5 Qualities that Great Brands and Great Characters Share

What makes some brands so great? Find out the five qualities they all share in this Big Ideas piece.

Editor’s Note: This post is part of our Big Ideas Series, a column highlighting the innovative thinking and thought leadership at IIeX events around the world. Jim White will be speaking at IIeX North America (June 12-14 in Atlanta). If you liked this article, you’ll LOVE IIeX NA. Click here to learn more.

By Jim White

We use brands to tell ourselves stories about who we are. The brands that are most meaningful to us are those that play a role in our internal life stories, or what psychologists call our Narrative Identity.

I’ve spent years listening to people tell stories about how brands fit into their lives. And something I’ve learned is that strong brands possess many of the same qualities as great characters.  

Think about the fictional characters that you love. I bet you’ll find they have some things in common. Now imagine your brand possessing these same qualities. Think about how that would change your brand strategy, your marketing and your insights work.

Here are 5 qualities that great characters and great brands share.

AGENCY

Great characters and great brands take action. They make things happen. They control their own destinies. For brands, agency is all about innovation and leadership. Netflix has agency in a category that requires it to survive. From DVD, home delivery to streaming to content production, the brand has managed to stay out in front of competitors.

MOTIVATION

Great characters and great brands have a clear motivation for what they do. They have a mission. They have a fight. They are compelled to resolve a conflict or champion a cause. IKEA’s motivation is “to create a better everyday life for the many.” That’s a clear motivation that comes through in their products, pricing and marketing.

CONFLICT

Great characters and great brands face conflict. They struggle. It gives their story drama. It’s clear not just what they stand for, but what they stand against. Sometimes they face a villain. Sometimes it’s an internal conflict they must overcome. A few years ago, Smart Car declared itself “Against Dumb,” challenging the excesses of modern life. They identified their villain and challenged car buyers to join their fight.

COMPLEXITY

Great characters and great brands aren’t one-dimensional. They have nuance and complexity. They don’t get stale or uninteresting. Great brands possess a collection of interesting stories and experiences for consumers to discover. Chobani yogurt’s backstory is interesting. Its founder, Hamdi Ulukaya, is a complex person who can be both likeable and brash — and the brand has exciting plans for the future. Chobani has a rich collection of narratives that give it complexity and make it interesting.

THE ABILITY TO SURPRISE

Great characters and great brands surprise us. While staying true to their identities, they say and do things we don’t quite expect. Last year, Patagonia’s Black Friday promotion – when it donated all Black Friday profits to grassroots environmental organizations- was surprising even for a brand known for philanthropy. The surprising act put the mature brand back into public consciousness.

So, does your brand have what it takes to be a great character? If not, I encourage you to think about how the traits listed above might change your brand strategy. And maybe your brand can play a starring role in the life story of your consumer.

If you’d like to read more characteristics of great characters, check out actor/writer Chuck Wendig’s website terribleminds.

For more on Narrative Identity, check out The Stories We Live By: Personal Myths and the Making of the Self by Northwestern University psychology professor Dan P. McAdams.

Mobile GeoLocation Studies Are Cutting Edge in 2017, but Let’s Give Props to Their Precursors from 1920

Location-based consumer research, with its origins in the 1920s, is not a new idea - however with increased technology it is becoming less complicated and expensive to obtain.

By Chris St. Hilaire, Co-founder and CEO, MFour Mobile Research

For nearly 100 years, location-based consumer research has been the gold standard for getting insights when they’re red-hot. Now, in the Smartphone Era, in-location insights can be even hotter, but considerably less complicated and expensive to obtain.

Location studies have come a long way since 1920, when a dozen researchers fanned out through the shopping district and surrounding neighborhoods of Sabetha, Kansas (pop. 2,003 at the time) to query townspeople for a Philadelphia company that published Ladies Home Journal, the Saturday Evening Post, and other popular magazines. They were on a quest for insights into how much bang these magazines’ advertisers were getting for their buck.

Today’s insights professionals can accomplish in-location surveys with just one researcher who’s sitting in front of a computer screen that might be anywhere. 21st century GeoLocation technology makes it possible to pinpoint any mobile device’s whereabouts, and an unlimited number of locations can be “geofenced” to encompass all the stores or other venues that might be  relevant to a given research project. All that’s needed is an accurate latitude/longitude coordinate for each location in the study.

For example, a comparative study involving products sold at pharmacies could geofence Walgreens, CVS and Rite Aid stores across the U.S., or within a particular region. When a member of an opt-in mobile panel crosses a geofence, that person is now GeoLocated, and automatically receives a push notification on the same phone that has revealed he or she is in the right place to receive the location-based survey. That makes each respondent a spiritual heir to the 1920 townsfolk of Sabetha, Kansas — and each researcher who conducts a GeoLocation study stands on the shoulders of the dozen intrepid people who came to Kansas armed with paper and pencils and questions about magazine ads.   

History – or at least Stefan Schwarzkopf’s account in “The Routledge Companion to Marketing History” — doesn’t specify what the Sabetha researchers working under pioneer market researcher Charles Coolidge Parlin managed to learn about magazine advertising’s efficacy in rural Kansas. But I’m pretty sure that future volumes on the history of market research will have plenty to say about GeoLocation studies.

They may note that the 21st Century gold standard for in-location research surpassed the 20th century standard in one important way. By eliminating  direct, face-to-face contact mediated by a clipboard and pen, GeoLocation studies reduce the bias that comes from unavoidable variances between researchers’ personalities, training, and consistency in asking survey questions – all of which can impact a study’s results.

Mobile GeoLocation puts the answers solely (and literally) in the respondents’ hands. The objectives of today’s unseen in-location researchers will be more or less the same as they were in 1920: insights into shoppers’ motivations, actions, thoughts and feelings at or just after the moment of truth when purchasing decisions are made. But by substituting smartphones in respondents’ hands for clipboards and pens wielded by the interviewer, today’s in-location projects can access an unprecedented fount of vivid data — real-time audio and video that can be introduced to enhance a question, or collected from respondents who make audio/video selfies to provide in-their-own-words answers. It’s a development that those pre-talkies 1920s visitors to Kansas probably couldn’t have imagined – but whose value for consumer research they surely would have understood.

Writing a survey is easy, right? Not so fast.

Research does take time. Like any painting or book, every time you look or read it again you have a new perspective or learning. Speed is important but so is the process of learning and understanding.

Editor’s Note: This post is part of our Big Ideas Series, a column highlighting the innovative thinking and thought leadership at IIeX events around the world. Sima Vasa will be speaking at IIeX North America (June 12-14 in Atlanta). If you liked this article, you’ll LOVE IIeX NA. Click here to learn more.

By Sima Vasa

For anyone who has been involved in the design of a quantitative research project, you might agree that the heart and soul of the project is the questionnaire. That seems like one of the easiest tasks…clients know how to talk to their customers, their employees, their resellers, etc. They know what questions they want to ask. Just organize the questions and collect the answers. It’s pretty simple, isn’t it? On the surface it feels like it should be. However, after having the experience of designing and analyzing the results of hundreds and hundreds of surveys, the reality is that is actually very difficult to design and implement an effective survey.

There are so many aspects that go into designing the survey, and the purpose of this article is to share a perspective on level of involvement and engagement required to develop a survey that will meet the goals of the research and support clients in making an informed decision. In-depth understanding of how the research results will be used, and what decisions will be supported by the project.

A successful survey designer knows the business decision being supported by the survey results. And the more you learn about the business decision, and the different inputs into the business decision, the better you can design the survey. No matter if it is a product name, product features, messaging, positioning, internal 360 review, etc., you should try to learn as much as you can. For example, for a naming study, many would want to know what names should be tested, and then be ready to design the survey. But you need to understand much more than that…what is the name the organization leaning toward, why they lean toward that name, where the other names came from, what is their naming strategy moving forward, are there different strategies being considered, are there companies’ naming strategies that they like or don’t like, etc.

The downside of not knowing this information can result in a common response from clients…we got some answers to the questions we had, but we have a few more questions after reviewing the results. Yes, this could lead to another research effort, which could be good for a supplier, but 9 times out of 10 this is not the response you want to hear. You would much rather hear that they got exactly the information they need to confidently make a decision. That is what we are hired to do, and how we can add the value that is expected.

Other factors are crucial obviously like question types to drive the right analysis, knowledge about the target respondent and overall respondent experience. However, none of these matter if we do not know the specific business decision we are trying help clients answer. It starts at the very top of the funnel.

So what does this mean?  As market research continuous to be disrupted we cannot forget the basics and underestimate the value of market insights professionals being at the “table.” The upfront discussions and interactions are crucial to understand in designing an effective survey. Too many times, researchers are tentative about their worth and do not push for the seat at the table in order to get a clear understanding of what is required. The result can be suboptimal research, providing another opportunity for other professionals within an organization to devalue the role of research in the decision-making process. We must continue to elevate our profession and the values we bring to clients in order to educate, shed light, and demonstrate the role of market research in business decision-making.

The Role of Measurement, Insights, and Loyalty in Customer Experience

Seth Grimes interviews Ipsos Loyalty SVP Trish Dorsey about her work, CX trends, and futures.

By Seth Grimes

Customer experience (CX) is the set and sum of perceptions formed through interactions with a brand, product, or service. CX starts with awareness created through advertising, word-of-mouth, and social buzz. It is confirmed in the course of online, in-store, and point-of-sale and point-of-service interactions. Central are perceptions of packaging, quality, and value, factoring in cost and relative to the competition. CX affects customer satisfaction, loyalty, and advocacy.

Ipsos Loyalty is the customer experience practice within Ipsos, a global agency that employs more than 16,000 people and conducts research in more than 100 countries. Ipsos Loyalty’s value proposition: “We specialize in all matters relating to measuring, managing, and improving customer relationships. We help our clients manage the experiences they deliver in a way that maximizes the value of customers to their organization.”

Ipsos Loyalty SVP Trish Dorsey

Ipsos Loyalty SVP Trish Dorsey

Measurement can get tricky. Modern CX involves dozens of touchpoints and feedback sources, among the latter surveys, reviews, social media, and contact centers, and analyses apply a suite of techniques that both optimize interactions and the overall customer journey, the path an individual takes from needs awareness to purchase and, in the case of a happy customer, loyalty, and a lasting relationship.

Given CX’s importance and Ipsos Loyalty’s prominence in the CX world, I’m delighted that Ipsos Loyalty SVP Trish Dorsey is speaking at the up-coming Sentiment Analysis Symposium, a conference I organize, and to have an opportunity to interview her about her work, CX trends, and futures. This interview, then, is a look at –

The Role of Measurement, Insights, and Loyalty in Customer Experience

Seth Grimes> You’re SVP East Region at Ipsos Loyalty, a global custom research agency. Would you please say a bit about your work?

Trish Dorsey> I’ve worked for Ipsos for 3.5 years and have 25+ years of experience in the research industry, across multiple industry verticals. Most recently, I have been supporting the customer experience measurement needs of the technology and telecommunications industry. This has been especially exciting for me personally, as companies in these verticals have been ‘reinventing’ themselves of late. It’s an incredibly dynamic space and that makes the customer experience challenges really fun to explore.

Seth> What do you mean by ‘reinventing’? How have customer experience goals, methods, and data sources changed in the years you’ve been working in CX?

Trish> All of us have seen the world of customer experience change. CX has become more important as evidenced by our own expectations as a consumer (thanks to brands like Apple and Amazon) and how the power of social media/the internet, etc. makes the importance of getting it right even more important. Consumers have access to more information and can make more informed decisions. Social media gives them a voice/power over brands they never had before, one customer’s feedback on a negative experience being able to influence millions.

At the highest level, I’ve seen the need for and reliance on customer experience measurement and management increase significantly in the 25+ years I’ve been in research – and at an especially aggressive pace in the recent several years. You don’t have to look far to find a CEO who will say that understanding his/her CX dynamics is one of his/her highest priorities! And the fact that many organizations are formally assigning a C-Level position to CX is even more testament to this fact. Moreover, the nature of the need and reliance has changed – no longer is it “as simple” as designing good surveys. Rather, organizations investing in CX are looking for partners who can provide research expertise, advisory services, and technology support.

Four stages and five outcomes: an Ipsos Loyalty customer experience conceptual framework (Ipsos Loyalty image)

Seth> And the data side?

Meanwhile, the numbers and types of available data collection tools have increased as well. Of course, we’ve managed the move from CATI (for most audiences) to online and now to mobile in the last 20 years or so. Add to that our continued evolution in use of other data collection capture methods, e.g., video, audio. Likewise, we also no longer restrict ourselves to structured survey responses for our CX programs. We’ve seen an increased interest in leveraging unstructured data sources – CRM behavioral data, social listening data, IVR, telemetry – to provide new data streams to provide insights around our client’s CX performance.

And all of this has happened as the availability and sophistication of technology platforms has exploded of late. No longer are we limited to back-office data collection platforms. Rather, clients increasingly require access to data in real-time; in highly visualized format; and in highly democratized ways.

Seth> Data analysis?

Trish> Of course, these dynamics mean that our analytic techniques have had to evolve as well. Certainly, we maintain analytic rigor in all that we do, but there is also increased focus and demand for real-time (or near real-time) analytics. Other than the traditional statistical frameworks, this has meant that we’ve had to invent new data science techniques and algorithms to accommodate this dynamic.

At the end of the day, all of these dynamics make the design and management of a CX program exponentially more difficult while at the same time making it more important to get right. And for those organizations who do, there is a financial gain – brands who provide a better CX have higher returns and outperform their competition in the stock market.

Seth> You’ll be speaking at the up-coming Sentiment Analysis Symposium on “Using Sentiment Analysis to Identify Emotions, Provide Insight, Enhance Customer Experience and Prevent Churn.” What emotions and what sort of insights are most relevant for your telecom clients?

Trish> I would say that we build our buckets from the bottom up by looking at which combinations of issues and emotional response have the highest impact on KPIs. I suppose that means that we don’t really use any specific model, per se.

Seth> Do the same measurement priorities apply in other industries, for instance, retail, financial services, and hospitality? I guess what I’m really asking is, how uniform are CX practices, and satisfaction, loyalty, and similar measurements, across industries?

Trish> At the highest level, the CX ecosystem we use to contextualize our measurement is the same regardless of industry. That is, this ecosystem suggests that we need to think about four levels of CX for measurement: relationship, touchpoint, transactional, operational. These levels exist regardless of industry. What might differ is how we think about the interaction among those different levels and how much measurement attention we give to each. For example, in those industries where the purchase experience tends to be more transactional (e.g., hotels, restaurants), more time is spent on event-based measurement while in industries where the experience tends more towards the relationship-level (e.g., investments, automotive) there might be more measurement at the relationship or touch-point levels.

Likewise, in terms of actual measurement, the conceptual frameworks we apply are largely similar across industries. NPS is NPS, regardless of industry, for example. The differences across industries come mostly in the types of corollary and diagnostic metrics we use or how we might design some of those. For example, in industries where there is multi-brand usage (e.g., hotels) one might use Share of Wallet as a way to measure strength of relationship, whereas in a market where usage is more monogamous (e.g., wireless phone providers), usage, total spend, or consideration might be appropriate metrics.

Measurement points and performance indicators in the CX ecosystem (Ipsos Loyalty image)

Seth> I interviewed an Ipsos Loyalty colleague of yours, Jean-Francois Damais, in late 2015. J-F is heavily into text analytics, the application of natural language processing (NLP) to produce insights from text-extracted data. What techniques are most important for you, in your work?

Trish> On any engagement, we leverage the techniques that best suits the objectives, budget, and timing constraints.

First, we take inventory of available data – what data does the client already have? – to answer the question at hand, and in what format do those data exist? If there are information gaps, we identify the best source (given budget and timing) to fill in those gaps. Who do we need input from (e.g., B2B or B2C customers)? Do we require structured survey data? Or can insights be culled from unstructured sources such as text analytics or social media listening or passive measures like online/offline shopping behaviors – this is the key to omnichannel – and so on.

More and more, however, it seems as though we are looking to unstructured, passively-collected data to address our business questions as survey response rates continue to decline and willingness to provide feedback in longer surveys wanes.

Of course, thinking about what kind of data are available is only part of the equation. We must also determine the analytic methods that are most appropriate to answer the business questions and we evaluate those methods within the context of what types of data are available. Linear regression? Logistic regression? CHAID analysis? Conjoint-based choice modeling? Text analytics mining? Etc.

Seth> Ipsos republished my interview with Jean-Francois under the title Don’t Kill the Analyst Just Yet, suggesting that human judgment and perhaps domain expertise are key assets. Has machine learning started to change your work? Or if not machine learning, are there other technologies or practices on the horizon that show promise of disrupting or revolutionizing the research and insights industry?

Trish> Absolutely, machine learning has provided new and unique tools for our analysts and the sophistication of these tools continues to improve at a rapid pace. AI is being used in many applications, for example:

  • Many companies are using AI/machine learning to know their customers and predict their behaviors.
  • Others are using AI/machine learning to predict demand for their products.
  • Still others are using AI/machine learning to manage dynamic pricing based on changing market conditions.

That said, human judgement and domain expertise remain crucial to the development of hypotheses to be tested by these models; interpretation of model results; and activation of results towards effecting business outcomes.

Seth> Thanks Trish!

For further reading, check out The Essential Steps for Building and Maintaining a Best-in-Class Customer Experience Culture, written by Trish and Ipsos Loyalty colleagues. And to meet Trish and a few dozen other cool speakers, join us at the Sentiment Analysis Symposium, June 27-28 in New York. Use the ID code GREENBOOK for a 15% discount on your symposium registration.

Making Great Advertising

The essential element to making creative - and effective - advertising.

Editor’s Note: This post is part of our Big Ideas Series, a column highlighting the innovative thinking and thought leadership at IIeX events around the world. David Ellis will be speaking at IIeX North America (June 12-14 in Atlanta). If you liked this article, you’ll LOVE IIeX NA. Click here to learn more.

By David Ellis

Turns out we’re not the rational creatures we think we are. We make most of our decisions intuitively, based on emotion and feeling. Only after our mind is made up do we build rational “reasons why” to justify the decision we’ve made already.  

For any marketer seeking to make their brand more memorable, these feelings are very important. The more creative your advertising, the more effective it is commercially. James Hurman makes a strong case for this, using lots of empirical research in The Case for Creativity.

Here are a few elements I believe are essential to making creative – and therefore effective – advertising:

  1. Start with your brand’s purpose. People don’t buy things based on a checklist of selling points. They buy stories. These often come from your purpose. Why was the brand founded in the first place? What is the job your brand was built to do?  
  2. Really understand your Consumer, Category and Broader Culture. Not just demographics and category purchase facts, but on a human level. If your advertising is true to your Purpose, differentiated from competition, and relevant to popular culture then you have the potential to make great work. A good example of deep consumer understanding for brands with Middle American consumers is the book Speak American Too, by Paul Jankowski.   
  3. Find a motivating consumer insight. Finding a motivating insight is often a marriage of Knowledge and Wisdom – the science of consumer research blended with the art of understanding human behavior. That understanding comes best from getting out of the office and into the lives of your consumer.  
  4. Watch all your competition’s advertising. Define your category advertising conventions. Then break them. If everyone shows a car on a winding road, or steaming plates of food, or long flowing shiny hair, do the opposite.  
  5. Resist the temptation to fiddle. Have great and vigorous debates with your Agency about the insight, the brief, and the creative idea. But once you’ve agreed the Idea, your job is to encourage and support great work, not to micromanage.  
  6. The best ideas are usually very simple, and often obvious in hindsight. Avoid “checkbox marketing.” The more selling points you pack into an ad, the less emotionally engaging it is, and the less likely it is to hit home. An informative guide to the art of making great ads is Hey Whipple, Squeeze This by Luke Sullivan and Edward Boches.
  7. Don’t forget your own employees, especially in a retail business. Once you have a Big Idea, start thinking right away how you can best communicate it in a persuasive and memorable way to your team members that interact with your Guest every day. As a colleague once said, “when you enter the store, you enter the brand.”

Consumers are bombarded with more advertising than ever before. But amid the clutter, there is a spectacular opportunity to stand out if you understand how the consumer makes decisions. It’s not always how they think they think. For more great background on this decision making process, read Nudge by Richard Thaler and Cass Sunstein.

Consumer-Centric Marketing is Dead

To be a truly transformative brand - one that enjoys true loyalty, passionate advocacy and a premium price - you have to be human-centric.

By Jim White, Founding Partner, RealityCheck 

I hear a lot of marketers these days say their companies are “consumer-centric.”  I used to think this was a good thing. But I’ve changed my mind. Being consumer-centric is good. But it’s not good enough.

To be a truly transformative brand — one that enjoys true loyalty, passionate advocacy and a premium price — it’s not enough to be consumer-centric.

You have to be human-centric.

The bottom line is this: Consumers don’t buy brands. People do.

And unless you understand the whole person you’re selling to, you’ll miss opportunities to play a profound and meaningful role in their lives.

Think about this on a personal level. Do you consider yourself to be a consumer? Are you nothing more than a demographic, a “user” or “non-user,” a “loyalist” or “rejecter?” Of course not. But that’s how marketers often think about the people who buy their brands. They concern themselves with only a fraction of the whole person.

This has real implications for the questions we ask in market research. And, as a result, it has real implications for how we market our brands.

A consumer-centric marketer asks “Why did you buy this versus that?” What do you think of my brand?” “What do you think of my competitor’s brand?” And so on.

A human-centric marketer asks “What’s on your mind today?” “What do you believe in?” “What are your concerns?” “What kind of person are you?” “What kind of person do you want to be?”

And then, and only then, does the human-centric marketer ask “How, if at all, does my brand fit into your life?” “How can my brand help you?”

Brands that connect with people on a human level are more relevant to them. They become part of a person’s narrative identity, the story that shapes their sense of self. They are better able to uncover the unmet needs people feel but struggle to express.

And, most important of all, they make people’s lives better, richer, easier, more interesting and more fulfilling. They speak to the whole person — not just to a fraction of that person.

So, if you work for one of those companies that is consumer-centric, maybe it’s time to push things to the next level. The human level.

It’s time to become human-centric.

Originally posted here. 

Jeffrey Henning’s #MRX Top 10: The Evolution of Happiness, Baby Boomers, and Mobile Research

Of the 3,064 unique links shared on the Twitter #MRX hashtag over the past two weeks, here are 10 of the most retweeted...

By Jeffrey Henning

Of the 3,064 unique links shared on the Twitter #MRX hashtag over the past two weeks, here are 10 of the most retweeted…

  1. Data Science Through the Lens of Research Design – Dr. Elan Sasson of Data Science Group discusses a framework for designing research projects. “Whether you implement XGBoost, random forests, HMMs, CNNs or RNNs…, if you are not addressing the concise business problem and its operationalization, you are essentially pushing water uphill with a rake.”
  2. The Evolution of Happiness: An Introduction to Happiness – Freya Vinten at Join the Dots discusses seven key drivers of happiness – Security, Health, Positive emotions, Engagement, Achievement, Relationships, and Meaning – and what they mean for Brits in 2017.
  3. Top 10 Market Research Blogs 2017 – The team at Voxpopme compiled a list of the top-ten research blogs.
  4. We’re Not from the Stone Age: A Baby Boomer Responds to a Millennial’s ‘Brutal Truths’ – Isabelle Albanese of Consumer Truth rebuts Nicholas Cole’s article “The 11 brutal truths every Baby Boomer needs to hear about Millennials” and fondly recalls what life was like before electricity and sliced bread.
  5. Moderators: 4 Tips for Improving Your Craft – Brittany Stalsburg uses her extensive experience with focus groups to provide four keys to being a good moderator: “Establish a rapport; Don’t judge; Work the room; Check with the backroom.”
  6. Open Data, What Does It Mean and Why Do We Need It? – Will Poynter at CLOSER Discovery opens up about open data and its potential benefits and pitfalls.
  7. Lightspeed Pushes Mobile First Approach – To speed the industry’s evolution to mobile surveys, Lightspeed is offering a promotion to companies that create short, mobile-friendly surveys.
  8. Cheap, Fast, & Easy – Michalis Michael of Digital MR predicts how market research will change in the near future.
  9. The ICC/ESOMAR Code – ICC and ESOMAR have updated their international code on market, opinion, and social research.
  10. Customers Prefer Bots Over Customer Service Agents for Simple Tasks – LivePerson conducted a global survey to understand consumers’ opinion on automated customer service tools compared with live human beings. “In a scenario where a bot is just as accurate as a human customer care agent, 55% of consumers said they would prefer to chat to a bot over a human.”

Note: This list is ordered by the relative measure of each link’s influence in the first week it debuted in the weekly Top 5. A link’s influence is a tally of the influence of each Twitter user who shared the link and tagged it #MRX, ignoring retweets from closely related accounts. The following links are excluded: links promoting RTs for prizes, links promoting events in the next week, pages not in English, and links outside of the research industry (sorry, Bollywood).

4 Design Principles to Help You Build More Actionable Insights

This Big Ideas article discusses four design principles that can be used to build more actionable insights.

Editor’s Note: This post is part of our Big Ideas Series, a column highlighting the innovative thinking and thought leadership at IIeX events around the world. Ingvald Smith-Kielland will be speaking at IIeX North America (June 12-14 in Atlanta). If you liked this article, you’ll LOVE IIeX NA. Click here to learn more.

By Ingvald Smith-Kielland

As researchers, one of our fundamental goals is to provide the fuel for new ideas and to help businesses innovate by developing meaningful, and more importantly, actionable insights. Therefore, it is imperative for these insights to be robust and clear enough to withstand wider distribution without being diluted or misrepresented.  

Yet, too often, these critical insights are presented in long, tedious PowerPoints, with the essence buried in text and lacking the succinctness, actionability and inspirational quality necessary for a successful adoption across departments and disciplines.

What can we learn from design to help better bridge the gap between insights and creation?

I would like to share 4 ways we have successfully leveraged design principles to build more actionable insights. I will go through these and give some additional examples in Pull’s upcoming session at IIeX in Atlanta.

1. Adopt a Collaborative and Multi-Disciplinary Mindset:

Include stakeholders from different disciplines from the start. Involving colleagues from multiple areas of expertise will help them better understand the process, build empathy for the end user and gather the necessary anecdotes to share the learnings in a more authentic way. More importantly, they will become powerful internal advocates of a user centered approach.

2. Use Reframe Statements to Articulate Insights:

While synthesizing the research and developing recommendations, it can be challenging to strike the right balance between succinctness and depth. The reframe statement is a simple yet powerful framework that can add memorability, authority and conciseness to the narrative.

WE USED TO BELIEVE -> WHAT WE LEARNED -> WE NOW BELIEVE.

The first part not only helps articulate the initial hypothesis and context, but also anchors and converges on the collective starting point of the research. The second part, the “AHA”, is then followed by a strong point of view that will be the foundation for sub-sequent recommendations.

Adding an illustration or icon symbolizing the reframe will further increase the overall stickiness of the statement.

3. Embrace Visualization to Build Empathy:

“A picture is worth a thousand words”, is not necessarily an idiom that comes to mind when describing the typical research report. In final presentations, why not replace some of the text with media more suitable for storytelling? Combining stills and videos from the field, incorporating iconography and infographics as well as building an immersive multi-sensory environment will bring the subject matter and context to life.

One of the reasons I am looking forward to attending Ari Popper’s “Is there room for Science fiction prototyping in the research industry?” in Atlanta is to further explore how emerging technology can help empathy building and increase the impact of our work.

4. Brainstorm What-If’s to Help Link Findings to Opportunities:

Developing final recommendations can be challenging for researchers and strategists: going too high level and abstract can lead to a perception of being too academic and detached from the business realities, while the opposite approach can become a solution trap where the output is a series of unresolved ideas.

Use the Reframe Statements as a springboard to brainstorm What If statements with your multi-disciplinary team. This pairing helps narrowing the gap from insight to opportunity, hinting at solutions without being prescriptive. You will then have an output that sets the team up nicely up for success and further co-creation.

I am excited to go into more detail on some of these principles and tools on June 13th.  In the meantime, if you have time, I recommend reading “The Little Black Book of Innovation” by Scott Anthony, as it covers innovation in a discipline-agnostic and holistic way, while also describing some of the design thinking principles and best practices we like to follow.

Looking forward to seeing you in Atlanta!

 

Get some GRIT: Perspective on a Research Industry Report

Sarah Faulkner shares a few highlights from the most recent GRIT Report along with some color-commentary from her own experiences.

By Sarah Faulkner

Each year, GreenBook publishes the GRIT Report, a summary of market research industry trends based on a global survey of client and supply-side researchers. The findings are always insightful and help me better understand which trends in research are really in play today and what’s coming next. Here are a few highlights from the most recent report that I think are particularly meaningful, along with some color-commentary from my own experiences.

What really matters in consumer research?

  • The number one answer here is “trust in the results”, which covers a multitude of underlying factors. It implies a strong relationship among partners, high quality sampling and survey techniques, and expert analysis. I would argue that the other highly-rated items: sample/panel quality, proven methodology, and participants’ engagement, are all just drivers of the first.

Which trends are hype and which are game-changers?

  • According to the survey, global researchers are most excited about automation, big data, and storytelling from the latest crop of market research buzzwords. I agree with automation—as noted in a previous post on industry trends, there’s a place for automating processes that are repetitive or don’t require much interpretation. The trick for smart researchers will be knowing where and how to best use it.
  • Buckets of e-ink have already been spilled on “storytelling” recently, but for research specifically, I see it as a cry from the end-users of research to make results more engaging, easy to understand and act on, and sticky for their organization. Specific ways to execute that include: a high level of synthesis in reporting (weaving together multiple data points into a cohesive narrative), the use of infographics and other graphical approaches to make data easily digestible, and the integration of direct consumer perspective (e.g. videos, pictures, quotes, etc.).
  • In the “hype” category, researchers place: AI, marketplaces, VR/AR, and attribution analytics. I can’t help but wonder if AI (artificial intelligence) lands here because people don’t know exactly what it means in a research context. If that option were to be renamed machine learning, I feel like it would shift into game-changing territory. Practical applications include: text analytics and sentiment analysis, algorithm-driven online “qualitative” interviewing, and automated facial coding/emotion analysis.

What are client’s unmet needs from research suppliers?

  • Number one on the list is “recommending business actions based on the research”, which I think is driven by two factors. One, most supplier-side researchers writing these reports have never worked on the client side so they may not know what an actionable business recommendation really means, or at least, how to frame it in a way that will be compelling within the client organization. Report writing is also typically handled by more junior employees in large research firms. A senior person might swoop in to add recommendations and present the report, but if they didn’t do the deep analysis, are they really in the best position to do that?
  • The second reason for this gap is that many client-side researchers don’t invest in developing the business knowledge of their supply-side partners. If the client is working with a massive multi-national research firm, it frankly may not be worth their time given high levels of turnover. In my previous corporate roles, I’ve trained junior supplier partners many times only to have them be transferred to another business by the time they were getting proficient in my category!
  • A good solution to this need is building strong, consistent supplier-client partnerships. Personally, I think this is easiest to accomplish with an independent research consultant (I would say that, wouldn’t I?!) or a smaller, more boutique research firm. There should be a direct correlation between the amount of time a client invests in educating a supplier about their business and the quality of their business recommendations!

You can learn more by reading the full GRIT Report (free to download). If you’re in the market research industry, I also encourage you to sign up for the GRIT Panel to participate in future industry surveys and receive advance copies of the reports in your inbox.

Generating Accurate Audience Data: Publishers’ Secret Weapon in Competition With Facebook and Google?

To succeed in attracting advertising spend, publishers need to drastically expand their ability to provide the self-declared data that Facebook, Google, and more have made commonplace.

By Kevin Gianatiempo

There is an ongoing quest to reach audiences in our multi-channel world and marketers, advertisers and brands have had to adapt to the rapidly changing landscape in the digital marketing space. No longer are marketers able to target consumers just through television or magazines. Instead, these experts have been compelled to embrace new ideas, technology and strategies. With the consumers’ shift to mobile, ensuring the right audience for a brand’s message has never been more important.

The emergence of ‘People Based Marketing’ has been a welcomed and boundless innovation, gaining immense traction thanks to businesses like Facebook and Google. With its cross-platform user profiles, Facebook has undoubtedly become the king of self-declared data.

Where are we now?

Reaching the right audience is the Holy Grail for advertisers, and web publishers in particular rely on this as their source of revenue. To succeed in attracting advertising spend, publishers need to drastically expand their ability to provide the self-declared data that Facebook, Google – and even players such as Amazon – have made commonplace.

Most web publishers have long relied on inferred data, licensed from a third-party provider running a Data Managed Platform (DMP), as they do not necessarily have the ability to regularly uncover rich, self-declared data from their current audience. Inferred data is an acceptable way to audience target, but questions about recency and accuracy persist. In fact, a study conducted by Atlas found that there was only a 65 percent accuracy rate in demographic targeting when using cookie-based measurement – that is a 35 percent error rate! This begs the question – is it even possible for publishers to compete with the current data giants?

Help is at hand  

During their data quest, some publishers have turned to third-party solutions to provide a viable way to passively track audiences to gain inferred data via surfing behavior. Unfortunately, this dynamic inevitably creates conflicts. To take one example of many, Business Insider found itself in a dispute with cross platform measurement company comScore. Business Insider published a data breakdown illustrating a monthly audience of 300 million – more than three times its comScore estimate.

Instead of relying solely on measurement companies, publishers are in the perfect position to use a lucrative source that is right at their fingertips – their own audience base. Publishers have always known that they have strong brands and credibility with their audiences. But the legacy of the print mind-set meant that many publishers have not known how to make the leap from a strong brand to premium ad rates. The answer is surprisingly simple: just talk to your readers, who are usually more than willing to divulge demographic information to support trusted news outlets. By inviting their audience to become survey panelists, using email, social media and the website, publishers are enabling their users to supply self-declared data which can be combined with inferred, to provide richer, more insightful data.

For a web publisher such as the New York Times, with around 30 million users, panelizing a relatively small percentage of that base would supply a large enough sample size to extrapolate data and create accurate insights. The benefits of creating a panel of users specific to a publisher are infinite. Uncovering more audience insights will not only benefit the publishing platform, but also help generate further revenue from the increased advertising sell. Similarly, there is the potential to create a panel marketplace, thus generating added user engagement – as both panel owner and panelist are rewarded.

Does size matter?

While publishers with millions of users can quickly generate this level of data, smaller brands may believe that their audience base will not yield substantial results. This is not the case and even modest publishers can obtain lucrative data from their users. In fact, consumer loyalty is frequently stronger with smaller brands as they are able to better connect with the audience and cultivate ongoing relationships.

Rewards are a key area where publishers can generate benefits for their audience. A publisher might attract or retain a panelist based on incentives and can create further brand affinity during this process. For a subscription-based publisher, a panelist could be incentivized via a subscription credit or several free article reads. By using a virtual currency that will benefit both parties, ‘stickiness’ and enhanced user engagement are created for the website, resulting in incremental page views and ad impressions. This in turn, feeds the cycle of creating data that will validate effective audience targeting to advertisers.

Where do we go from here?

Surveying a portion of an audience base may seem like a daunting task while also being time-consuming and expensive. The truth is, technology is a publishers’ most trusted ally. Generally, publishers are unaware of the options available to them to generate their own self-declared data.  They are sitting on a gold mine of insights and just need to implement the right mining tools to unearth the benefits. When first-party, self-declared data insights are combined with inferred data sets, the result is more relevant audience profiles that can be used by brands for accurate ad targeting – and that is how publishers can compete with the data giants!