Tag Archives: Marketing

The Ruthless Efficiency of Algorithms is Advancing Digital Frontiers

We recently caught up with Alistair Croll, Visiting
Executive at Harvard Business School as well as our Marketing Analytics &
Data Science Conference keynote speaker, to discuss the state of marketing
analytics and data science, and where it’s going in the future.
Today, Croll helps to accelerate startups, and works with
some of the world’s biggest companies on business model innovation. As an
entrepreneur, he co-founded Coradiant; the Year One Labs accelerator; and a many
other startups. Not to mention, he’s a sought-after speaker, and has launched
and chaired some of the world’s leading conferences on emerging technology,
including Startupfest, Strata, Cloud Connect, and Pandemon.io. Croll is also the
author of four books on technology and entrepreneurship, including the
best-selling Lean Analytics, which has been translated into eight languages.
What is the state of
the data science and analytics industry in 2017?

Croll: There is a realization that data itself doesn’t lead
to answers. This is really maturity: It’s asking the right question that’s
hard. Big data is replacing business intelligence, but most of it is still
being used to run reports and batch processes’rather than to find advantage or
insight.
At the same time, feeding the corpus of data into learning
algorithms holds promise. Those with the authority to do so are pointing
machine learning at their data seta to find correlations, then testing those
for causal relationships they can exploit.
What have been the
biggest changes data science and analytics since you started your career?

Croll: I’m not an analyst by trade. But the biggest change
is clear: once, we first defined the schema, then collected data. Now, we
collect the data, then define the schema.
In other words, “Collect first, ask questions
later.” This is a huge difference, but it has sort of snuck up on us. It
means we can iterate more, answering questions and adjusting our lines of
inquiry.
Have the influx of
social media and mobile made your job easier or harder?

Croll: More data sets mean more potential insights, but also
more spurious correlations. So it’s a two-edged sword.
How is data science
and analytics transforming every industry right now?

Croll: The simple, and somewhat terrifying, truth is that AI
gets unreasonably powerful, very quickly. Whether driving a car, or playing a
video game, or diagnosing a disease, or optimizing the design of an aircraft
part, algorithms are better than humans. They don’t get tired; they make fewer
mistakes; they don’t take breaks.
And what do we feed such algorithms? Data. There is no
industry that will not be changed by the ruthless efficiency of algorithms
advancing its digital frontiers.
Why is data science considered
the ‘sexiest job of the 21st century’?

Croll: Data science is the intersection of statistics,
critical thinking, and engineering. It requires a sense of narrative, and the
ability to build something. It’s that element of engineering that distinguishes
it from simple analytics, because it builds things that become products, or
processes. Rather than running a report, it improves the report’s results.
If big data is oil, data science is the refinery that makes
it usable.
What is the biggest
challenge in data science and analytics today?

Croll: We are still, sadly, trying to replace opinions with
facts. My good friend Randy Smerik argues that there’s no such thing as big
data: An airline that knows you’re running late fails to update your hotel;
false positives about in credit card management.
His point is that while we have tremendous amounts of data,
we seldom apply them to significantly improve the business or the customer
experience because doing so means making fundamental changes to the organization,
job descriptions, customer policies, and so on.
Where do you see data
science and analytics moving in the next 5 years?

Croll: Democratization, with the help of smart agents.
Pundits have been saying that for a long time, but in the last couple of years
tools like Cortana, Google Now, Siri, and Alexa’as well as various chat
interfaces like Slack, Sophos, and Skype’are going mainstream.
I also think that insurers will put significant pressure on
companies to implement better analytics and algorithms because it will be too
risky to do otherwise. If the organization can know everything about itself all
the time, it will be expected to do so. “We didn’t know this was
happening” will no longer be an excuse. And consequently, algorithms that
can parse all of that data and reduce risk will be mandatory.
Hear more from
Alistair during his keynote session, ‘Don’t’ Get Duped by Data’ at the
Marketing Analytics & Data Science Conference April 3-5, 2017 in San
Francisco, CA.

Data science and marketing analytics are transforming every
industry. There is a reason why it is being called the sexiest job of the 21st
century. Calling all professionals that want to harness analytics and data
science! Do you realize how critical you are to the future of your organization?
Learn more here: https://goo.gl/CbYosj

Use our exclusive
Blog discount code MADS17BL for $100 off the current rate. Buy your tickets
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Marketers and the Future of DMP Insights

By: Hannah Chapple
Advertisers, agencies, and publishers are swimming in data.
They have so many data points, from a variety of sources, that they are simply
overwhelmed by it all. Website (cookie data), social data, CRM data, you name
it, and they’ve likely got it. Sorting all of this data from various (often
siloed) sources, in a timely and efficient manner is a near impossible human
task.
We all know that the role of a marketer is to reach the
right consumer, at the right time, with the right message. But to do this
effectively, marketers are challenged with interpreting their mass amounts
of data and uncovering actionable insight, at speed and scale.
Interpreting mass
amounts of data is no easy feat.
As the demand for digital marketing and
programmatic/real-time ad buying rises, marketers face more pressure than ever
to target audiences faster, and with laser-precise, data-driven insights. We
know that consumers will only respond to the messages that speak to their
interests, passions, wants, and needs. And in the world of real-time bidding,
technologies only have milliseconds to get that messaging right. And guess
what? These messages cannot be crafted with broad categorization methods like
demographics alone. Demographics as a stand alone are limiting and tell you
nothing about what an individual is interested in, passionate about, or value.
To fill this gap, we have seen marketers seek more and more
data resources. That’s why we see marketers not only trying to make sense of
their first-party data but also second party data (from partners) and purchased
third-party data. Can you understand why marketers are swimming in data? It’s
a vicious cycle. So again, we arrive at our original problem: how can
marketers turn mass amounts of data into actionable insight, at speed and scale?
Are DMP’s the magic
solution in the advertising ecosystem?
To better target potential consumers, many advertisers rely
on Data Management Platforms (DMP’s) to collect their mass amounts of disparate
audience data (including the first, second, and third-party data we spoke
about) and interpret it. In short, DMP’s are cloud-based warehouses used to
generate an audience segment(s) based on patterns and trends set within defined
parameters. The goal, of course, is to deliver high-quality, accurate audience
segments to marketers, and all other players in the advertising ecosystem, like
DSP’s. When placed into action, these audience segments (generated by the DMP)
should result in smarter optimized ads, efficient media spend, and less ad
waste. But is this actually the case?
Marketers are sitting on a wealth of data, with a goldmine
of potential insights to derive from that data. That’s why more and more
companies are investing in DMP’s for their business and are hiring
highly-qualified, expensive professionals to manage them. However, while DMP’s
are used to extract insights, there is still a lot of wasted potential in these
tools.
Here’s a quick DMP lesson: DMP’s operate on a ‘hypothesis’
basis. DMP users must set conditions or a query to break down the data sources
and form a specific audience segment they want. For a DMP to work properly
(with speed and accuracy) and know what data to segment or pair, a DMP user
must understand many factors including media, marketing, analytics and of
course data. The DMP will then do its best to match data and form an actionable
audience segment for the marketer to leverage.
For example, a marketer could leverage behavioural cookie
data to build an audience of males in Nova Scotia, over 30 who browsed a car
website on their mobile device. This audience can then be used for ad-buying,
media placement, etc. 
But marketers don’t
know, what they don’t know.
But what does this marketer really know about this audience?
What are their interests and passions, outside of cars, and how can they be
determined? This is why, despite the integration of DMP’s, marketers still
aren’t getting it right. While automated, there is still a human error in how
DMP’s select which data to process and interpret.
Don’t get me wrong; there is incredible value in DMP’s but
there is also an incredible opportunity present. Ultimately, the goal of
leveraging a DMP is to provide a personalized consumer experience by relating
to their interests and behaviours. But marketers are only grasping at the data
that they are currently able to understand. Like I said, DMP’s operate on a
hypothesis basis, contingent on the user’s understanding of the data.
We, as marketers, haven’t even scraped the surface of what
is possible with DMP data. Marketers need a solution that looks beyond
predetermined hypothesis and attributes. Instead, we need a solution that
interprets unsupervised data and can discover the hidden relations and insights
within audiences that marketers don’t yet know.
How do you foresee 2017 shaping up? How will DMP’s evolve?
Share what you think down below: [Read
more on the Affinio blog]

About the Author: Hannah
Chapple is the Marketing & Content Coordinator at Affinio, the marketing
intelligence platform. Hannah holds a Bachelor of Business Administration with
a major in Marketing from the F.C. Manning School of Business at Acadia
University. 

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#MADSConf

Consumer Behavior, DIY, Omnichannel and Millennials

By: Keri Hodnik and
Liz Williams, Euromonitor International

This article was
originally published on Euromonitor
International
The Market Research Event, TMRE, is an annual conference
that seeks to unite both clients and vendors, positioning itself as the only
event in the world with twice as many client side participants than any other
industry event of its kind. This year, it was held in Boca Raton, Florida, and
covered a wide range of topics, including: People; Tools, Tech, and
Methodology; Innovation, Macro Trends; Customer; Omni-Shopper, B2B /
Health&Wellness; and Partnerships. TMRE hosts a broad array of speakers,
from CEOs of Fortune 500 Companies to Neuroscientists that seek to decode the
mind of the consumer.
The theme of the entire event was ‘Command the Boardroom’,
which focused on how to bring the eyes and ears of the consumer into the
boardroom itself. The presence of the Consumer Insights function is not only
needed to energise the boardroom on the importance of the ever changing
consumer, but it is crucial in representing the big ideas that drive business
growth.
With that theme setting the stage for the event, the
following four trends emerged from the speakers:
CONSUMER
BEHAVIOUR                                                                    
                 
Better understanding the inner workings of the consumer was
a common theme at this year’s TMRE Conference. Zoe Chance, Author of ‘Better
Influence’ and Assistant Professor of Marketing at Yale School of Management,
led a keynote on Mastering Influence & Persuasion.
Chance was driven to leave the world of corporate marketing
to understand behavioral economics after observing a repeating trend: companies
often put a lot of time, money and energy into using data for business
decisions, but in the end, would use their guts anyway. Why is that?
Chance went on to explain the difference between System 1
and System 2 decision making. These are better known as the unconscious and
conscious mind, or as she called them: ‘Alligator Brain’ and ‘The Court’. The
unconscious mind is fast, it’s intuitive and it’s automatic. On the other hand,
the conscious mind is slow, deliberate and effortful. Most of us believe that
we’re making decisions with The Court, but Alligator Brain kicks in far more
often than we care to realise.
Rather than trying to ineffectively engage consumers’
conscious mind, Chance suggests that instead we should be working to peak the
Alligator Brain with her 5 key forces of influence:
  • Labelling: giving a name to the behaviour that you wish to
    encourage or discourage.
  • Ease: ‘Alligators are lazy’; companies like Uber, Tinder and
    Amazon are great examples of how to make it as easy as possible for consumers
    to take action.
  • Attention: creating open loops, or Moments of Truth (as
    coined by P&G), both stimulate curiosity since we as consumers have an
    insatiable want to close the loop.
  • Scarcity: loss aversion is a powerful motivator and can be
    roused by communications such as limited time, limited quantity and
    exclusivity.
  • ‘Hot Potato’: when forced with resistance, give it back as a
    problem to solve. If someone says they’re not interested, instead try asking:
    ‘You’re not interested’? as a way to promote deliberate decision making.

The subject of the conscious versus unconscious mind was
revisited again by David Eagleman: Neuroscientist, Author of ‘Incognito: the
Secret Lives of the Brain’ and Host of PBS’ ‘The Brain with David Eagleman’.
In his talk on ‘Emotion, Motivation, and Reputation’, he
explained that there is an enormous gap between what your brain is doing and
what your conscious mind is actually thinking. ‘Everything about your cognition
is happening incognito,’ Eagleman said. The implication of the unconscious
brain being the core driver of decision making is that asking consumers
questions about their decision making process is irrelevant.
Neuroscience can tell us a lot about the driving forces
behind the consumer path to purchase. Eagleman explained that there are three
networks in the brain: one for price point, one for pleasure and one for how
the decision itself is viewed:
  • Valuation: everything is judged in context. Saving $10 on a
    pair of headphones has a higher consumer response than saving $10 on an iPhone,
    despite the benefit being equal. We as consumers do not actually know what we
    want until we see it in context.
  • Emotion: despite our want to believe we are rational and
    unbiased, our actions prove otherwise. For instance, did you know that humans
    make harsher decisions if in a fowl smelling room?
  • Social: Eagleman explained that ‘people are wired to
    understand companies the same way they understand people. Breaches of trust
    travel fast and are un-erasable.’

DO-IT-YOURSELF RESEARCH
DIY Research was a key theme for one of the tracks at the
event, focusing on how and when to ‘be scrappy’ with research. DIY research is
a cost effective alternative to outsourcing solutions that allows you to
analyse research results in real time. As Andrea Stokes, the Senior Director of
Consumer Insights at Marriott International, said in her session titled, ‘Cheap
and Cheerful DIY Research’, it’s important to know when it makes sense to
pursue DIY research and also when it makes sense not to:
5 reasons to go DIY:
1.      
When you need it fast
2.      
When you have an easily accessible customer
database
3.      
When the question is not a $20,000+ question
4.      
When a question can be answered by consumer
feedback alone, meaning that advanced analytics and modelling are not required
5.      
When you have only 60 minutes of your
stakeholders’ time
5 reasons not to go DIY:
1.      
When the ask is complex
2.      
When more than one translation is needed
3.      
When data will help to defend or prevent a large
investment
4.      
When the CEO needs to make a business case to
the Board of Directors
5.      
When research is needed for crisis management
Some of the tools that Stokes suggests to aid in DIY
research are software, such as survey software and an insight community
platform through which to conduct your research. Mobile devices like iPads and
smartphones make data collection fast and easy, while tools such as excel or
other data visualization programs like Tableau are essential for storytelling.
Last, all that is needed is you (and maybe a videographer to capture the
process).
MILLENNIALS AND THE
FUTURE OF RETAIL

Any Channel, Anytime, Anywhere: Today’s consumer is very
busy with little downtime, always on the go, always carrying their phones and
always connected to the internet. Consumers are looking for a more convenient
and seamless way to shop given their busy lifestyles. Many businesses realize
this and are changing to fit consumer’s needs by providing seamless easier ways
to shop. Several examples include:
??        
Sephora Flash ‘ Sephora’s new stores that allow
consumers to purchase an item online or through the app and pick up in store
the following days
??        
Charity Wait ‘ an app that allows consumers to
donate to a charity in order to skip a line at their favourite restaurant
??        
Shyp ‘ an app that allows consumers to ship out
postal packages without having to visit the USPS store. The consumer arranges a
time for pick-up and Shyp will pick up the box and send it to the nearby post
office.
??        
Task Rabbit ‘ an app that offers a personal
assistant to complete your tasks that you have to do throughout the day, making
your day more efficient
Customized Products: Even though consumers are on the go,
they are still making specific decisions on what they are purchasing. Consumers
are looking for more personalisation and customisation in their lives and they
want it to be easy.
Ugg has made it easier for consumers to try on shoes by
providing them with an interactive floor mat that allows them to picture what
the shoe would look like on
Break Free of Demographics: Consumers want to break free of
demographics. They are looking for more of a new wholesome look which basically
means retailers should start positioning products as being non-gender.
OMNICHANNEL

Many large tech gurus such as Facebook even have a difficult
time capturing all types of consumer market research data. Companies like
Facebook capture any shopper data on mobile phones and desk top data but are
not able to see what is happening outside of their own space. Facebook
expresses that it is important to capture all channels of shopper insights to
understand the full data set for the ever changing consumer.
Facebook has found that through their internal data numbers,
consumers tend to have a purchasing pattern per omnichannel. Many consumer turn
to mobile to shop for categories that are less expensive, perhaps because it
doesn’t take much thought or commitment to purchase these items that might be
used every day. However, consumers tend to turn to their desktop for categories
that are more expensive which may be due to internet connection worry or being
able to see the product on a larger screen.

What Facebook is unaware of through internal data is
in-store shopping habits. This type of data may help companies like Facebook
understand what brand elements trigger market behaviour, what is going to drive
consumers to make purchases in store, what the importance of labels play when
shopping in different channels and how can they measure behaviour of a shopper
on each channel.

#MediaInsights Day 3 Recap

Day 3 started with co-chair Bruce Friend recapping Day 2,
then introducing today’s first keynote speaker.
KEYNOTE 1 – MONEYBALL:
THE ART OF WINNING AN UNFAIR GAME

Paul Depodesta, CSO of Cleveland Browns,
engaged the audience with an overview that there’s a certain way that things
work.  Whether baseball, black jack, or
other situations in life, there’s always that ‘rule of thumb’ that we are
taught to follow.  However, sometimes the
‘rule’ doesn’t always work.  It’s all
about the process. Paul described a process/outcome quad:

??        
Good process/ Good outcome =
success
??        
Good process/ Bad outcome
= just unlucky
??        
Bad process/
Good outcome = get lucky once, but then rely on that luck to be successful
again
??        
Bad process/
Bad outcome = recipe for failure 

So, how do you
win with a lack of resources? 

Putting together a championship team is like cooking a
gourmet meal – you need the right ingredients. We’re always asking the naive questions- why is the market
down, why is this player struggling? We need a reason, but there not always is
a reason, so we try to explain by creating our own cause and relationships.
As with The
Oakland A’s in Moneyball, sometimes we need to throw out the old metrics, that
‘rule of thumb’ and start new.  Key
takeaways he learned from testing these new metrics were:         
??        
Find skillful
affordable talent to replace high priced starts
??        
Statistics can
be misleading
He drew
comparisons of scouting baseball players to testing programs.  Emotions drive our decisions, and we tend to
look for data to support and confirm these decisions, while dismissing any data
that contradicts what we believe.

Paul left us
with these 3 points: 
??        
become aware
of biases
??        
become
relentless in asking the naive question
??        
in the game of
uncertainty, how can we beat the house? Learn by previous failures to better
hit success.
KEYNOTE 2 – INSIGHTS
FROM THE 2016 ELECTION

The late morning keynote was actually broken
into 3 parts.  Robin Garfield of CNN
spoke first, and then we heard Dr. John Lapinski from NBC News, followed by a
Q&A with our 2 speakers.

Millennials told us they wanted a candidate who has a plan
to:
?? 
Create good paying jobs
?? 
Make healthcare more affordable

Millennials also told us they didn’t want a candidate who:
?? 
Represents ‘more of the same’
They were looking for a transformational candidate – someone
who will ‘change the government’, and that they were ‘done with the Clintons
and Bushes.’
Most Millennials liked Bernie Sanders, and both
Trump and Clinton were viewed negatively.

Not only was 2016 the most watched year on record in cable
news (with over 3 million total P2+ aggregate audience), but more people came
out to vote in 2016 than ever before.
??        
2000 ‘ 105.4
million total turnout (54.2% of eligible population that voted)
??        
2004 ‘ 122.3 million
(60.1%)
??        
2008 ‘ 131.3
million (61.6%)
??        
2012 ‘ 129,1
million (58.6%)
??        
2016 ‘ 136.6
million (59.0%)
We were show examples of ‘what-if’ scenarios, that
demonstrated how close the election really was.
While Clinton’s popular vote lead was just shy of 3 million
(65.8 million for Clinton compared to 63.0 million for Trump), the red/blue map
showed that the majority of Clinton’s popular vote came from New York and
California.  And the 2016 Electoral
College hinged on a handful of states, with Trump taking Florida and the Rust
Belt states (Iowa, Michigan, Ohio, Pennsylvania and Wisconsin).

KEYNOTE PANEL – CROSS PLATFORM MEASUREMENT AND THE FUTURE
OF MEDIA
                 
Jane Clark, from the Coalition for Innovative Media
Measurement, moderated this panel which included:
Jed Meyer (Univision), Jonathan Steuer (Omnicom),
Carol Hinnant (comScore), Steven Schmitt
(TiVo) and Kelly Abcarian (Nielsen).
The panel gave us a perspective of the industry from the
network, agency, and measurement side.  They
addressed the integrity of data and optimizing tools for better plans.  They talked about how there’s a constant
struggle trying to bring all measurement across all platforms together.
Kelly stressed how measurement needs to be a team sport.  Media companies are more and more starting to
own their own data, and that changes the dynamic of the industry.
There is a call from the network and agency side for duration
weighted viewable impressions across all platforms, and the measurement
companies just aren’t there yet.  The
question remains ‘ how do we get there?
The Day 3
afternoon Audience Insights breakouts were:
?? 
MULTICULTURAL
TV AUDIENCES ON TWITTER
‘ Meghann Elrhoul, Twitter
?? 
FULL SPECTRUM:
ILLUMINATING THE CONTENT PREFERENCES OF MULTICULTURAL AUDIENCE
‘ Thomas
Grayman, SpikeTV
The Innovations
in Media
breakouts were:
?? 
USING TRENDING
DATA TO UNCOVER THE WHITE SPACE
‘ Rob McLoughlin, POPSUGAR
Below are the Track 1 – Targeting Viewers case
studies:
QUANTIFYING
CROSS-PLATFORM ADVERTISING IMPACT IN LATIN AMERICA

ESPN’s David Hobbie gave us insight to David’s study focused on an advertising
campaign during this past year’s Olympics in Rio, and the impact and brand lift
experienced on ESPN Latin America.
THE STORY OF
KIDS MEDIA
The last case study track of the conference had Theresa
Pepe of Viacom give us an in depth look at kids’ data and… The
Story of Me.
We learned about kids under 11 and how they are the most
diverse kids ever. They make up 15.4% of the US population, and are extremely
persuasive. 
Theresa showed us a breakdown of these kids
focusing on:
??        
My beginning
??        
My world
??        
My family
??        
Myself
??        
My friends
??        
My tech
??        
My dreams
??        
Me in a nutshell. 

Since they were born these kids experienced: 
- The
first Black president 
- Terrorism
- Marriage equality 
- Great recession 
- YouTubers 
- On demand 
- Social Media 
- Device overload 
- Gender neutrality 

Their role models are their families’ and some
celebrities.  While 78% of girls look up
to mom, on 58% of boys look up to dad. 
26% said the look up to a grandparent, while the rest of their role
models included YouTube/Vine stars (19%), teacher (18%), brother (17%), sister
(15%), aunt/uncle/cousin (13%), actor/actress (10%), athlete (10%).
And they are busy!  6.2
hours of the day they are in school, while the rest of their day entails
sleeping (8.7 hours), eating/traveling (1.7 hours), organized sports/activities
(.9 hours), doing homework (.8 hours), and 6.4 hours going towards leisure (26%
of their day.)
In their free time, they watch TV (48%), play with toys
(43%), play video games (33%), and play outside (18%).
CONFERENCE
WRAP-UP

The Conference concluded with a wrap-up with the year’s
co-chairs and the advisory panel giving their feedback of the sessions,
discussing plans for next year’s conference, and taking questions from the
audience.

#MediaInsights Day 2 Recap

After co-chair Rob McLoughlin gave a recap for Day 1 and a
look at what to expect for Day 2, Amber Case, author of Design for the Next
Generation of Devices, presented our first keynote: 

MULTIDIMENSIONAL MEDIA
& THE FUTURE OF ENGAGEMENT

Here, we got a comical look at connected devices and how the average
consumer has become dependent on them. She gave us a look at products like
PetNet, and how the Web and technology play a major role in self-development.

Day 2′s second keynote DIGITAL HUMANISM: THE COMING AGE
OF CONTENT
featured Edwin Wong of Buzzfeed and his insights on Recoding
Culture.  We got a look at Millennials
and how culture is being reshaped and where it’s headed.
76% of Gen Y say “it’s the norm to be radical” (as
opposed to 60% of Gen X).
Buzzfeed measured 4 millennial groups: Omegas, Sigmas, Cult
Kids, and Nichesters and the strong overlaps between these groups.
Wong stressed how we’re moving towards the end of
demographics, evolution of psycographics and the rise of the individual.
Tobin Trevarthen of 21st Century Narrative and author of
Narrative Generation was our next keynote speaker – BEYOND THE STORY: WHY
YOU NEED A NARRATIVE
.
Tobin covered:
??        
what is a narrative
??        
why you need a narrative
??        
story vs. Narrative
??        
building a narrative
A narrative differs from a story. More directly, a narrative
is a mosaic of related, contextual stories that inform and define one’s
perspective.
A story has a beginning, a middle and an end.  A story has a plot, and acts as a one-way
monologue.
A narrative is endless, and has a more interactive dialogue.
Tobin showed how Tesla automotive expanded the brand
narrative to reach consumers.
Our last keynote of the morning had Mainak Mazumdar, CRO of
Nielsen, speak of ADDRESSING TRUST AND TRANSPARENCY WITH BIG DATA IN TV
MEASUREMENT
.
Recently data sets had errors and inaccuracies in station
crediting, time shifted content and missing live viewing.  Mainak addressed 2 key questions:
??        
what is our “ground truth?
??        
how do we understand and correct for biases?
Nielsen used RPD data along with 200,000+ high quality
person’s panel to address methodology challenges.
The first of Day 2′s Track 1 case studies (Targeting
Viewers)
was CHANNEL ME, presented by Jason Shalaveyus from
Starcom and Nicole Tramontano from Turner. 
Despite the industry pendulum swing away from engaged reach
towards efficiency and programmatic buying in recent years, Starcom and Turner
set out to determine:
??        
Relative importance of contextual factors
??        
Range of impact
??        
Net effect
??        
Prevalence of optimal contexts among segments
Top findings included:
??        
easy wins where you have high control over
highly influential factors are hard to come by
??        
content has a stable shelf life, but ads spoil
quickly
??        
relevance is important
Armida Ascano and Gil Haddi from Trend Hunter presented our
next Targeting Viewers case study 
GEN Z: DIVING INTO THE YOUTH GENERATION.
Trend Hunter is helping clients find the stories that
connect them to Gen Z (infants to 17) – what defines them and what they mean to
Media.  They are not as big as
Millennials, but they are just as important. 
By 2020, Gen Z will be 40% of the consumer base.
Gen Z is the most diverse generation, and they are underrepresented
in the mainstream media. As a result, they:
??        
turn to influencers who look and speak like them
??        
already have the tools, creativity and desire to
create, but do not enjoy passive media consumption
??        
are swapping in aspiration for realism
As content providers, we need to choose influencers and messaging
with this in mind.
A nearly packed room showed up to see Melanie Schneider
(AMC) and Stephanie Yates (WE) present their case study VIEWER CHOICE:
PRIMETIME ALL OF THE TIME.
TV viewership has shown downward declines over the past 5
years.  However, content is up more than
ever.  How are we able to watch all this
content?  Technology has propelled viewer
choice.
AMC Networks did a study focusing on content, taking a
deeper dive into Nielsen respondent level data exploring viewers, their habits,
and how they watch content.
Our last Targeting Viewers case study for Day 2 was THE
OTT CONUNDRUM: USING PSYCHOGRAPHICS TO UNDERSTAND CROSS-PLATFORM VIDEO
CONSUMPTION
 
presented by Tamara Barber from Simmons Research.
Video consumption is not just linear and live anymore.  Simmons looked at comprehensive video
measurement across linear, SVOD, OTT and other connected devices.
OTT users are psychographically different. The Top 10 OTT
user attributes included:
??        
more digital
??        
more social media
While the Top 10 attributes for non-OTT users included:
??        
use cell phone for calling only
??        
read newspaper daily 

Simmons is hoping to use psychographics to optimize Media
planning and buying.

Diverse Demographics: Breaking Stereotypes

Millennials are the most diverse generation
in history ‘ only 59% are Caucasian and 27% have an immigrant background (Deloitte, 2015). Therefore, it’s no surprise that this
demographic expects brands to embrace and reflect the diversity of their lives
‘ a trend previously highlighted by Stylus Life in our report No
normal: Post-diversity marketing
. If brands are to do this successfully, they
must move beyond crude stereotyping to represent a broad spectrum of race,
gender and sexuality.
For instance, Muslim millennials offer
growing opportunities for brands
‘ the Muslim consumer lifestyle market is
predicted to reach $2.6tn by 2020. The modern yet faith-driven outlook of this
group, along with a growing disposable income, will see them buy into brands
that reflect or understand their values. Make-up brand CoverGirl is already
tapping into this lucrative demographic with its latest brand ambassador ‘beauty
blogger and hijab wearer Nura Afia
. One of a growing number of Muslim
beauty bloggers, her new role demonstrates the importance and appeal of diverse
representation.

Beauty brands are working particularly hard
to cater to often forgotten demographics. A new initiative from L’Oreal
offers free step-by-step audio tutorials
to give visually impaired women
more independence. The usability has been carefully considered to fit the needs
of this consumer group ‘ the cosmetic and skincare tutorials are concise to fit
into everyday habits, while the app’s customisable user interface features a
monochrome palette and large text.
Also targeting a currently under-catered
market, UnBeweavable
Hair
is an on-demand hair service specifically for women of colour.
On-demand beauty services, which provide a stylist straight to your home or
workplace, have been rising in popularity for some time now ‘ yet UnBeweavable
Hair is the first tailored to the specific needs of this demographic.

Created by Zina Alfa, it was inspired by her own difficulties in finding
hairdressers who understood her needs. Made by a woman of colour for other
women of colour, this case study shows that if brands want to provide products and
services that appeal to all, they must improve the diversity of their
workforce.

Rebecca Minkoff recently highlighted the
need for diverse workforces, citing the lack
of female employees in technology companies
(and STEM fields in general) as
a key reason why wearables are not currently capturing female consumers. The
fashion designer also mentions examples of having to explain female
expectations and behaviours ‘ such as taking jewellery off at night ‘ that were
missed by an all-male team.
There’s a popular saying promoting better
gender and race representation that suggests ‘you cannot be what you cannot
see’ ‘ but this could easily be extended to ‘you cannot create for audiences
you don’t represent and understand’. Which is why companies with diverse workforces
are more likely to financially outperform those that are not (McKinsey,
2015). So if you want to ensure your products appeal to an increasingly diverse
consumer landscape, you’d better start with your job adverts.

Brought to you by Stylus Life, creativity and innovation news
from around the web.

Stop Listening, Start Watching. How Interest-Based Segmentation Gets to the Heart of Consumers

By: Hannah Chapple
In recent years, we’ve seen companies increase their
reliance on social data. Why? Today there are more social signals than ever.
Consumers are sharing comments, their interests, thoughts, and more online. The
result being an incredible amount of consumer-provided data at our fingertips.
The problem facing marketers is trying to make sense of the
deep end of social data. One way we’ve seen businesses and big brands try to
make sense of this data is by investing in a little something called social listening.
If we watch and listen to what consumers are saying in real-time, we’ll paint a
more accurate picture of them, right? Wrong.
Social listening is biased. Many times our online persona is
different than who we are or doesn’t show us in our entirety. And only a small
percentage of those online ever actually engage or vocalize their thoughts,
interests, and beliefs ‘ the consumer insights that companies crave.
I’ll use myself as an example. If you comb through my social
feeds (and please, don’t feel you have to) you’ll find my comments and a flurry
of articles shared on all things marketing. While I am interested in this
stuff, yes (it’s my profession after all), it is not the complete picture of
who Hannah is as a person.
So how do we get to
the heart of the consumer?
One way companies can figure out who their consumers are and
what they want is by leveraging interest-based segmentation.
Interest-based segmentation is when individuals are
clustered and segmented into naturally-occurring, unbiased clusters, by looking
at who or what they choose to follow. Instead of focusing on the vocal
minority, at Affinio we consider
following patterns and interest data to be paramount to listening or
traditional research methods. 

 Image: Interest-based
clusters generated by Affinio
Following and connecting with other people is a fundamental
property of social behaviour. It is also a silent action, whereas social biases
might keep individuals from being honest about their interests (who they
follow) or what they talk about in person. The takeaway: you wouldn’t know
everything that I’m interested in just by looking at what I say, but you would
understand my interests by looking at who I follow.
By focusing on how an audience is connected (analyzing their
shared interests and affinities), interest-based segmentation gets to the very
heart of the consumer. Instantly, companies can identify who and what their
audience cares about, even if they’ve never vocalized it. Or if they have, this
method validates that finding. This approach places focus on the honest
relationships consumers have built and maintained and lets marketers understand
their audience as human beings and not one-dimensional data points.

About the Author: Hannah
Chapple is the Marketing & Content Coordinator at Affinio, the marketing
intelligence platform. Hannah holds a Bachelor of Business Administration with
a major in Marketing from the F.C. Manning School of Business at Acadia
University. 

Selling on Emotion: Why Show Ratings and Demographics No Longer Tell the Whole Story

By Jared Feldman, Founder & CEO of Canvs



An earlier version of this article appeared in AdAge.



With upfront season just around the corner, early signs are that brands, finally, are again buying more of what networks are selling.

That’s great news for the networks, after over three straight years of declines in upfront ad-time purchases (and two years of plateaued spending before that). But as the buying season kicks off, let me suggest that brands should pay attention to some new factors this year as they lock in deals.

In the past, in making decisions about where to spend their ad dollars, buyers had only ratings and some demographic data about existing shows, plus a first peek at new ones coming in the fall. What I’d like to propose is that buyers not use, or just use, those same old methods this time around.

Oh sure, keep the ratings and demos you’re used to working with. Nielsen’s work continues to have value and it’s evolving to embrace the new TV realities.

But show ratings and audience demographics by themselves no longer tell ad buyers everything they need to know in the new universe of “TV” we now live in. The TV audience is shifting, and in lots of directions at once. With it, the business is shifting, too.

Audiences are watching TV in more ways and on more platforms than ever, and at different times and in different settings. Just as importantly, audiences are talking about the shows they’re watching, on more social media and chat and other online platforms than ever.

And when fans are talking about these shows, sharing important moments, creating content about the shows, and reacting to that, they’re also evoking and expressing a whole raft of feelings and attachments about favorite programs.

The savviest programmers realize this. They’re building shows that connect with and captivate dedicated, niche audiences who care deeply about that show. They’re sharing compelling behind-the-scenes content, live tweeting with fans, and creating other experiences that will hook and engage the superfans who care most about a program.

And those shows and networks are exactly where advertisers should be. Those fans will be a show’s best ambassadors. And the research says they’ll also be the best ambassadors for brands advertising around that show.

The shows that stir emotional reactions are the ones that also will stir reactions and buying impulses for the ads of those shows. As they say in the business, that is gold. So it’s important to figure out which companies are doing a good job reaching and holding those audiences your brand cares about most.

For instance, the two networks whose shows most often evoke the emotion “addicting” on Twitter were MTV and Freeform (then known as ABC Family), according to a Canvs analysis of tweets captured by Nielsen.

It shouldn’t be a complete surprise — both networks target millennials, who are tech-savvy and sharing-mad. They share everything they care about, including some of their favorite shows on those two networks.

“Addictive” programming isn’t the only thing buyers should look for. For instance, what networks and shows do fans find consistently “funny?” A laughing fan is one predisposed to like the brands connected to those shows.

And though the industry may not be quite ready for it, let me propose another thing. Networks and show runners will become increasingly skilled at creating compelling niche programming for ardent superfan audiences. They’re also going to get better at using the new measures of success and building to it.

At some point, as creators improve, and as brands integrate what this means for their bottom line, we’ll have new network milestones for ad sales. Expect networks to begin guaranteeing more than just ratings.

Providing a minimum level of emotional reactions that can help drive advertising success will become important. And when a show doesn’t drive that emotional response, a network will have to figure out how to make good on its promise.

By that point, the entire industry will know how much emotion matters in making a show, and its advertising, succeed. And then we’ll really see the full power and value of advertising in the new TV universe.

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