Tag Archives: data

Free Webinar: Data Analytics in the Retail Store of the Future

Marketing Analytics & Data Science speaker Dave
Bhattacharjee, VP of Data Analytics for Stanley Black and Decker, was
unfortunately unable to be at the conference last month, but he still wanted to
share his presentation with our community digitally.
In Dave’s upcoming webinar ‘Data
Analytics in the Retail Store of the Future
‘, he will outline the
challenges for brick and mortar retailers and their use of analytics to improve
their business and create the retail store of the future. Brick and mortar
retailers are going through a period of unprecedented change. To remain
competitive, retailers are focused on omni-channel and the use of the retail
store as a competitive advantage for both customer experience and order
fulfillment. The focus for this presentation will be the innovative use of
sensor and video technology, machine learning and the use of blended data to
improve customer lifetime value, marketing analytics, sales lift and margin
optimization.  
Dave will cover topics such as data acquisition and store
instrumentation leveraging the internet of things. He will discuss advances in
video analytics that enable retailers to better understand customer engagement,
experience and behavior. And, he will also discuss the use of blending
unstructured data to enable retailers to better assess promotions and their
impact on sales and margins.
Save your seat for
the webinar on Wednesday, May 31st at 2:00 PM EST: http://bit.ly/2p11Lye
About the Presenter:

Dave Bhattacharjee is the Vice President of Data Analytics
for Stanley Black and Decker. In this role, Dave is responsible for monetizing
Stanley Black and Decker’s data assets. His current projects include analytics
applications for physical security, retail, healthcare, smart factory and
marketing.    
Prior to Stanley Black and Decker, Dave was at Cisco Systems
where as Managing Director, Dave managed and led Cisco’s consulting services
for analytics and big data in the Americas. He has also held leadership
positions at IBM and PriceWaterhouseCoopers where Dave worked with the Fortune
500 on large scale initiatives designed to create business value through data
and technology. He has an MBA from the University of Texas at Austin and a
Bachelors in Computer Science and Engineering from Arizona State University.
  
Cheers,
The Marketing Analytics & Data Science Team

Study Compares Recall Versus In-the-Moment Surveys

This post was originally published on mfour’s Blog.

If you want to know what consumers buy, you’d better not
hesitate to ask. Because if you don’t ask fast enough, your data will fall into
a recall gap ‘ the chasm that opens when you rely on days-old (or weeks-old)
memories instead of capturing consumer sentiment when the experience is fresh
in mind. 
That’s the takeaway from a comparative study MFour conducted
to explore how memory decay impacts data reliability. The results underscore
how using GPS-enabled technology lets you reach the right consumers in the
right place at the right time for insights that can truly drive the right
business decisions. 
The study involved fielding essentially the same mobile
survey to two demographically similar groups of 200 consumers. GeoLocation told
us that our first group had been shopping that very day in at least one of the
five retailer categories in the study ‘ grocery stores, convenience stores,
drug stores, membership club stores, and mass merchants. 
These panelists were identified inside specific stores and
received in-app push notifications just as they walked out the door to learn
about their shopping experiences. The non-GeoLocated control group was asked
about most recent shopping experiences in the same store types ‘ which may have
occurred days, weeks, or even months earlier. 
Key Findings

??        
When asked to state whether they had purchased
products in any of eight general categories (beverages, personal care, etc.)
during their most recent store visit, all 200 GeoLocated respondents named one
or more categories. Not one of them selected the ‘Don’t know/Can’t remember’
option.
??        
That contrasts with 28% of the non-GeoLocated
control group who said they could not remember which product categories they’d
purchased during their most recent store visit.
??        
There were also significant gaps when it came to
recalling the brands our respondents had bought. The GeoLocated group had a
brand recall advantage for 13 of 16 specific product types.
??        
Notable brand recall gaps include differences of
23.8% for facial cleansers, 14.1% for juices, 13.4% for feminine hygiene
products, 12.3% for shampoos/conditioners, and 10.1% for snack chips.
Conclusion 

Talking to consumers when an experience is fresh in mind is
crucial for obtaining accurate data about any kind of experience. Exploiting
GeoLocation and other key smartphone features takes you as close to the moment
of purchasing truth as you can get without tagging along in person. This is why
a Point of Emotion?? response, capturing data the moment when information is at
its most memorable, is the most reliable way to understand what consumers
really think. 
To learn more about how to keep your research from falling into the
recall gap, just reach out by clicking sales@mfour.com.
And be sure to check the MFour blog throughout the week for more insights from
this study.

Introducing the TMRE On Demand Webinar Series!

Introducing the TMRE On Demand Webinar
Series!

TMRE ON DEMAND
As insights leaders, we are
constantly tasked with evolving our skill sets and staying on top of the latest
MR trends.
The producers of TMRE: The Market
Research event are excited to announce that we’ll be delivering the
cutting-edge content and speakers to keep you informed year-round. The TMRE
webinar series takes you beyond the in-person event, and is designed for executives
with a relentless focus on securing the future of insights as a powerful force
for business success. Each quarter, the TMRE Webinar series delivers a 3-part
webinar experience designed to empower insights executives with the latest
information around hot topics to ensure insights drives bottom line impact.
Schedule of WEBINARS:
STORYTELLING WITH DATA
Wednesday, May 24, 2017 ‘ 2:00 ‘ 3:30 PM EST
Driving the
value of insights forward requires much more than just unearthing great data.
You need to use that data to tell a story and command influence across the
broader organization. Because storytelling may not be an inherent skill, this
3-part webinar focuses on how to use data to create an engaging, informative, compelling story. 
               
THE NEED FOR SPEED: BALANCING SPEED OF
INSIGHT WITH QUALITY OF INSIGHTS
Wednesday, August 16, 2017 – 2:00 – 3:30 PM
EST
There is a constant tug of war within
insights and research departments. Your internal end-users want things done
quickly and cheaply. While career market researches want to ensure they are
using the savviest tools and techniques, and not just will get the job done
first. This 3-part webinar focuses on how to balance speed and quality.
DEMYSTIFYING THE MILLENNIAL MINDSET
Wednesday, November 15, 2017 ‘ 2:00 ‘ 3:30 PM
EST
Millennials are currently the
largest purchasing base, but remain one of the biggest mysteries for companies
looking to understand the ‘why’ behind their actions and anticipate future
needs. This 3-part webinar focuses on MR in the on-demand mindset and generate
impactful insights that create brands/products around a purpose that speaks to
millennials.

Meet the Powerful Women Driving the Future of Customer Insights

TMRE: The Market Research Event and OmniShopper have some
exciting news to share’
Not only is TMRE partnering with WiRE (Women in Research)
for the first annual TMRE/WiRE Women in Research Award to celebrate some true
rock-star researchers, but we’re happy to share a preliminary list of powerful
women in insights confirmed to take the stage at both the TMRE and OmniShopper 2017
events.

Check out the inspiring women speaking at TMRE 2017:


??        
Dawn Cunningham, Chief Insights Officer, 3M
??        
Amber Case, Cyborg Anthropologist, Author, Calm
Technology
??        
Cole Nussbaum Knaffic, Founder, Storytelling
with Data
??        
Kristin Luck, Founder, WiRE: Women in Research
??        
Marina Kosten, VP Research – International
Theatrical, 20th Century Fox
??        
Elizabeth Merrick May, Head of Customer
Insights, Nest
??        
Christina Jenkins, Director, Global Business
Marketing, North America, Twitter
??        
Anna Fieler, Chief Marketing Officer, Popsugar
??        
Lisa Courtade, Head of Market Research, Merck
??        
Judy Melanson, SVP, Travel & Entertainment,
Chadwick Martin Bailey
??        
Amanda Hill, Chief Marketing Officer, A+E
Networks
??        
Margo Arton, Director of Ad Effectiveness
Research, Buzzfeed
??        
Lauren Zweifler, Senior Vice President
,Strategic Insights & Research, NBCUniversal
??        
Terrae Schroeder, Senior Director, Wholesome
& Shopper Insights, NA Snacks, Kellogg
??        
Theresa Pepe, VP of Research, Viacom
??        
Sarita Bhagwat, Vice President, Market
Intelligence, Fidelity Investments
??        
Julie Brown, President, The Center for Strategy
Research
??        
Lori Tarabeck, Global Market Insights, Abbott
Diabetes Care
??        
Renata Polcicio, Vice President, Fan and Media
Intelligence, International, Global Markets, ESPN
??        
Jennifer Avery, Director, Consumer Insights,
Universal Orlando Resort
??        
Sara Fahim, Senior Research & Innovation
Consultant, Seek Company
??        
Tiffany Sanders, Business Intelligence &
Research, CBS
??        
Emily Akinson, Insights & Planning, Consumer
& Market Insights, Kellogg
??        
Mary Beth Jowers, Consumer Insights Lead for
North, Central and Eastern Europe, Gruppo Campari
??        
Stephanie Cunningham, Senior Manager, Customer
Insights & Analytics, eBay
??        
Lina Roncancio, Insights & Innovation
Director, Discovery Communications Latin America
??        
Michelle Gansle, Director, Consumer & Market
Insights, Wm. Wrigley Jr. Company
??        
Karin Kricorian, Director, Management Science
and Integration, Disney
??        
Sarah Beachler, Director, Market Research &
Client Insights, Sephora
??        
Beth Coleman, SVP Marketing and Partner
Insights, Viacom
??        
Samantha Dawkins, Vice President, Client
Strategy & Advocacy, ADP
??        
Gabriela McCoy, Director of Global Consumer
Insights, Bacardi
??        
Kassie Deng, Director, Marketing & Partner
Insights, Viacom
??        
Lyndsey Albertson, Director of Sales Research,
ABC
??        
Maria Cristina Antonio, Director, Metabolic
Insights & Analytics, Novo Nordisk
??        
Julia Oswald, Senior Vice President, Strategy
& Insights, Domino’s Pizza
??        
Carley Metsker, Vice President, Client Service,
Directions Research
??        
Monika Mandrakas, Market Researcher &
Customer Advocate, Mutual of Omaha
View the TMRE brochure
for a full list of speakers:
https://goo.gl/1Ricj2
Check out the inspiring women speaking at OmniShopper 2017:

??        
Shopper Marketing Activations: Marketing &
Merchandising: J Lynn Martinez, Vice President & Team Lead Kroger, Dr
Pepper Snapple Group
??        
Customer Experience Design: How Research &
Design Collaborate to Build New and Differentiated Experiences: Kate Kompelien,
Customer Experience – Center for Excellence for Research & Strategy, Best
Buy
??        
Omnichannel Customer Analysis: Lakshmi
Venkataramari, Senior Director, Customer Insights & Analytics, Walmart
eCommerce
??        
Winning in Her Purse: Kelley Styring, Principal,
InsightFarm
??        
Knowledge is Power, If You Can Find It: Ashley
Starke & Diana Powell, Manager, Shopper Insights, ConAgra Foods
??        
Team Structure Doesn’t Matter: Sue Butler, Director
of Omnichannel Insights, Walmart
??        
Going Beyond Behavior to Drive Category Growth:
Monica Melichar, Senior Manager, Consumer Insights, Beam Suntory & Erin
Barber, Senior Vice President, C+R Research
??        
Longitudinal Data & the Low Purchase
Frequency Category: Stacy Carty, Shopper Insights, Samsung
??        
Driving Change While Driving the Business:
Improving Tools & Automation: Theresa Hendrickson, Director, eCommerce
Engineering – Business Tools & Processes, Best Buy
View the OmniShopper
Brochure for a full list of speakers: https://goo.gl/Qw8Juo
Use exclusive
LinkedIn discount code TMRE17LI for $100 off the current rate. Buy tickets to
TMRE now:
https://goo.gl/1Ricj2
Use exclusive
LinkedIn discount code OMNI17LI for $100 off the current rate. Buy tickets to
OmniShopper now:
https://goo.gl/Qw8Juo
Also, don’t miss our
upcoming free webinar ‘Storytelling with Data’ http://bit.ly/2o0bpAS
featuring speakers Kelsy Saulsbury, Manager, Consumer Insight & Analytics,
Schwan’s Shared Services, LLC and Bill Greenwald, Founder and Chief
Neuroleaderologist, Windsor Leadership Group, LLC. 
Driving the value of
insights forward requires much more than just unearthing great data. You need
to use that data to tell a story and command influence across the broader
organization. Because storytelling may not be an inherent skill, this webinar
focuses on how to use data to create an engaging, informative, compelling
story.  Register for the webinar here:
http://bit.ly/2o0bpAS
Cheers,
The TMRE & OmniShopper Teams
@TMRE
@OmniShopper

Why Social Influence is Important in Business: Q&A with Jonah Berger

We were lucky enough to recently catch up with one of our
favorite conference speakers Jonah Berger, who is well-known as a Wharton
Professor and Bestselling Author of Invisible
Influence
and Contagious:
Why Things Catch On
.
Berger shared some key insights about why social
influence is key to business from his new book Invisible Influence.

Here’s what Jonah had to say:
What is ‘social
influence’?
Berger: Social
influence is the impact people have on others around them. We vote if our
spouse is voting, run faster if someone else is watching us, or switch our entr??e
if someone at the table orders the same thing.  In each instance, others’
behavior influences or affects our own. Those others can be spouses and
friends, but also people we never even talk to, like the stranger sitting next
to us on the plane.  Social influence effects small things, like the food
we eat, but also big things like the career we choose or whether we save money
for retirement. Ninety-nine-point-nine percent of all decisions are shaped by
others. It’s hard to find a decision or behavior that isn’t affected by other
people.
Why is social
influence important in business?
Berger: If we
understand how influence works, we can harness its power. We can convince
a client, change the boss’ mind, and motivate employees to take action.  One section of the book, for example, talks
about how being a chameleon can make you more successful. Researchers looked at
what makes someone a good negotiator. 
What makes them more likely to reach a deal when all looks
lost. And they found that one simple trick led negotiators to be 5x as
successful. That trick?  Imitating or mimicking the language,
behavior, or facial expressions of their negotiating partner. If their partner
crossed their legs, they did the same.  And if their partner leaned back
in the chair, they did so as well. Not obviously, but subtly mirroring
their partner.  Turns out the same trick works in a range of
contexts. Waiters or waitresses that mimic their patrons’ orders get 70%
higher tips.  Mimicry increases liking, trust, and affiliation.  It
deepens social bond and makes people feel a kinship that turns strangers into
friends and acquaintances into allies.
Why is social
influence key to reaching the right customers?
Berger: Word of
mouth is 10x as effective as traditional advertising. People trust it more and
its more targeted.  So, to reach the right customers, we have to turn our
existing customers into advocates. Use social influence to get them to
talk about and share our message and bring new converts in along the way. 
 
How can individuals
harness the power of social influence to make better decisions in their
personal lives?  
Berger: If we
understand how influence works, we can take advantage of its benefits and avoid
its downsides. Following others can provide a useful shortcut that saves
time and effort. If lots of people chose or did something, it’s probably pretty
good. So, others can be a valuable source of information, a heuristic that
simplifies decision making. Other times, however, following others can
lead us astray.  So, simple tricks like considering whether others have
the same preferences as we do can help us avoid going the wrong way.
Have you ever been personally affected by the power of
social influence? What is an example?
Certainly. I was telling lawyer friend of mine from DC about
the book and he was lamenting the effect of social influence on his
colleagues. He said the first thing new lawyers in DC do when they make
partner is go out and buy a BMW.  I said that was interesting, but then
pointed out that he himself was a DC lawyer and drove a BMW. He said yes, but
they all drive grey BMWs. I bought a blue one.
What I love about this story is that it perfectly
encapsulates the tension inherent in social influence.  People often think
being influenced means doing the same thing as others, but it’s more complex
than that.  There’s more than one flavor of influence. Sure, sometimes we
imitate those around us, but we also care about standing out and being
unique.  So, when do we do the same thing as others and when do we do
something different. 
In your book, you
share an experiment about cockroaches and how their behavior changed when they
had an audience.  What insights can you share about how we behave when our
actions are observed?
Berger: It makes
sense that people and animals might work harder when there is a
competition.  If two pigeons are racing to get the last piece of bread, or
two people are competing to win a golf tournament, the desire to achieve the
reward or win the competition might lead people and animals to work harder.
Even the mere presence of others though, can have similar effects. 
Cockroaches, for example, ran faster through a maze when
other cockroaches were watching them, even though those others weren’t directly
competing.  People behave similarly.  The mere fact that someone is
watching us can increase motivation and performance.  But for new or
difficult tasks, others can sometimes have the opposite effect.  Having
someone else in the car when we’re trying to parallel park, for example, makes
it harder for most of us to fit in the spot.  So, whether others presence
helps or hurts depends on the nature of the task.

Online Ad Effectiveness Research Grows Up

 This article is
brought to you by Survata.

The days of giving
digital a pass are over. It’s time to grow up.’- Marc
Pritchard, Chief Branding Officer, Procter & Gamble, January 2017
When the CBO of P&G tells us to grow up,
we listen. And after speaking with clients at last month’s Media Insights
Conference, it’s clear that there’s consensus: online advertising research
needs to get more sophisticated.
We’re here to help. IAB breaks research down into phases: design, recruitment & deployment, and
optimization. We’ll walk through each phase and determine what’s most in need
of ‘growing up.’ We’ll also include questions to ask your research partner to
help increase the sophistication of your ad effectiveness research.
Design

Let’s start by acknowledging that
statistically sound online ad effectiveness research has not been easy to
implement at reasonable cost until recently. As IAB notes, ‘Questions around recruitment, sample bias and deployment are
hampering the validity of this research and undermining the industry as a
whole.’
Just because perfect research design is
challenging to achieve doesn’t mean that advertisers should settle for studies
with debilitating flaws, leading to biased, unreliable results. In addition to
challenges inherent to good research design, most ad effectiveness research
partners have systematic biases due to the way they find respondents, which
must be accounted for in the design phase. There has been innovation in this
space within the past year using technology to reduce or eliminate systematic
bias in respondent recruitment. 
Assuming you’re able to address the systematic
bias of your research partner’s sampling, the major remaining challenge is how
you approach the control group. At Survata, we think about this as a hierarchy: 
Using a holdout group is best practice, but
implementing it requires spending some portion of your ad budget strictly on
the control group. In other words, some of your ad budget will be spent on
intentionally NOT showing people an ad. A small portion of people in the ad buy
will instead be shown public service announcements to establish the control
group. We love the purity of this approach, but we also understand the reality
of advertising budgets. We don’t view holdout as a requirement for sound online
ad effectiveness research. Smart design combined with technology can achieve
methodologically sound control groups without ‘wasting’ ad budget.
Along those lines, the Audience Segment
approach has become de facto best practice for many of our clients. Basically,
you create your control group from the same audience segment that you’re
targeting in the ad buy. This isn’t perfect, as there could be an underlying
reason that some people in the segment saw the ad but others didn’t (e.g., some
people very rarely go online, or to very few websites), but it’s still an excellent
approach. It’s the grown-up version of Demographic Matching.
Demographic Matching, in which the control
group is created by matching as many demographic variables as possible with the
exposed group (e.g., gender, age, income), is still a very common strategy.
It’s straightforward to accomplish even using old online research
methodologies. As online data has allowed us to learn far more useful
information about consumers than demographic traits, this approach is dated.
Simply sampling GenPop as a control is
undesirable. The results are much more likely to reveal the differences between
the exposed and control groups than the effectiveness of the advertising.
Questions for your research partner:
  • What are known biases among
    respondents due to recruitment strategy?
  • What is your total reach? What
    percentage of the target group is within your reach? Is it necessary to
    weight low-IR population respondents due to lack of scale?
  • What’s your approach to creating
    control groups for online ad effectiveness research?
  • For Demographic Matching, how do
    you determine which demographic characteristics are most important to
    match?
  • How do you accomplish Audience
    Segment matching?
Recruitment/ Deployment

Historically, there were four methods to recruit respondents / deploy the
survey: panels, intercepts, in-banner, or email list. To stomach these
methodologies, researchers had to ignore one of the following flaws:
non-response bias, misrepresentation, interruption of the customer experience
or email list atrophy. In our view, these methodologies are now dated since the
advent of the publisher network methodology.

The publisher network works by offering
consumers content, ad-free browsing, or other benefits (e.g. free Wi-Fi) in
exchange for taking a survey. The survey is completed as an alternative to
paying for the content or service after the consumer organically visits the
publisher. In addition to avoiding the flaws of the old methodologies, the
publisher network model provides dramatically increased accuracy, scale, and speed.
Questions for your research partner:
  • What incentives are offered in
    exchange for respondent participation?
  • What are the attitudinal,
    behavioral, and demographic differences between someone willing to be in a
    panel versus someone not interested in being in a panel?
  • What are the attitudinal,
    behavioral, and demographic differences between someone willing to take a
    site intercept survey versus someone not interested in taking a site
    intercept survey?
  • How much does non-response bias
    affect the data?
  • Are you integrated with the
    client’s DMP?
  • How long to get the survey into
    the field, and how long until completed?
  • How does the vendor ensure that
    exposure bias doesn’t occur?
  • How does the vendor account for
    straight-liners, speeders, and other typical data quality issues?
Optimization

An optimal ad effectiveness campaign returns results quickly, so that immediate
and continuous adjustments can be made to replace poorly performing creative,
targeting, and placements with higher performing ones. We call this real-time
spend allocation. It’s analogous to real-time click-through rate optimization,
as it relies on solutions to the same math problem (known as the multi-armed bandit).

By integrating with DMPs, ad effectiveness
research can be cross-tabbed against even more datasets. The results will yield
additional insights about a company’s existing customers.
Questions for your research partner:
  • Are results reported real-time?
  • How much advertising budget is
    wasted due to non-optimization?
  • How can DMP data be incorporated
    to improve ad research?
Conclusion

Flawed research methodologies can’t grow up,
they can only continue to lower prices for increasingly suspect data. For
online ad effectiveness research to grow up, new methodologies must be adopted.

To learn more about
conducting your own ad effectiveness study, visit Survata

Image Recognition and the Future of Digital Analytics

This post was originally
published
on Kelton Global’s Blog.

The days of text-centric social feeds are officially long
gone. A whopping 1.8 billion images are uploaded to the Internet daily
and of those, 350 million are shared on Facebook. Instagram recently
surpassed 500 million active users, and Snapchat now has more active users than Twitter. The content that flows
into our social feeds is more heavily optimized than ever to deliver more of
what people want’less text and more visuals.
Brands have adapted their social content strategies
accordingly by delivering more visually immersive experiences. And while we’re
seeing significant shifts in branded content, this influx of visual content has
yet to herald a commensurate change in social analytics. Accordingly, few gains
have been made to measure and derive insights from the contents of images or
video. Social listening has historically focused on the challenges of text-based
analysis’specifically, the challenge of determining the context and meaning
behind posts. But as social media habits evolve, it’s clear that deriving
insights from pictures is an increasingly important aspect of understanding
consumers. That’s where image recognition comes into play.
Brands have adapted
their social content strategies accordingly by delivering more visually
immersive experiences.

Simply put, image recognition is the process of translating
images to data. Photos and images can reveal a wealth of data
points’demographics, purchases, personalities, and behaviors (just to name a
few). Through next generation image recognition, a mere selfie may reveal a
person’s gender, approximate age, location disposition, and even the clothing
brands that the person is wearing. As text-centric media takes a backseat to
image and video, the opportunity to understand the contents of these formats
grows. These insights represent a veritable treasure trove of actionable data
for brands.
Tools that analyze image and video-based content are still
in development, but increased investment in research is already impacting
commercial products and how they’re advertised. One example is brand logo
recognition’scanning images for brand logos, and flagging them with the
corresponding brand names. This tool is especially powerful considering that 80% of photos shared online depict a brand logo but don’t
explicitly call out the brand’s name.
 This fact points to a sizable
opportunity for companies to measure and understand the impact of these formerly
inaccessible data points.
Photos and images can
reveal a wealth of data points’demographics, purchases, personalities, and
behaviors (just to name a few).

As an example of how this applies to brands, Kelton’s
Digital Analytics team took a look at the scores of backyard BBQ photos that
flooded public forums, blogs, and social feeds over the recent 4th of July
holiday. We experimented to see which of two quintessentially American beverage
brands’Coca-Cola and Budweiser’netted more published images of
patriotically-themed bottles and cans (as well as other forms of branding) on
social media.

In the end, Coca-Cola branding was twice as prominent as
Budweiser’s. We found that Coke bottles and cans popped up in more diverse
settings such as public parks and inside motor vehicles, whereas Budweiser was
predominantly found in bars and house parties. Coke also aroused greater
sentiment around the theme of Americana, as many consumers
photographed vintage Coca-Cola gear and opted for bottles over cans. This might
explain why Coke captured a significantly greater share of social mentions than
Budweiser.
This example illustrates several ways that brands can
leverage image recognition technology to build actionable insights:
??        
Ethnographic data ‘ Identify where, when
and how often brands are showing up in people’s lives.
??        
Updated brand health analysis ‘ We now have
a more comprehensive point of view of brands’ online footprint.
??        
Sponsorship and Branding ROI ‘ Extend the
value of branding and sponsorships shared via online news, blogs and social
media through a multiplier effect.
??        
Influencer identification ‘ Find authentic
brand advocates who consume and spotlight your merchandise.
??        
Misuse use of brand iconography ‘ Surface
content that depicts improper usage of brand’s logo or other creative assets.

In today’s ever-shifting social media landscape, it’s never
been more important for brands and their partners to stay aware of the new and
emerging capabilities that can help better understand consumers’ behavior
online. Image recognition is just the beginning. From AI startups to instant
objection recognition devices
, the mobilization and fusion of research,
tech, and capital is quickly reshaping the way we think about analytics. These
new tools will add even more contextual understanding to sentiment on social
platforms, empowering brands to understand consumers like never before.

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. 

#MediaInsights Day 1 Recap

By: Jim Bono, Vice
President, Research, Crown Media Family Networks

MI&E Conference Director Rachel McDonald started
off the day welcoming this year’s attendees and introducing this year’s
co-chairs: Janet Gallent (NBCUniversal), Rob McLoughlin (POPSUGAR) and Bruce
Friend (Maru/Matchbox).
Bruce then sat with Turner’s Howard Shimmel for the OPENING
KEYNOTE INTERVIEW: Re-Imagining the Future of Television
.  Recently, at a Cynopsis conference, Shimmel
said “we’re at a measurement crisis.” 
Elaborating on that comment, he explained how it’s 2017 and we still do
not have a robust cross-platform solution for our industry. Advertisers want an
infrastructure that allows more exposure than just reach and frequency.  With Total Audience, we still don’t know what
to do with it.
They also discussed the Turner Ad Lab, and how people go to
Netflix, Hulu, etc., to watch content without ads. What can we do to make the
advertising experience better for the consumer? Howard believes that the industry should have a published
document that mandates what currency data research vendors should provide for
the content providers. As new platforms are emerging, we need to better
understand where those consumers are going to find content.
Bruce asked about big data and how it’s all the rage. As an
industry where do we go from here?  
Howard explained how there is an abundance of research tools out there.  We just haven’t done a good enough job
telling our clients that we have all these tools.  Big data is a component to an overall data
framework. We need to know when to use it and not to use it. Sometimes Big Data
can be wrong data.
Bruce also questioned how new companies are great with tech
but don’t understand the data they deliver. However, other great long-time
research companies are very good at analyzing data but don’t have the tech.  Howard feels that there’s nothing wrong with
using a combination of data sets like Nielsen, MRI, and panel data to come up
with the best solution. Unfortunately, there are too many companies that reach
out and don’t really understand our businesses.
He still believes that survey research is important to our
industry as data tells what, but not why.
KEYNOTE: The Importance of Race and Ethnicity in Reaching
Millennials

Cathy Cohen, Professor at University of Chicago, gave us a
very entertaining look at millennials and the importance of race and ethnicity
among this group, especially regarding this year’s election. The majority of
Millennials in the US are Hispanic and African-American, and by 2060 White will
be a minority. In this past year’s election, more African-American and Latino
Millennials voted for Democrats, while there were more white Millennials voting
Republican. However, in the 2016 primary vote the choice among all Millennials (regardless
of ethnicity) was Bernie Sanders.
Cohen’s presentation covered: 

  • ??        
    The complexity of Millennials through a racial
    framework
  • ??        
    Researching race and Millennials
  • ??        
    Rise of Millennials in the workforce
  • ??        
    Importance of Millennials in the Political force
Millennials are becoming an increasingly important electoral
demographic. The share of eligible
voters that are Millennials has grown during last 3 elections:

  • ??        
    2008 – 23%
  • ??        
    2012 – 29%
  • ??        
    2016 – 36%
Cohen also addressed the six key problems with studying
Millennials:
1.      
 Generational frames / over-representation of
white Millennials
2.      
 Under
investigation of white Millennials
3.      
 Homogenous communities of color missing
Millennials
4.      
 Segmentation of Millennials of color – pick
one!
5.      
 Millennials as experts of Millennials -
homophily
6.      
 One-offs
or waves – assumes stability in taste, preferences and decisions
KEYNOTE PANEL: How Consumers Engage with Programming Across
Social Platforms
Sean Casey from Nielsen Social Guide moderated this
morning’s Keynote Panel featuring Brian Robinson (Facebook), Tom Ciszik
(Twitter), Guy Ram (NBC), Leslie Koch (HBO).
Insights focused on the evolution of social media and how
quickly it’s grown.
Consumers spend 5.5 hours per week using Social Media on
their smartphone.
64% of consumers use smartphone while watching TV. 
1.2 billion interact on Social referring to TV.
After breaking for lunch hour afternoon consisted of Concurrent
Tracks.  These case studies were broken
into three groups:

  • ??        
    Track 1 – Targeting Viewers
  • ??        
    Track 2 – Audience Insights
  • ??        
    Track 3 – Innovation in Media
Track 1 – Targeting Viewers case studies:
From Ordinary Target to Persuadable Target

David Kaplan from Bravo, along with Zach Schessel from NBCU
and Peter Bouchard from Civis Analytics, discussing how to hit the right target
audience and “swing” viewers. The presentation also looked at how to
attract casual viewers without alienating the core viewers.
Key takeaways were:
??        
The different creative approach is often
required for on-air vs. off-channel to drive maximum impact with loyal and
casual viewers
??        
Casual Bravo viewers may all have some affinity
for the network but only the “swing viewers” in this group can be
readily persuaded to deepen their commitment and watch more
??        
 An ads
positive persuadability should be balanced with any potential backlash effects
to ensure a net positive effect
??        
 Not all
swing viewers are created equal, eg. consumers in different DMAs can have a
varied response to creative hooks
Viewing Predictions & Inventory Optimization: The
Secrets to Success in Audience Targeting

Steve Schmitt of TiVo showed us how TiVo is helping clients get
from traditional linear to non-linear content, and how they improved campaign
performance using optimizers and brand targeting. His presentation focused on
how:
??        
 TV
consumption has undergone profound changes, especially Millennials age 18-34
??        
 Total
video consumption continues to expand with DVR, VOD, SVOD and online/mobile
viewing extending the power of linear TV
??        
 Linear TV
has majority share, but it is declining as on-demand options expand
Concepts on the rise are binge viewing, on-demand,
cord-cutting and cord-shaving, while things like appointment viewing and one-size-fits-all
on decline.
Online Video in the Toolbox: A Must Have

Darlene LaChapelle and Maya Abinakad from AOL talked about
the top drivers for video growth, with “social media video offerings”
and “better quality creative” leading the way, and how online video
growth is driven by mobile devices.
??        
Online video viewing on a smartphone is on par
with that of a computer
??        
 Consumers
indicate they have few technical barriers watching online video on their
smartphones, but get the convenience of watching anywhere, anytime
??        
 62% said
I watch more online video today than one year ago
??        
 62% said
in the next 6 months I expect to watch more online video
Laptop/desktop (70%) is still the leading device on which
online video is watch daily, just edging smartphone (67%)
How to Engage  Multicultural Millennial Influencers in 2017
and Beyond

Our afternoon continued with our only Track 1 panel.  The panel was moderated by Horowitz’s Adriana
Waterson, and we heard from Michele Meyer (Univision), Tom Kralik (Revolt) and
Lia Silkworth (Telemundo) as they discussed their key takeaways about
multicultural millennials and the importance of this audience in our business
today, as leading consumers of cross-platform media.
??        
 Hispanics
are leading the charge in cross-platform media consumption
??        
 Millennial and Gen Z trends ARE multicultural
trends
??        
Gen Z is more diverse and multicultural and are digital
natives
??        
 If you
join a multicultural network, your general market skills may not “translate”
The Next Generation of Ad Effectiveness
Our first day concluded with this presentation from Chris
Kelly at Survata.