 battleground for drug pricing legislation, it would stand to reason that Proposition 61 has galvanized California doctors, right?

Not quite. We queried our proprietary MDigitalLife system, looking at verified doctors with Twitter accounts, to see the extent of the conversation. The volume was underwhelming: just 160 tweets about Prop 61 from docs in the past 90 days. And only eight physicians who practice in California have tweeted on the topic.

But physicians are hardly politically disengaged. For context, Donald Trump turns up in 190,000 tweets over the same time period, and Hillary Clinton figured in 111,000 tweets from physicians. And, for the record, @HillaryClinton is getting more retweets from doctors than @realDonaldTrump: 3,000 to 1,400.

Why these engaged physicians are disengaged about the year’s most prominent drug pricing battle isn’t clear. The issue is complex for 140 characters. Also, many who are sympathetic to price regulation have said the initiative is the wrong way to go (see editorials above.) Or it could be, in a presidential contest with the madcap pacing of a Benny Hill episode, physicians have simply been too distracted by bad hombres, nasty women, and baskets of deplorables to focus on down-ballot measures.


It is not news that social media has changed every arena and industry since its genesis, from social justice movements to healthcare to television; the sport’s world is no exception. Social media, specifically Twitter, has transformed how fans and foes communicate with one another and with their teams. The social media giant essentially serves as a virtual sports’ bar for fans and rivals alike to brag, argue, boo, or cheer despite location.

You are not a fan of the call the ref made? Complain with your fellow fans.

Did your favorite player have an excellent game? Brag with your fellow fans.

Did your team dominate in the season opener? Let the world know about it.

Are you ready for your team’s season to get started? Sing your rally cry in 140 characters.

Did your team break a curse that lasted 108 years? Fly the W with the fellow Chicago faithful.

This phenomena of a virtual sports’ bar was showcased through the pinnacle of America’s favorite pastime, the 2016 World Series between the Chicago Cubs and the Cleveland Indians. Specifically, how Cubs’ fans discussed being cursed on Twitter throughout the post season.

The Curse of the Billy Goat and the Chicago Cubs

Even if you are not a die-hard baseball fan, odds are you are aware that the Cubs playing the World Series is historic at minimum and a dream come true to many of the Chicago faithful. Since 1945 many fans have believed that their beloved Cubbies were cursed by tavern owner, William “Billy Goat” Sianis. Sianis attempted to bring along his pet goat, Murphy, to game four of the 1945 World Series. The pair was not admitted because of Murphy’s smell which angered Sianis greatly. It is reported he professed, “The Cubs ain’t gonna win no more.” The Cubs lost that World Series and instantly The Curse of the Billy Goat was born.


The Curse was nearly broken in 2003, which fans refer to as the “Bartman game”. The Cubs were up 3-0 and just five outs away from their first World Series appearance in nearly 60 years. A foul ball was hit that fell over the wall in the left field, Cubs’ left fielder Moises Alou went to make the grab to close out the inning, but a fan (Steve Bartman) reached for the ball as well, knocking it out of play. Following this play the Cubs gave up five runs that inning, losing the game and ultimately losing the National League Championship Series. The curse lived on.

Curse Conversation on Twitter

Twitter was not around during the lion share of the Curse of the Billy Goat, it certainly was not around in 1945 and still had not gotten off the ground for the Bartman game in 2003. Can you imagine if an entity existed where any fan, rival, spectator, coach or reporter could gather in one space to discuss the magnitude and heartbreak of the curse?

Thanks to the creation Twitter and our analytics team we do not have to.

Our analyst listened to how frequently the words/phrases: curse, cursed, curse of the Billy goat, Billy Goat, Steve Bartman or Bartman were mentioned along with the Cubs throughout the postseason (October 7, 2016 – November 3, 2016).  Check out our findings below:


The Importance of Knowing Your Audience

Twitter has not only eliminated the guessing game in the sports’ world but in a plethora of industries. The platform has created virtual physician offices, virtual presidential debate watch parties, and virtual discussion groups on topics ranging from latest software update to the latest museum openings. Brands, companies and people are no longer guessing what the people they care about are talking about and how they are behaving online. At W2O Group we define this as audience architecture. The combination of technological advancements, analytics expertise and a need to improve outdated models is leading to a new way to identify, architect and then learn from the specific audiences you care about.

In short, it is key to know what audience segments are saying about themselves, but also what their online behavior is saying about the types of stories that will have the most impact on them, whether it is discovering a product or celebrating the end of 108 year old curse, people are talking on social media and it is key for brands and companies to listen.

Jon Carillo HeadshotCreative for this project was provided by Jon Carrillo, a graphic designer at W2O Group. Connect with him on LinkedIn and if you don’t mind the occasional rant about the San Antonio Spurs, follow him on Twitter at @JonnyCTweets


aaeaaqaaaaaaaasraaaajdhlngrlmtrjltnhnzgtndc2zs1izwfjltm1mjc0ztlkyjcxnwAnalytics for this project were provided by Madison Reineke. Madison is a junior analyst at W2O Group where she focuses on deriving data-driven insights for a wide breadth of clients. She is a recent graduate of The University of Texas at Austin and majored in Advertising Management. Feel free to connect with her on LinkedIn.

For the past few weeks, we’ve been exploring the complexities of using analytics to answer strategic business questions. In an evolving digital environment where an abundance of data can actually complicate things, rather than clarify them, we’ve given you a look at how W2O Group approaches honing the right tools, skills and thinking to cut through all the clutter. We’d like to close out this three-part series by delving into a key differentiator, the analysts.

We’ve said it before. We’ll say it again. The quality of findings and insights are all about the people conducting and guiding the analysis. And since we don’t focus on one single type of analytics at W2O, analysts need a broad range of capabilities and expertise in order to ensure insights gleaned from data are actionable for clients. They need to extensively understand public relations and communications, how data feeds and informs them, the business context and industry of each client, and the abundance of potentially viable tools to use.

This style of analysis isn’t exactly a major concentration of study at a university. So how do we select, onboard and develop our people in order to sustain the consistency and quality we’ve incubated over the years?


It’s about teaching judgment. After recruiting analysts with diverse backgrounds across research, communications and business, the objective in W2O training and ongoing learning is aligning the team around a way of thinking and balancing forensic and exploratory approaches.

That’s done by focusing on the client first, and teaching analysts to operationalize key research frameworks with a core curriculum grounded in these key areas:

  • Client/Industry Background: What are the tactics and strategies that clients can deploy in order to meet their responsibilities? What exactly do those responsibilities look like? And what broader business context does the team need to know?
  • Tools: Some tools allow the team to export a large sample of data. Some are better applied to some channels over others. What tools does the analyst need to know operationally? How do they think critically about how (or if) they should be applied, given the question being asked? How do they practice evaluating new and existing tools on an ongoing basis?
  • Measurement Frameworks: How do you design and activate a measurement framework? Specifically, how is it shaped from the overarching business objectives, the client’s objectives and resulting research objectives? How are the research questions shaped?
  • Visualization/storytelling: Analysts must think critically about the format and narrative when formalizing their insights. What are the differences in showing your data in a table or chart? How do you create and visualize a network map? What’s the story arc that needs to be conveyed?


In such a fast-moving industry, knowledge management becomes increasingly important. At W2O we house all these courses and supporting materials (like cases) in a wiki-based platform. It allows the team to tweak and adjust, and also prompts debate and discussion around what approaches, tools and frameworks work best.

It’s all in an effort to keep teams pushing the needle and continually re-assessing new ways to come to the most actionable, relevant insights possible for clients. When it comes down to it, analytics today is as much an art as a science, but we’re excited about keeping a healthy mix of both with whatever is next in a space that keeps allowing us to be smarter and make better-informed business decisions.


If you’re struggling to make sense of the reams of data coming your way, or how to figure out what business objectives the right data efforts can help you reach, we’d love to hear from you. Reach out to us, we’d be happy to talk. If you have an insatiable curiosity and love to play with data, you’ve piqued our interest! Check out positions we have available.

This blog series was authored was by Meriel McCaffery, Corporate & Strategy Senior Manager and Abigail Rethore, Corporate & Strategy Group Director. It was made in Los Angeles, Austin, New York, and London with experience and insight from our colleagues Lucas Galan, Head of Analytics Productization; Meredith Owen, Analytics Director; Kelley Sternhagen, Analytics Director; and Paul Dyer, President of Analytics and Insights. Connect with them to learn more!


In last week’s Art of Analytics post we talked about how an increase in data is not necessarily leading to an influx in useful information for businesses. This week we invite you to take a closer look into W2O Group’s use of analytics and what we can’t wait to offer clients soon.

 Deciphering Behaviors

What hasn’t changed over the past seven years?

Our commitment to ensuring data isn’t being used for data’s sake. Analytics needs to be tied to business objectives. Asking how a project gives us information to improve business results, strengthen relationships and influence stakeholder actions keeps us focused.

Our approach. Four guiding principles and questions consistently drive our work as the field of analytics diversifies:

  1. Clarity is key. What are we looking to answer? What are we solving for and why does it matter? How will that objective improve relationships with clients’ employees, partners and customers, and drive desired behaviors?
  2. Be agnostic. What is the combination of data (e.g. digital, traditional, government, etc.) that will be most beneficial for the objective? What data is most useful and relevant versus nice to have?
  3. Be inquisitive. What can we do to be proactively searching for an original, perhaps unexplored approach? How can we push beyond our initial thinking to stretch possibility into emerging strategies and tools?
  4. Be discerning. How can we ground exploration of interesting insights and information in the realism of the market and what is most actionable for the client? What’s the simple, human conclusion? What do we need to remember specifically about the client to guide our selection of data?

 Today’s interests. We work to help client-partners identify opportunities to grow the business through their role in the enterprise (such as, Communications, Marketing, Sales, Consumer Insights, and Human Resources). This often involves:

  • Identifying people who have influence and are vocal in spaces that clients and their key stakeholders operate in; monitoring and engaging them as part of a long-term strategy
  • Determining perception and sentiment around a client organization and what product or service they offer
  • Mapping and monitoring key conversations and topics relevant to the spaces clients want to enter and/or grow their share of voice in, specific topics of interest (such as Crisis), and the key audiences clients want to connect with


Analytics in Action (an example). W2O Group colleagues recently completed a project for a leading pharmaceutical subsidiary that focuses on dermatological treatments. How could they better market one of their acne medications to their primary – often overgeneralized – demographic, teenagers? The team used social data to model real-world teenager behavior and drew corresponding insights. It revealed distinct personas, each with very different preferences and triggers. With deeper insight into this core demographic, the Client more specifically marketed to each of them, in personalized ways that closely spoke to the current reality they face (vs. historic ones).

Tomorrow’s needs. Working with client-partners, we continue to see that there is interest and need in improvement in three primary areas:

  1. Combining traditional data with government data and digital data – The converged movement can be bigger and better. It’s no longer enough to look at one form of research in a vacuum. Collectively looking at information that’s been available for years and overlaying it with digital analytics, for example, is only going to grow and improve.
  2. Visualization (or storytelling) of data beyond charts and graphs – There are great tools emerging that can be used to help make data significantly more human and digestible. More work can be done to tell clear, simple stories with data, that anyone and everyone can understand easily.
  3. Predictive analytics – We’re most jazzed about increasing clients’ ability to see and act on trends sooner – to help them get ahead of the curve so they can better serve and add value to their stakeholders. It’s not quite telling the future, but it’s close enough that we’re excited to get ahead of what’s next.


We are fast at work addressing all three of these future needs in the space and can’t wait to continue to bring them to our client-partners.

As companies become even more digital and clearly technology-informed, we will continue to have more opportunities to explore on- and off-line interactions to help us get smarter about stakeholder perceptions (re: products, services, brands and companies) and their behaviors. It puts us in a confident position to build and manage relationships with them in authentic, mutually beneficial ways.

In our next Art of Analytics post, we’ll look at how we’re building the best team of analysts in the business to ensure quality and to perpetuate ingenuity.

This blog series was authored was by Meriel McCaffery, Corporate & Strategy Senior Manager and Abigail Rethore, Corporate & Strategy Group Director. It was made in Los Angeles, Austin, New York, and London with experience and insight from our colleagues Lucas Galan, Head of Analytics Productization; Meredith Owen, Analytics Director; Kelley Sternhagen, Analytics Director; and Paul Dyer, President of Analytics and Insights. Connect with them to learn more!


How is it that data can generate different answers to the same strategic business question? How can we be confident in the findings we gather and insights we glean if there can be such variation in the outcomes? Isn’t the beauty of data its objectivity?

Assorted business analytics have become both the cornerstone and the future of business decision-making, generating incredible opportunity. At the same time, data doesn’t seem to be making business decisions easier (more astute) for many companies. In many cases, it’s actually making business decisions more convoluted.

Over the next three weeks we’ll explore the use of business analytics – including Sales, Marketing and Communications data – to answer these questions and more. We’ll also provide a deeper look into W2O Group’s approach to analytics, how we think, what we do and how we do it, which helps us deliver the most actionable and relevant solutions for our clients.

First up….

Data (Alone) is Not the Answer

We all know that there is more data available now than ever before, ushering in what Alan Murray calls a “new era of business enlightenment.” At the same time, McKinsey reported last year that only one percent of data is turned into useful information. What’s causing the disconnect? Why isn’t more actionable insight a result of having more data that’s more easily accessible?

For us, the answer can be found in understanding and appreciating data for what it is (and isn’t). In the broadest sense, data is a resource and tool. It helps us get to the answer, or the best course of action given a variety of variables. As our title indicates, it’s not (unfortunately) the solution itself. Being a tool, it’s only as effective as the person using it – specifically as strong as his/her:

  • Clarity around the objective
  • Understanding of business and research context
  • Ability to identify the right type(s) of data to speak to what’s driving the inquiry

The Objective. No meaningful analysis comes from broad, unfocused exploration. We must be clear on what we’re looking for and open-minded to learning something new, and unexpected. Have a hypothesis. Have focus on what we want to learn about. Understand how learning about that topic will help us take next steps. If it doesn’t, omit it. It will only distract.

Sample objectives: How are our customers interacting with our brand online? Who is our next generation of customers? What are their interests? Are we relevant to our consumers in China the same way we are in England?

The Context. This includes anything that impacts why our objective is important – the urgency and business imperatives. It can be product challenges, opportunities, competitors, policies/regulations, economic health, customer demand, and the list goes on and on. It also considers where “the ask” is coming from internally; Marketing’s interests in customer segmentation, for example, will be different from Communications’ or Operations.’ Understood before analysis kicks-off, context validates the question we’re asking and our objective. Context applied after data is collected gives us insight behind our numbers – why they might be the way they are.

Sample context: Employees expressed frustration in June and July. That’s when we reorganized business units. In August, frustrations lowered AND referrals increased. The open-forums we conducted and manager trainings we implemented seem to be making a positive impact on employee perceptions.

The Right Data. Just because data is available, doesn’t mean it will help us answer our objective. Good analytics is about customized research design that gathers only the information that will help us answer our question. Similarly, it’s also about looking beyond one type of data source and integrating information from a variety of relevant data points as determined by our objective. Identifying the right data reinforces why data is only as good as the people leading the analysis – our understanding of the objective, context and information needed to make sense of and explore a situation.

Sample data: Web analytics, social, search, and traditional market research

As Intel’s Chuck Hemann reminded us at SXSW last Spring, it’s the people leading the analysis who make all the difference in a world of ever-maturing data, technology and automation software. The skill and strategic thinking of these people help explain why (and how) the same data sets can produce different results. Data is not black and white; it’s not purely objective. It is a piece of problem solving that requires an innately curious team of people with tremendous customer, cultural and business acumen. Next week, we’ll take a deeper look at what our team is doing with clients to help them solve their most pressing business questions

This blog series was authored was by Meriel McCaffery, Corporate & Strategy Senior Manager and Abigail Rethore, Corporate & Strategy Group Director. It was made in Los Angeles, Austin, New York, and London with experience and insight from our colleagues Lucas Galan, Head of Analytics Productization; Meredith Owen, Analytics Director; Kelley Sternhagen, Analytics Director; and Paul Dyer, President of Analytics and Insights. Connect with them to learn more!