Monday, March 27, 2017

Is Amazon in the Room?

By: Laura Sigman

This post was originally published on the LightSpeed Research blog.

On a recent earnings call, Sir Martin Sorrell, CEO of Lightspeed’s parent company WPP, talked about what keeps him up at night. And no; it’s not (necessarily) his infant daughter – it’s Amazon.

“And I would just mention the rise of Amazon, because in answer to the question, my favorite question is what worries you when you go to bed at night and when you wake up in the morning. It's not a three-month-old child (laughter), it's Amazon, which is a child still, but not three months. And Amazon's penetration of most areas is frightening, if not terrifying to some, and I think there is a battle brewing between Google and Amazon.”


The fear mostly seems to be of the unknown, as Amazon is thought to be quietly pursuing an advertising strategy carefully away from the watchful eyes of Wall Street.

Is Amazon really committed? They are by pure virtue of their strategically evolving business model. By being among the first big players on the e-commerce scene, they cemented their early adapter consumers to them. They’ve grown a multimedia offer around their core competency, and now Amazon knows not only what we read, but what we search for, what we buy, what we watch, what we listen to. I’m an Amazon Prime customer, and I take advantage of all of the bells and whistles that come along with it. So they know what content I’m engaging with, and whether I’m connecting to the content from my PC, smartphone, tablet or Alexa. And they can leverage this vast supply of shopper and behavioral data to sell hyper-targeted advertising to brands who can then speak directly to me.

When you look at it like that, it’s really not much different than how we’ve worked in the panel world. Historically, we have facilitated the conversations brands have with consumers, and have evolved by taking advantage of emerging technologies to help amplify those conversations. And, like Amazon, we grew our business by embracing early on that panelists (consumers) are people, too. 

(Believe it or not, it’s not as obvious to everyone as that sounds!) Today’s consumers want to have meaningful interactions, but they also want to have them when and where is convenient to them. So we meet them on their devices of choice; we always design surveys mobile-first (in fact, Lightspeed has an entire team dedicated to this) and we use data appends to reach the right consumer with the right questions. We invite survey respondents to answer open-ends with video responses – an engaging experience for them resulting in more meaningful data for brands to act on. We’re able to blur the line between quant and qual, intercepting surveys with invites to participate in deeper, on-point conversations. And brands can leverage all of this to create hyper-targeted advertising that speaks directly to their consumers. Which ties back to that Amazon example I shared above.

As Kantar pointed out at their FragmentNation event, the marketplace is splintering -- not with a whimper but with a bang. So while the ad world should fear the Amazon in the room, it should also embrace it. It’s an eye-opening reminder that consumers are advertising’s most valuable assets in a marketplace that is more diverse and fragmented than ever.



Wednesday, March 22, 2017

Here Comes Gen Z: 10 Keys to Understanding Them


According to Open Mind Strategy research, these are the top things to know about the new kids on the block Gen Z:

1. Huge
Gen Zs make up more than a third of the world’s population and comprise nearly a quarter of the US population – bigger than both Millennials and Baby Boomers – and still being born.

2. The most diverse generation ever
Gen Z will be the last majority-White generation born in the United States. Already the white majority is holding on by a thread, only 51% of Gen Z born into non-Hispanic White families.
This generation’s diversity also extends to their sexuality and gender identity. More than one-third of Gen Zs self-identify as bisexual to some degree; more than half know someone who uses gender-neutral pronouns.

3. They idolize Influencers, not Celebrities
Most dedicate more time to YouTube than any other social site and their view of celebrities isn’t limited to movie stars and musicians, note the billions of views racked up by YouTube stars RayWilliamJohnson and PewDiePie. They want to emulate self-made Influencers who are just like them.

4. A plan to get paid
While Gen Zs are certainly passion-driven, if they know their passions won’t lead to financial stability, they have a plan for something that will. In everything from entrepreneurship to sports, kids and teens are finding places to excel early and focus their efforts in hopes of a payoff.

5. Having safe fun
Gen Zs are still teenagers! They want to have a good time, but they don’t want to negatively impact the successful future they are working to build. The teen pregnancy and birth rate are at historic lows, as is the usage of cigarettes and heroin among high-schoolers.

6. Caring about “cool”
Gen Z is snarky and very image aware. With the ever-growing influence of social media, there is a palpable return of “cool kids” and “losers” among Gen Z. They will quickly take down a post that doesn’t receive enough likes for fear of someone seeing its lack of attention.

7. Don’t share everything online
Gen Z takes a crafted and curated approach to posts. They are more aware of who they are sharing their lives with and how it affects their identity, which is why platforms like Snapchat are so appealing. They saw the devastating effects party pics had on their sibling’s scholarship or job offer.

8. No Mo “Beta Boys”
Gen Z boys want to be taken more seriously. To them, girls are certainly equal, but not better. Gen Z boys want in on the partnership by taking themselves a bit more seriously in school, work and relationships, but also embracing their sensitive side.

9. Mostly cynical
Gen Zs have realistic expectations and are skeptical that the world will work in their favor. More than eight in 10 Gen Zs were born after September 11. Growing up, conflicts over issues like the economy, gun violence and climate change, have been common. As a result, these teens have developed a valid claim to cynicism.

10. Still KIDS!
This generation is just beginning to come of age, and as uptight as they may seem, they’re still kids who haven’t quite figured it all out yet. They’re working hard and taking themselves seriously, but they are still silly, young, fun and undeclared.
END

Open Mind Strategy, LLC, is a research and brand strategy firm founded by Robin Hafitz, in 2010, with the mission of providing “more human intelligence.” OMS (http://www.openmindstrategy.com/) provides insight services, including qualitative and quantitative research, brand studies, show and message testing, segmentation, and customized inquiries, as well as strategic brand consulting and educational workshops. The OMS team is proud to have worked with leading clients, such as A&E Networks, AMC, Amazon, Clear Channel, Condé Nast, Gannett, Kao Brands, MTV, NBCUniversal, Scripps Networks, Unilever, USA Today, Yahoo!, and many more.


Monday, March 20, 2017

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

Monday, March 13, 2017

Must See Talks from KNect365’s Spring Insights 2017 Events

From former gang leaders, to cyborg anthropologists, to biomimicry experts- KNect365’s Must See Talks will challenge you to look at problems in a whole new way and become an ignitor of change for your organization.

“The Centrality of a Detailed Understanding of your Audience” – Haile Owusu, Chief Data Scientist, Mashable
Marketing Analytics & Data Science
April 3-5, 2017
San Francisco, CA
Use code MADS17LI for $100 off.
Buy tickets to see Haile: https://goo.gl/YqXZdx

“The Consumer Influence – and Impact – of Virtual Reality” – Jeremy Bailenson, Founding Director of Stanford University’s Virtual Human Interaction Lab at Stanford University
TMRE in Focus
May 1-3, 2017
Chicago, IL
Use code FOCUS17LI for $100 off.
Buy tickets to see Jeremy: https://goo.gl/c2UdIv

“Originals: How Non-Conformists Rule the World” – Adam Grant, Professor, Author of Give and Take and Originals at The Wharton School of Business at the University of Pennsylvania
OmniShopper
June 20-22, 2017
Minneapolis, MN
Use code OMNI17LI for $100 off.
Buy tickets to see Adam: https://goo.gl/oUB85g

“Underdogs, Misfits & the Art of Battling Giants” – Malcom Gladwell, Best-Selling Author of Outliers, The Tipping Point and David & Goliath
TMRE: The Market Research Event
October 22-25, 2017
Orlando, FL
Use code TMRE17LI for $100 off.
Buy tickets to see Malcom: https://goo.gl/gM7Dtv

We hope to see you this spring!

Cheers,

The KNect 365 Event Team

Wednesday, March 8, 2017

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 here: https://goo.gl/CbYosj

Monday, March 6, 2017

Using Geofencing to Observe Shopper Behavior

This post was originally published on the Research Now blog.

It is widely discussed that mobile opens up incredible opportunities for researchers. It is perhaps equally widely discussed that mobile provides challenges for researchers – especially those most reticent to part with, let’s say, more traditional approaches. I could think of a number of examples of this two-sided coin, but I’ll leave all of those, save one, for future discussions.


One that the industry needs to tackle head on is the use of geolocation for understanding shopper behavior. So much opportunity! But logistics and analysis is so hard (for many rooted in market research)! The notion of using geolocation itself for research is no longer new. Geofencing has been used to target people for research for several years – with the most commonly used methodologies centered around delivering a survey to someone when they are in a specific location or after they have left. In many cases this is a viable approach to understanding shoppers – and getting feedback close to the point of experience.

Personally, I’m a fan of targeted and efficient research engagements that ask people to recall their shopping behaviors before they forget them. But I am also a fan of not having to ask what we don’t really need to ask, for example who they are, where they shopped, and when. With this idea in mind, and wanting to piggyback on prior years of researching Americans’ Black Friday shopping habits, we looked to explore how geofencing could be effectively utilized to understand shoppers with minimal active engagement from them. So, last Fall, we brainstormed with Placecast and their savvy team of location-focused researchers on how we could shed new light onto shopping behaviors around this critical time period for retailers.

While we did end up asking some questions directly of people, we managed to glean a lot by matching our panelists’ location data with existing profiling attributes. We discovered, for example, that the most affluent Walmart shoppers came to the store on Black Friday when compared to days leading up to and following that day.


The most affluent shoppers also proved to shop early in the morning in the days immediately prior to and following Black Friday. Understanding who shops where and when is crucial to retailers and advertisers as they try to craft relevant messaging and promotions for holiday sales. Combining geolocation data and associated advanced analytics with known profiling attributes creates a compelling story about shopper behavior, one that can be layered with surveys and other data sources to provide actionable insights.


The industry has an opportunity here – to use geolocation data in a smart way and one that alleviates much of the survey burden often placed on participants.

Wednesday, March 1, 2017

The OmniShopper 2017 Full Keynote Lineup

You’ve already heard about some of the biggest changes we’ve made to OmniShopper for 2017 – moving the event to June, away from your summer vacations and changing the location to Minneapolis, home of the Mall of America, the retail mecca.


But, what you may not have heard about yet is the FULL keynote lineup – it’s completely different from what you’ve seen before. Covering everything from marketing in the Trump era, the future of retail, the human side of selling, data informed design and more:

·         Originals: How Non-Conformists Rule the World
Adam Grant, Professor, The Wharton School of Business at the University of Pennsylvania, Author, Give and Take and Originals
·         Marketing in the Trump Age: New Rules for a New Reality
Peter Horst, Former Chief Marketing Officer, The Hershey Company
·         Digital Humanism & Recoding Culture: Moving Toward the End of Demographics, Evolution of
·         Psychographics and the Rise of the Individual
Edwin Wong, VP Research & Insights, Buzzfeed
·         CX Sells: How to Win with the Human Side of Selling at Brick & Mortar
Bridget Brennan, CEO, Female Factor, Author, Why She Buys
·         Moments Matter... Make Yours Iconic
Soon Yu, Former Global Vice President of Innovation, VF Corp, Author, Iconic Advantage
·         Data Informed Design: How the Evolution of Data Science Has Permeated into Product Vision & Design
Charlie Burgoyne, Principal Director of Data Science, Frog Design
·         Winning in Her Purse: How the Rise of Technology has Caused Far-Reaching Disruption Even in the Most Ubiquitous Fashion and Life Accessory
Kelley Styring, Principal, InsightFarm
·         Panel: Shaping the Future of Retail with Science, Technology & Consumers
Lakshmi Venkataramani, Senior Director, Customer Insights & Analytics, Walmart eCommerce
J Lynn Martinez, Vice President & Team Lead Kroger, Dr Pepper Snapple Group
Dr. Duane Varan, Chief Executive Officer, MediaScience

View the OmniShopper agenda for full session details: https://goo.gl/EqFq4h

Use exclusive LinkedIn discount code OMNI17BL for $100 off the current rate: https://goo.gl/EqFq4h

Subscribe to our monthly insights newsletter, The Insighter: http://bit.ly/2m9UIoG

We hope to see you in Minneapolis!

Cheers,
The OmniShopper Team
@OmniShopper

#OmniShopperEvent