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What The LRW Investment Means For The Market Research Industry

I interview David Sackman, CEO of LRW, on their just announced successful capital raise.

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Today Lieberman Research Worldwide announced the successful raise of significant growth capital from Tailwind Capital, a private equity firm. This marks the first time LRW has raised outside capital, and the latest in a series of significant PE-backed moves in our category (previous notable examples include deals for Research Now, Macromill/MetrixLab, SSI, and Focus Vision).

Before we jump into my take, here is a snippet of the press release for details

Los Angeles – LRW (Lieberman Research Worldwide), a leading market research and data analytics company, announced it has raised significant growth capital from Tailwind Capital, a private equity firm focused on investing in growth-oriented middle market companies. This capital will be used to drive LRW’s innovation strategy and vision to be the leading integrated data analytics research and marketing strategy consulting firm. This capital infusion will help LRW more rapidly develop and expand its suite of innovations in the areas of Pragmatic Brain Science®, virtual reality, social media analytics and big data. The capital will also be used for targeted acquisitions to strengthen LRW’s global footprint and leading edge capabilities in the “new” market research industry. The current management team of Chairman and CEO Dave Sackman and President, Jeff Reynolds will continue in their current leadership roles and remain significant owners of the business. Terms of the transaction were not disclosed.

Dave Sackman, Chairman and CEO of LRW said, “The market research industry is at an inflection point, and we see tremendous opportunity. Our partnership with Tailwind will enable us to innovate even more rapidly than we have the past few years and to meet the changing needs of CMOs and their marketing organizations. The world of data and digital marketing is growing exponentially, and with growth capital, we can shape that future. We fully intend to be recognized years from now as one of the pioneers and true leaders in creating what people are now calling the ‘new MR’ and we’re calling Integrated Data Analytics Consulting.”

Adam Stulberger, Partner at Tailwind, said, “This transaction represents a tremendous opportunity for Tailwind to invest in a proven winner that provides high quality services to a dynamic industry in the midst of a transformation. LRW has a very experienced management team and is well-positioned for future growth and expansion. We look forward to supporting LRW as it pursues future organic initiatives and acquisitions.”

LRW is recognized as one of ten most innovative firms in its industry and is one of the top 25 largest marketing research firms in the world.  Since 1973, LRW has been providing its data-driven consulting services to management teams of top global brands on issues such as strategy, branding, communications, new product development, and customer experience.  LRW leverages its unique “so what?®” consulting model, sophisticated marketing science capabilities and recent innovations in Pragmatic Brain Science® to deliver real business impact for their clients across a wide range of industries, including entertainment, pharmaceutical, technology, consumer packaged goods, health care, retail, food service, financial and business services, automotive, and many more.

The LRW deal stands apart for one important reason: this is the first time in this latest wave of interest in MR that a primarily service-focused consultancy has raised capital to pivot to a combined technology and services growth strategy. LRW has certainly invested significantly in the last few years in technology (their VR and new BX offerings for example), but now they are poised to begin acquiring new technology capabilities that they can provide a service wrap around to, and perhaps even more importantly, leverage multiple data sources for a holistic data synthesis offering, which is an important distinction. The combination of globally leading consulting human capital, a developing contextual framework for data analytics, and a mix of proprietary technology and smart tech partnerships is a forward looking formula for success.

Will LRW pivot as a tech play? No, I don’t believe so, but they obviously are focusing on the intersection between consulting and technology (specifically around data that drive insights) and I think that is where the future of the industry lies.  Increasingly we are seeing the demand from clients on pure tech / self service offerings to augment with a service solution. Just as most consultancies can’t fully pivot to tech companies, pure tech companies can’t pivot to service organizations either: new hybrid models are necessary to meet the need.  This new SwaS  (Software with a Service) category is likely to be one of the major trends in the research space over the course of the next five years and is a smart play across the board.

I had the opportunity to chat with CEO Dave Sackman on the news of this deal and get his view on what it means for LRW and the industry as a whole. It’s a great discussion and one that everyone should pay attention to, since LRW is now poised to become not just one of the smartest companies in our space, but also likely one of the largest. Here is the interview:

 

 

One last take away from this deal: Private Equity money continues to be available in this space and many investors are looking for opportunities. If your business fundamentals are strong, you have a proven track record of success, and are making the necessary changes in your business to remain not just competitive but to actually lead with innovation that delivers real business impact then you can find deals. Despite all the myriad dynamics impacting our industry, it’s still a great time to be in the insights space  as LRW just proved yet again.

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8 Reasons Your Company Needs an Open Data Strategy

Emily Fullmer discusses the multitude of benefits that an open-data platform could provide for your company

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By Emily Fullmer

Data seems to like reinventing itself. We’re still in the midst of  ‘data’ becoming ‘big data’, while also coping and learning to capitalize on data as an asset class. And yet, we are faced with yet another simultaneous data revolution—the Open Data Economy. 

As a reader of the GreenBook blog, I know you either strive to be an innovator, or already are. For this reason, I urge you to consider exactly how the forthcoming restructuration of data will impact your firm, your competitors, and your value offering. As 2015 takes off, what will your Open Data Strategy be? Will your firm be proactive or reactive? You need a game plan. Here’s why: 

1) Data-as-a-service model

The entire concept of open data may seem counterintuitive to the private sector. Giving away data means giving up both earned and proprietary information, and putting it into the hands of competitors. But opening up your data portals doesn’t mean you have to open up all the floodgates—consider using your most basic data as a ‘hook’ for attracting new clients. SaaS business models are thriving by offering subscription and ‘freemium’ pricing models. Why shouldn’t it apply to data providers as well? The concept of data-as-a-service will become increasingly applicable to businesses that capitalize on merging government data with their own proprietary information.

2) Crowdsourced solutions

Crowdsourcing platforms have recently proven their value in a variety of spaces. For data, the possibilities of crowd-sourced solutions are endless. Platforms like Kaggle are bringing together self-proclaimed data scientists and hard-to-crack data sets. Organizations such as GE, Expedia, and Liberty Mutual sponsor challenges backed by cash rewards. In response to a challenge being posted, as many as 1,300 teams submit their predictive models.

The solutions being created are faster, more innovative, and of higher quality because an entire world of data scientists is being tapped, rather than a single department, individual, or algorithm. Crowd-sourced solutions should have a prominent role in your open data strategy, but the extent will depend on exactly how much information you’re willing to share.

3) Attract higher quality talent

When predictive models and solutions are submitted through crowdsourcing platforms, quality talent sets itself apart from the pack quickly. Instead of chasing the best and brightest, and then gambling on their expertise, why not let them identify themselves?  By attracting talent through this method, you can avoid the cost of hiring a full-time team and acquire the winning individual(s) before the competition discovers them. 

4) Contribution to a more efficient economy

It needs to be clear what the Open Data economy is and is not. It is an ecosystem, where every stakeholder benefits in some form. It is not Data Philanthropy (a noble cause, but a smaller concept within the whole mentioned below). By making your data public in some form, the entire ecosystem becomes more efficient, and thus, more profitable. McKinsey & Co estimates that there is approximately $3 trillion USD in “potential annual value enabled by open data in seven ‘domains’”. That’s a figure that would make anyone into a believer.

5) Better storytelling

A subset within the Open Data Economy is Data Philanthropy—the UN describes the neologism as “a new form of partnership in which private sector companies share data for public benefit”. It might not be the most glamorous way to give back, but sharing seemingly useless data sets could have profound social benefits. The UN cites, “academic researchers have shown how cell-phone location data was used to understand how human travel affects the spread of malaria in Kenya, while mining of anonymized Yahoo! email messages provided a detailed view of international migration rates.” Anecdotes such as these lead to far better material for compelling and organic press. And by capitalizing on your current assets and internal digital humanitarians, there’s no need to waste resources on campaigns that often negate the credibility of intentions.

6) Rejuvenation of innovation

In the MR space, innovation and tech often go hand in hand. At conferences like IIeX, we are often drawn towards the disruptors who have tangible, foreign technologies. We sometimes forget that innovation doesn’t always have to be hi-tech. By leveraging this new economy, innovation can emerge in the most unlikely of partners and situations if you allow yourself to be found through your data. 

7) Leadership positioning

Buying your way to the top of the thought ladder is becoming a thing of the past. Take a proactive role in accepting and understanding the open data ecosystem landscape. Strategize and position yourself within it now. What value will you be offering? What value will you seek? Early adopters will be rewarded through both value and leadership status. 

8) Unlock new value

It’s time to dust off our old data sets, and realize we have a hoarding problem. What’s the point of sitting on old data, while it depreciates in value? By sharing and publicizing the analysis and trends of the data you own, you open yourself up to others who may have complementary data that allows both entities to create new value from old data.

Still not convinced? Take a look at the McKinsey and Deloitte Open Data Reports for in-depth reads on the subject.

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The Rise of Machines: Is DIY Going to Eliminate Your Job?

Sami Kaipa of GlimpzIt reflects on how DIY research tools have quickly taken the industry by storm.

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By Sami Kaipa

As we bring a fully self-serve GlimpzIt offering live to the market in the next few days, I’ve had the opportunity to reflect on the revolution that is DIY research. The value of DIY research tools in a word – TREMENDOUS. I don’t think many sensible individuals disagree at this point. The concept of DIY, even just a few years after its birth, doesn’t divide market researchers like it had before. There is a very safe niche for full service market research professionals amidst the indispensable tools on the market – that niche is to use these tools to more effectively make sense of the world. And smart researchers and marketers get that. These tools help researchers do more, faster and better, and they help marketers do research that was otherwise untenable.

Today’s DIY tools accomplish varying degrees of work. In some cases, they help with data collection, in other cases, with data categorization and organization, and in some cases visualization. In other extreme applications, they do almost “human like” tasks like making sense of unstructured text. The fact still remains, however, that they make practitioners’ lives easier in all cases. A sensible data scientist running factor analysis these days wouldn’t think of proceeding without excel, or a calculator at the very least. These tools make his task far easier. A qual researcher, similarly, should consider the use of sentiment analysis tools, because, if you believe in their efficacy, they can make tasks far easier for the same reasons.

Ok, enough with my diatribe on why we should use DIY tools. We all get it right?

Well, I’m pleased to note that most people do. My experience at the North American Insight Innovation Exchange Conference in Atlanta this year was reassuring. When describing GlimpzIt, I could freely use terms like DIY, self service, or self guided with confidence, knowing that folks understood our offering and even more so, our value prop. Contrast that to just over a year ago at IIEX 2014 Amsterdam, when you could hear a scornful murmur in the crowd when Paul MacDonald from Google talked about how Google Consumer Surveys could help bring cost effective research to small businesses. Moreover, I didn’t sense the same sort of fear around losing business or even more personally, losing your job. That underlying sentiment seemed to permeate the Amsterdam conference center, and certainly still continues to at other conferences like CASRO.

It takes only a slightly deeper study of DIY tools to appreciate their value even more, and realize that they make all of our jobs more productive, not obsolete. During my exploration of the more common DIY tools in the insights space, I learned quite a bit about DIY strategies and their respective value. Let’s take a quick look:

Survey Tools:

SurveyMonkey, Qualtrics, Google Consumer Surveys – these are the giants and pioneers in the space and we all know what they do. The take away from these services is to make products valuable and applicable to researchers, but also accessible and usable by non-researchers. A marketer or product developer in the past, who might be completely unfamiliar with executing a survey, now has that potential, and that’s a good thing!

Marketplaces:

Zappistore, Qualtrics, CoolTools – they provide platforms for companies to submit their products for researchers to pull off the shelf and use independently. As an example, you might buy a “standard” NPS test where the question is pre-formulated, the survey is pre-programmed, and everything is executed for you automatically, all online. From these offerings, we’ve learned that DIY tools should strive more for turn-key solutions. We don’t need to stop at just delivering a function. There is merit to layering methods, analysis and presentation into our DIY offerings to make them more valuable and complete.

Other Somewhat DIY Solutions:

GutCheck – based on client needs, they make research methodology recommendations and are able to pull the appropriate “products” off the shelf to meet these needs. The learning from this strategy is that solutions that mix consulting and automation are just as effective, if not more so, than DIY alone.

DIY Panel:

Google Consumer Surveys, Branded Research, TAP Research, Cint, Federated – through the use of online web apps and APIs, anyone with some basic computer programming know how can recruit sample and achieve completes – no need for professional services anymore to confuse us with terms like LOI and incidence.

Passive Analytics:

Google Analytics, Kissmetrics – perhaps we don’t think of these tools as research, but their value is clearly aligned with the goals of many researchers, i.e. to understand consumer behavior and help with making more informed business decisions.

Our own tool, GlimpzIt, is used in scenarios ranging from ethnography and ideation to issue identification and political message testing. Cool stuff right? Sure, but we have a lot to learn from our predecessor DIY brethren. As a starting point, we adopted a similar vision – to democratize our brand of insight generation; make visual conversations accessible to anyone, regardless of job role, expertise, and budget.

I am happy to see the direction in which the industry has evolved just in a matter of a few short months. Its my firm belief that, as these tools get better and researchers get more comfortable using them, their use will become even more widespread. It’s time we sharpened our resolve to innovate, not dust off our resumés. With less time spent on the mechanics, the door is wide open for researchers to focus more on revealing deeper insights and deriving innovative methods to get to them.

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The Technology Dilemma

We live in a tech-centric world. It is challenging and revamping almost every brand and industry, and market research isn’t immune to this change.

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By Zoe Dowling

We live in a tech-centric world. It is rapidly changing how we live. It is driving cultural change. It is challenging and revamping almost every brand and industry, and market research isn’t immune to this change.   The Insights Innovation Exchange (IIeX) conference, held in Atlanta 15th–17th June, demonstrated just how much technology has infiltrated our industry. Not only did the conference have a disproportionately large tech presence, its parlance infused many sessions with references to ‘lean’ and ‘agile’ approaches to ‘hacking’ solutions and ‘start-up’ mentality.

Technologies providing automation and computation are leading forces, followed closely by those providing access to consumers, be it as a sample source or a means to connect directly with them. The question then becomes how to leverage these technologies, how to innovate in this new order. And how to do so with the same refrain of ‘better, faster, cheaper’.

In one of the opening talks, Reality Mine’s Rolfe Swinton talked about the exponential growth of massive computing power, coupled with the trend towards technology becoming nearly ubiquitous and nearly free. This inadvertently hits upon a Catch-22. Technology is powerful and cheap, comparatively speaking from 10 or even 5 years ago. Furthermore we, as consumers ourselves, have become used to getting technology for free.  How many of the apps on your phone did you actually pay for?

This hides a truth that while the technology may be freely available via open source code or inexpensive off-the-shelf packages, customizing it to meet research needs takes specific skills, time and financial resources. This quickly removes free, and even inexpensive, from the equation and yet talk of better, faster, and cheaper prevails.  TNS’ Kris Hull suggested that a language disconnect between clients and agencies is a factor. When clients hear innovation, they are hearing ‘faster and cheaper’ but the agencies saying it are actually implying ‘upfront investment’. There needs to be more upfront conversations around the real cost of implementing these new technologies.

More broadly, it feels like the word ‘Innovation’ has become the ultimate buzzword. There are continual cries around the need for the industry to innovate or that we aren’t innovating fast enough by adopting all the new technologies available. This skirts over the gritty truth that innovation isn’t easy, even beyond the simple financial constraints. It was encouraging (perhaps even comforting) to hear some focus on this reality. Lisa Courtade, Merck & Co, spoke directly to the point that innovation is hard. It requires focus and tenacity. We need to ‘do it again, and again, and again’ before we’ll get it right. Another refreshing talk came from Lowes’ Tanya Franklin who highlighted the need to build a culture of innovation in order to be successful. This means bringing in the right skillsets and individuals to do so.

So what should we take from this? The first is to celebrate that there are a lot of exciting, and very worthy, technologies for us to employ. The second is to openly acknowledge that employing them involves a lot of hard work as well as significant human, financial and time investment to get it right.

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Cannes Innovation: French Taxi’s vs Uber

Stephen Phillips from ZappiStore, one of the Unilever Foundry's top fifty Global Marketing Start-Ups, details his experiences in Cannes at the Festival of Creativity.

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By Stephen Phillips 

To get to the festival you land in Nice Airport and get a taxi to take you the 30 minute drive along the coast to Cannes. Or at least that is what you normally do but this being France there was a simultaneous taxi and rail strike. The taxi’s were protesting against Uber and the train drivers were presumably protesting against roads. Anyway, it meant the journey to Cannes required pushing yourself onto a bus on the side of the road and hoping it was going in the right direction as surly taxi drivers tried to stop anyone from picking people up on the side of the road.

We were going to Cannes to join the Innovation section of the Cannes Festival of Creativity. The main conference lasts 5 days and includes all the great and the good (and others) from the advertising industry. This is the first time they have run an Innovation offshoot and it was on for the last 2 days of the main conference. ZappiStore was included as one of the Unilever Foundry top 50 global marketing technology start-ups so we headed into the festival excited to find out where technology was leading the industry.

The 2 days included various speakers from futurists, technologists to business leaders and F1 drivers (David Coulthard who, suffering like us from the transport crisis, drove his wife’s small electric car from his home in Monaco).

The VP of Advertising from Domino’s kicked things off as she talked through how technology was changing their business completely. She described how Domino’s had gone from a small technology department and a big marketing department to a much smaller marketing team but with a large technology group driving the business forward through innovations in customer service.

Over the two days there was a lot of talk about AR and VR (augmented reality and virtual reality of course!) and how they would change culture, society, people and everything else. Having promised much ever since the mid 1990’s, it does seem that VR may be hitting the mainstream soon and when it does so it is predicted to have a big impact on marketing. Unfortunately no-one seems sure what that impact will be but from a research perspective there seem some obvious uses from shopper simulations to car clinics.

Another theme was people based marketing. Instead of predictive based technologies which are suffering more and more from the decline in cookies (due to them not being on mobile), campaigns need to be based on real information about individual users so that completely targeted messages can be made. This in turn requires real time advertising creation, driven by technology, so that ads can be tailored to specific people, at specific times, in specific situations with specific offers. Surely this should be a boon to the research industry, assuming we can manage the real time, targeted testing required.

Machine learning (or AI to some folks) also came up with the IBM Chief Strategist discussing how Watson could help answer the marketing industry’s core questions. Given this fast changing technology landscape, several big brands talked passionately about how they were partnering with innovative start-ups to learn together about how to navigate through this new landscape. VP’s from Mondelez and Unilever talked about their companies approaches and of course Unilever have taken this as far as running the Foundry 50 program as a way to specifically engage with as many new ideas as possible.

Finally there was a lot of discussion around the role of creativity in this new, high tech world. This argument seemed odd to me as companies like Uber have shown a great deal of creative thinking but I think the creatives who are concerned are the old school advertising creatives who probably also think that they have a monopoly on creativity!

This being Cannes there were lots of parties; on beaches, islands, yachts and penthouses. We did manage to get into a few with help from our friends at Millward Brown. The highlight was a party on a yacht provided for by a technology company that was apparently young, rich and clever!

By the time it came to leave the Uber strike was over but the Uber drivers were nervous still and mine asked me to sit in the front with him and pretend we were friends. On the trip back he lamented the overpaid and protected taxi drivers and asked, rhetorically speaking, how on earth they can try and just stop progress. This seemed an apt description of some of the thinking we can come across in the research world, and so the thought I left with was are we in the research industry with Uber or with the French taxi drivers? Mind you, the overpaid, underworked taxi drivers did at least get to spend more time on the beach than I did, maybe they are getting something right after all!

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Consumer Insights Lead to Activation: Q&A with MotiveQuest’s Brook Miller

Seth Grimes interviews MotiveQuest CTO Brook Miller in the run-up to the next Sentiment Analysis Symposium conference, taking place July 15-16 in New York.
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Editor’s Note: Seth Grimes is the true guru of the world of Text and Sentiment Analysis, and today’s post is one of the reasons why: he is intimately connected to the movers and shakers in that space. Similar to our own IIeX events, Seth’s Sentiment Analysis Symposium conference, taking place July 15-16 in New York is a MUST attend event for insights professionals who want to stay on the cutting edge of this exciting space that has such a profound impact on market research. I encourage all GBB readers to go if you can, and you can get a 10% registration discount with the code GREENBOOK.
By Seth Grimes 

Brands search constantly for consumer insight, seeking to understand customers, prospects, and market directions and to discern what works in creating desire, response, satisfaction, and loyalty. These latter concepts seem straightforward, yet they’re not so easy to compute. Measures that are typically applied, for instance the Net Promoter Score, paint an over-simplified picture based on attitudes rather than actions; they lack predictive ability. The prevailing method of studying actions, in the online world at least — digital analytics — falls far short due to lack of explanatory power. And these methods provide what are in essence point-in-time measurements. They record only a small portion of an often-extensive set of customer interactions that occur across multiple channels over time, the customer journey.

Brands get better answers, according to insights agency MotiveQuest, via study of motivation and advocacy. We inhabit a big data world; we’re entering an Age of Algorithms. Insights voodoo doesn’t cut it. Instead, marketing science dictates application of a rigorous analytical framework, and clients demand that findings be presented in useful form, translated into useful, usable strategy. Technology including text and sentiment analysis is a key element, but in the words of MotiveQuest CTO Brook Miller, “We’ve done interesting work to understand the emotional states along the customer journey, but it always has to come back to making it actionable for our clients.”

Brook Miller, CTO at MotiveQuest

I interviewed Brook in the run-up to the next Sentiment Analysis Symposium conference, taking place July 15-16 in New York. Brook will be speaking; his talk is titled “Segmenting Advocates to Develop Marketing Strategies and Communications.” As a preview, here’s an —

Interview with MotiveQuest CTO Brook Miller, on brands, listening, insights, and value

Seth Grimes> In just a few sentences, what does MotiveQuest do and how do you do it?

Brook Miller> MotiveQuest delivers consumer insights to our clients to help them improve their communications and marketing strategy, as well as uncover new consumer segments and product opportunities for growth. Our strategy team uses our proprietary software tools to listen to billions of organic consumer conversations happening across online communities and social networks, and then turn that data into insights, opportunities and recommendations.

Seth> I see three judgments implicit in the Web-site statement, “At MotiveQuest, we leverage custom curated consumer data from online communities to help our clients see the world through their customers’ eyes, by listening, not asking.” I read into that statement that MotiveQuest is dissing surveys (that is, asking), open-social listening (given that you favor communities), and uncurated data. So where and how, exactly, do surveys and social listening fall short?

Brook> Is it ok to use the word “dissing”? This is fantastic! Expect to hear that during my presentation at the Sentiment Analysis Symposium.

Our approach delivers the qualitative nature and deep understanding of focus groups at tremendous scale and we can do it faster and more efficiently. Surveys have their place; for example consumers rarely talk about advertising unprompted, so if you need to test a specific copy or creative some sort of asking based research will be involved.

Our listening research can also be very complementary to traditional. Many of our clients find that traditional research methods are much more powerful after they’ve engaged with us to identify better questions and even new consumer segments to evaluate. Then they are able to direct additional quant and qual into sizing and clarifying opportunities. In some cases, we’ve even partnered with technology enabled “asking” based research companies to provide our clients with a holistic view of their consumers by combining asking and listening research at scale.

Over the last 10 years there’s been a tremendous expansion in the number and type of social channels and we absolutely use the broad social networks to inform our analysis, but the communities with consumers talking back and forth with each other (typically outside of the brand / company’s influence) gives us the best fodder for deep understanding. A lot of our analysis starts with the perspective of consumers / category rather than looking at the brand.

What sort of signals do you look for in the data, that is, what do you measure and how do you transform what you measure into insight?

Typically we’re casting a wide net to surface the key topics and drivers for consumers in a given category and then we’ll want to see how those ebb and flow over time. We’re looking for the dynamic trends and interesting changes that our clients can act upon. We really try to not get too bogged down in all the “interesting” data but to focus on data our clients can use to make decisions and move their businesses forward.

One more inference from that Web-site snippet: Does “[we] help our clients” imply that do-it-yourself doesn’t deliver for brands, even for the majors among MotiveQuest’s customers? Or is the crux of the matter not capability but rather the degree of access clients are allowed to core assets such as the curated customer data and analytical framework?

Have you ever seen someone that worked in I-Banking at Goldman Sachs build a financial model? I’m pretty handy with Excel, but at Kellogg [School of Management] I’d just be opening the file and they’d already have 15 tabs with a 3 year forecast completed. Our strategists spend more than half their week deep into our software utilizing our existing or building new frameworks to understand consumers.

Our best clients are looking to push their businesses forward and while the insights we deliver are a part of that, they also have to execute, manage, plan, etc. We deliver the insights with recommendations for our clients to act upon, which we think drives a lot more value than just a toolset.

Your SAS15 talk is about segmenting advocates. How do you define an advocate, what sorts of segmentation deliver value to clients, and how may that value be measured?

Advocacy has been a linchpin of our ability to provide insight for the last 8 years. We worked in conjunction with professors from Northwestern to build a model tying the people promoting brands and products to others to sales and share. I think it’s an accepted fact that the most effective promotional channel is word of mouth from people like you and with our tools, we’re able to listen in on the online set of these conversations, that have always taken place.

Once we understand advocates, we can break them apart by interests. Is this person a Gamer or Mom, or both? For each group which driver is more important: customization or price?

I think the segmentation depends a lot on whether our client is trying to find white space for a brand extension or a hook to spur their social campaign launching next week.

A recent MotiveQuest blog post stated, “Brands that stand tall for something have many advantages, the most important of which is a strong emotional connection with their audiences.” The focus on emotional connection is really interesting. What technology and methods do you apply to discern, measure, and exploit emotional connection?

We’ve built frameworks and linguistic sets of the ways in which people express emotion as a pretty standard part of our toolkit. We’ve done interesting work to understand the emotional states along the customer journey, but it always has to come back to making it actionable for our clients. Knowing that people are “frustrated” in customer service is not so helpful. Knowing consumers are 10x more frustrated with wireless carrier A vs. wireless carrier B’s customer service can start to spur some action. Being able to then unpack that frustration into topics can create the need for change as well as a recommendation for what that change should be.

Seth> What role does data visualization play for you and your clients?

A MotiveQuest visualization: Emotions detection for brand-category understanding

I will probably sound like a luddite, but line charts, bar charts, x-y plot with straight forward axis make up the majority of what we do. We employ stream graphs, clustering, heat maps and force directed diagrams as part of our toolset but try not to include those just as eye candy in our work for clients. We see a lot of “interesting” visualization ideas but are often left scratching our heads by the ambiguity the visual creates and we ask, “why didn’t they just use a bar chart?”

Where are you heading next? What would you be measuring if you could, that you aren’t already measuring? Are you working to bring new or improved algorithms to bear on the customer-understanding challenges?

The visual web is fascinating, and we utilize a lot of the imagery that consumers create to bring our ideas to life, but going beyond “does the visual have a logo in it?” or counting how many times a particular visual meme is shared in an automated fashion, to be honest I don’t know exactly what that will look like yet. We’re certainly not ready to extract emotional states from imagery… (Google might be, if you haven’t used their photos app, you have to try it.)

I think we’re still on the precipice of what value can be delivered through listening insights. Rather than innovation in methodology, I think I’m most excited by innovation in the marketing organization and process, such as what happens when we’re able to deploy a lean start up approach to the marketing org.

If we can build a virtuous cycle where consumer insights lead to activation ideas that get piloted and then scaled across marketing channels, I think we can usher in the new era of agile consumer research, leading to more effective insights, and marketing tactics.

Again, hear directly from Brook at the July 15-16 Sentiment Analysis Symposium in New York. Attend either of the two days or both, and mix-and-match attendance at presentations — our speakers represent Instagram and Affectiva, Verizon and Lenovo, Face Group and Cision, IDC and Forrester Research, and many others — and at longer-form technical workshops. And stay tuned, by following @SentimentSymp on Twitter, for additional interviews in this series.


An extra: MotiveQuest CEO David Rabjohns’ 2014 Sentiment Analysis Symposium presentation, Mapping Human Motivations to Move Product…

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The Top 10 Challenges in the Market Research Industry

The 10 biggest challenges in the market research industry according to the most recent GRIT study.

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In the most recent edition of the GRIT report we continue to explore how the research industry views both Challenges and Opportunities, and so we employed numerous open-ended questions on the topic. To further develop and advance our knowledge, we used a combination of automated probing during the survey as well as text analytics during analysis to delve deeper into respondent answers.

The 3 biggest challenges researchers feel are facing the industry can be bucketed into these groups:

  • Impactful reporting: The ability to provide or receive consultative reports, to tell a cohesive story, and account for all the pieces of the puzzle in the client’s world,
  • Technology: Its introduction, use, and reliability to answer business questions in more efficient or creative ways, and
  • Data Management: How businesses gather, handle and integrate the vast amounts of data– from both primary and alternative research resources to make sense of all the data points.

MR Challenges

 

Client-side researchers place the most emphasis (40%) on getting actionable reports that relate directly to their business needs, followed closely by the management of data (37%) – specifically the marrying of Big Data and all of the information about their consumers into relevant business processes and systems.

Being able to successfully develop behavior models or provide a forecast for the business based on the data that is available (and cheaply procured) will prove to be the most fruitful for this group. Until then, they are relying on their suppliers to provide better forecasting and recommendations that speak clearly to them and their stakeholders. When done effectively, these researchers feel the research is;

“Connecting the dots – bringing together all of the insights we have to have clear, thorough, and actionable insights, which are brought to the stakeholders in a way that is easy for them to understand both the insight and what action should be taken by us.”

Conversely, suppliers are placing the greatest focus on technology (45%), not only as a means for embracing newer trends and to enhance differentiation, but also as a way to deal with the ever-shrinking timelines and budgets that impact the quality and delivery of their research.

They understand that there are great benefits when technology is used well, but there are also costs associated with its proliferation.

“The rapid change in technology. Everyone wants to be doing the new stuff yesterday and much of the new stuff becomes obsolete very quickly. Mobile devices have created both exciting positives and nasty negatives for the industry. The way we deliver findings to clients is becoming challenging too. Taking on or considering new software. Changing some of our processes.”

Top 10 themes in response to the question, “What do you feel is the biggest challenge facing market research in 2015?”

There was an immense amount of richness in these responses, so although in the preceding section we delivered a comprehensive summary of the overall responses, we also thought it would be instructive to dive deeper using advanced text analytics to explore some of these themes more fully. We found 10 themes that emerged.

  1. Methodology

56% of respondents mentioned the methodologies of market research as one of the biggest challenges they face.

  • Using social media for data collection and analysis
    • Data is clunky, messy, and full of garbage
    • The “now what” factor: What are you supposed to do with social media insights?
    • There is no way to quantify the qualitative insights
    • No one in the organization is trained to do the interpretation of the data (i.e., there are tools that quantify SM data, but there aren’t enough researchers who are skilled at teasing out the useful information and making decisions based on that information)
    • Researchers generally get push-back from organizations that are resistant to change and skeptical of social media
  • Response rates:
    • Generally low response rates, waning participation
    • Difficulty getting respondents to be cognitively engaged: There is a sense that consumers have lots to say about products and services, but they are so bored by surveys that they won’t participate
    • Lack of representativeness: we’re only sampling the kinds of people who are likely to be interested in taking surveys, participating in panels, etc.
    • Consumers are bombarded with too many surveys; don’t take any of them seriously
  • Too many competing techniques
    • Researchers are often juggling various tools that their company is testing out
    • Don’t receive enough training to become proficient at any of these tools
    • These tools often provide vastly different results on the same data set, rendering interpretation challenging and actionable insights difficult to find
  • Privacy and security issues
  • Getting data is difficult because of government regulations about privacy
  • Modern consumers are becoming increasingly more private and more suspicious of research organizations asking them questions about their thoughts/feelings/behaviors. This causes them to opt out of surveys, panels, interviews, etc.

 

  1. Clientele

29% of respondents mentioned that one of their biggest challenges is dealing with their customers and clients. This topic often co-occurred with other topics in this report, meaning that when respondents talked about clientele, they were often likely to talk about one or more of the other topics in this document.

  • Customers expect insights far too quickly
    • Big companies have trained customers to expect insights quickly. Researchers who are interested in precision over speed cannot compete
  • Customers have dwindling budgets for Market Research
    • This leads customers to prefer low-cost, low-quality insights that don’t benefit them
    • Customers feel that they can save money by interpreting the data themselves
  • “Insight schizophrenia”
    • Customers have constantly changing needs and are always chasing the next shiny object
    • They are seduced by high-tech solutions that are expensive and not scalable
  • Clients want market researchers to find ways to replicate the expensive, high-tech solutions in a low-cost, scalable way
  • Customers cannot articulate what they want/need, and when they finally do articulate their wants and needs, those wants and needs change quickly. Market research feels like a constant game of catch-up with a non-focused customer
  • Customers need to be re-educated but are resistant
    • Need to learn that expensive, accurate data is indeed more valuable than inexpensive, shoddy data
    • Due to the conflation of (1) low budgets and (2) customers’ perception that they are skilled enough to interpret their own insights, customers are resistant to re-educating themselves

 

  1. Outcomes

25% of respondents mentioned that poor market research outcomes are the biggest challenge in 2015.  The top themes in this category were:

  • Lack of actionable insights
    • Insights are sparse, disparate, and difficult to interpret (e.g., “the ability to turn research into valuable and actionable insights. Much of research is not used because it is difficult to make actual decisions based on the outcome of the research”)
    • There is the perception that suppliers and customers are often at odds when it comes to interpreting the data. Market researchers perceive that they are seeking the “truth,” while their customers are seeking confirmation of what they want to believe about their company, brand, product, etc. Making good decisions based on the data is challenging if there is utter disagreement
  • Lack of timeliness
    • Businesses are moving too fast and need their insights immediately. Data scientists and market researchers cannot keep up with the demand
    • Even tools that promise to speed the data collection and interpretation process cannot meet the high-paced standards of businesses today
  • Lack of honest/integrity by data insights providers
    • Businesses feel that many market research data providers promise great insights but usually fail to deliver (e.g., “Most companies talk a good game, but are not able to execute on the analysis of big and small data.”)

 

  1. Technologies

22% of respondents mentioned that their biggest challenge is the new technologies used in market research.  The biggest issues relevant to technologies were:

  • Big data
    • Big data has become a buzzword and every client wants market researchers to do something with it. However, many market researchers are beginning to perceive that no one really knows how to best handle big data
    • Big question: Does big data actually gather a better, more comprehensive picture of who the consumer is? Or is it just one more data point that causes confusion?
  • Mobile technologies
    • Computer-delivered surveys and data collection methodologies are on the way out. They are clunky and static.
    • Tomorrow’s research design involves mobile, dynamic methods for data collection that gather real-time, in-situ information
  • Social Media
    • See Section 1a

 

  1. Differentiation

21% of respondents mentioned that the biggest challenge they face is trying to differentiate themselves from a sea of competitors.

  • Demonstrating unique value
    • So much information is available that it’s difficult for a market researcher to show that there is unique value and novel contribution in his/her approach to MR
    • Customers are inundated with so much information that it is difficult to tease out the signal from the noise
  • Staying relevant in changing times
    • There is always the new up-and-comer that is sexier than you
    • You must become a jack of all trades and a master of none
  • Avoiding commoditization
    • Market researchers are concerned about becoming “just another seat at the table”
    • Market researchers perceive that market research is somehow simultaneously sexy and yawn-worthy: New technologies and exploratory methodologies make the field exciting and new, but because supply is so high, market research is viewed as a commodity and therefore is less interesting
  • In light of that, how to keep your sex appeal?

 

  1. Quality

14% of respondents mentioned the quality of data, quality of respondents, and quality of insights as their biggest challenge to market research:

  • Samples are not representative
    • Researchers mentioned that they often use suppliers to bring representative samples to them, but feel that these suppliers do not follow through
    • There is confusion around how to get a truly representative sample that contains a cross-section of all demographic segments
  • Respondents are dishonest or unthoughtful
    • Data quality is poor because respondents are bored and disengaged
    • Respondents are over-inundated with surveys
  • Leads to incomplete, careless, and dubious responses
  • Statistical assurances are not provided: Probability sampling is not used and the margin of error is not reported which interferes with interpretability
  • Can’t afford the good data: Researchers perceive that high quality data is out there, but their organization cannot (and will not) allocate budget toward gaining that data. Shoddy data at a cheaper price is of higher value than expensive but excellent data

 

  1. Internal Talent

8% of respondents said that internal talent is one of the biggest issues or challenges to market research in 2015:

  • Lack of experience and expertise
    • Young market researchers haven’t been trained in the kind of rigor that more experienced researchers have
    • A general lack of academic training in statistics, research methods, etc.
  • This is the generation of SurveyMonkey; young researchers seem to think that SurveyMonkey is the only way to collect data and disrespect methodologies like interviews, panels, etc.
  • Why are there no experts? (e.g., “It seems so obvious to anyone that a heart surgery requires expertise. If the market research industry cannot convince the market that there is a similar obvious need for expertise then there are a lot of good reasons why this industry should shrink in the future.”)
  • Lack of critical thinking
    • New market researchers are perceived as being unwilling to think deeper about their findings
    • It’s the day of the “obvious findings”: If an insight doesn’t jump right off the page – but, rather, requires some mental acuity and creative or critical thinking, new researchers will say that the data is bad or useless
  • A transition from quality to quantity
    • Time-honored, rigorous techniques are losing respect
    • What is valued now is the ability to gather data/insights quickly and at high volumes, regardless of accuracy
  • g., “I think this is the year when veteran researchers become the minority and disciplined research becomes rarer. Experienced research professionals who understand multiple modes of data collection and sample frames will be supplanted by newer researchers who can gather a lot of data quickly but may not have enough rigor in their background to know what bias they include
  • Customers don’t value MR expertise and insights
    • Researchers feel that they cannot convince their customers that there is value in expert MR insights
    • Clients feel that they are proficient at interpreting their own data and prefer to save money this way

 

  1. Old and New Methods

6% of respondents mentioned the challenge of old methodologies in market research. It was discovered that there is a dichotomy of thought in the marketplace about “old methods”. Some believe that old methods are tried and true, and therefore are to be trusted, while others believe that it’s time to put aside the old methods and try more innovative techniques.

  • It’s not “Old vs. New”, it’s “Traditional vs. Innovative”
    • Some market researchers reported that there is a tension even within their own organizations about old versus new approaches. They reported that the research veterans seem to perceive that the new, younger generation of market researchers are trying to eliminate methods that are useful just because they are “so two years ago!”
    • The younger crowd of market researchers feels that older researchers intentionally put barriers to innovation in place because they don’t want to learn new methodologies, try new approaches, or learn from youngsters who lack the experience that veterans have
  • Traditional methodologies don’t meet client’s needs
    • Panels, interviews, transcribing and coding responses, etc. take too long and are no longer effective. By the time all the work is done, the marketplace has shifted and the findings are irrelevant
    • Must rely heavily on aggregated quantitative data and almost completely suppress the rich qualitative data. Under the old approach, qualitative data is not used to its full potential
  • Innovative methodologies are confusing and unfocused
    • No one knows how to properly use the new technologies and methodologies of today in order to achieve their full potential
    • There are too many new methods that all paint a different picture of the same data
  • No one is an “expert” of any of these methodologies
  • The real answer is that both are needed
    • Although many respondents sided with either the traditional side or the innovative side, many more respondents admitted that the way forward is a blend of old and new
    • Capitalize on the rigor of traditional methods AND the expediency, innovation, and sex appeal of new methods

 

  1. Big Companies

4% of respondents mentioned issues related to big companies, with the largest proportion of these conversations about competing with big companies:

  • More funding
    • Bigger companies have more funding and can afford expensive, high quality respondents and data analysis
    • Smaller companies can’t compete
  • Looser standards
    • Big companies are perceived to have lower standards for data quality and prefer speed over accuracy. They have created an industry standard for quick turn-around deliverables. Smaller companies that focus on accuracy cannot compete because – although their insights might be better –it takes longer to do the analysis and customers aren’t interested in waiting when a bigger company could do it faster
    • No one is regulating the conclusions at which customers arrive. Customers see what they want to see, but what they see might not be accurate

 

  1. Communication

3% of respondents mentioned that communication with real consumers is the biggest challenge to market research in 2015:

  • What to do with consumer insights
    • Consumers seem to want to share their opinions and to be engaged with on a personalized, individualized level. However, market researchers feel that they are uncertain of the best ways to prompt consumers’ opinions
    • How to prompt in real time?
  • How to prompt in a way that will elicit natural, authentic, and unbiased responses?
  • Lack of engagement from consumers/respondents
    • This was a central theme throughout the GRIT report. Market researchers perceive that respondents would provide really interesting insights if they weren’t so bored during data collection
    • Market researchers are hungry for methodologies that interest, intrigue, and engage consumers so that they will be enthusiastic about responding to market research endeavors
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When Text Analytics is Your Brand: What I Learned About Personal Branding at #IIEX

Tom H.C. Anderson uses text analytics to dig deep into his personal brand and shares lessons with us all.

tom1

 

Editor’s Note: I’ve written extensively about my personal journey in brand building before: my “magnum opus” is the post My Life On The “V List”: How Social Media Reach & Influence Translate Into Offline Opportunity and my position hasn’t changed much since then. If anything, I have now come full circle where I have leveraged my personal brand to build several businesses that are doing well and am now considering the need to scale back my personal brand identification with them so that the business brand can thrive without my direct involvement. It’s a tricky issue to navigate, and one that many folks who build a business around themselves face; after all, businesses need to be scalable and that is one thing individuals are not.

All that said, today there are unprecedented opportunities to engage in effective brand building via social media, self-publishing, events, etc… and many individuals in our space have emerged as brands unto themselves using these channels (Ray Poynter, Annie Pettit, Tom De Ruyck, Tom Ewing, Tom H.C. Anderson, Dave McCaughan, Kristin Luck and Dan Foreman all come to mind as great examples) to help grow the businesses they are aligned with. Since quite a few of these folks were attending IIeX in Atlanta last week, I thought it would be interesting to pull together a panel on this topic.

As a prelude, Annie Pettit conducted a short open-end survey asking what comes to mind when thinking of her, Tom Ewing, Tom Anderson, Dave, and I. The results weren’t surprising: most folks had a very positive association with each of us, with a small but vocal minority of “haters”. Like any brand study, the goal here was to understand what attributes are associated with the brand and then explore ways to amplify those that fit with the strategic vision and downplay/correct those that could detract from that strategy.

Annie Pettit did an awesome write up of her key takeaways from the survey and the panel: How to create a personal brand #IIeX. It mirrors my own feelings and is a great primer on the topic for anyone interested. Dave McCaughan also wrote a great piece: WHEN THE BRAND IS YOU : FOOTNOTES ON MEDIA, MARKETING AND PEOPLE from the perspective of an ad agency veteran that is well worth a read.

Finally, Tom H.C. Anderson put his thoughts to paper, with the added bonus of using his OdinText software to do additional analysis on the survey results. It’s a piece that only Tom could write, and is actually a lot of fun and very smart, just like the author.

I hope all of this navel gazing on our parts has produced some useful insight for you. It would be great to see the number of personal brands in MR increase as we all explore what the future of this new dimension of our world means.

 

By Tom H.C. Anderson

Coming back from Insight Innovation Exchange (IIeX) this week in Atlanta and thought I’d blog briefly about the two panel sessions on Personal/Digital Branding I was asked to participate in.

Text Analytics

My main reason for attending IIEX was actually to give a brief presentation on how intuitive our OdinText text analytics software is, and how it really can turn any market research analyst into a powerful Data Scientist. This was the first time we’ve ever given any kind of demo of OdinText in public. Usually our presentations are approved case studies about how our clients like Coca-Cola, Disney, Shell Oil etc. are using the tool.

Also, text analytics remains a very competitive field, we prefer to share details around the software with those we know have the kind of data that OdinText can help with. However, since we’ll soon be launching a new version of OdinText and I was assured by Lenny Murphy that, contrary to what I believed, a lot of attendees actually want to see software demos rather than just hear use cases we agreed to do a short demo.

In case you missed it, I’ve posted a brief teaser video below, along with a shameless plug before I go on. If you regularly collect comment type text data, we’d love to hear from you and get you more info about OdinText (Request Info Here). Shameless ad plug over.

 

 

Personal Branding

Other than showing off OdinText though, I was also honored to be asked to sit on a personal branding panel with prolific market research tweeters Tom Ewing and Annie Pettit, as well as Dave McCaughan who is a well-known name in East Asian and Australian market research circles.

On the Summer Friday (at 5:30pm no less) before our Monday morning session, Annie Pettit came up with the idea to field an impromptu convenience sample survey, and to my surprise by Sunday afternoon we already had about 150 comments relating to the panelists. Lenny Murphy who has also accumulated a loyal #MRX following on Twitter and on the Greenbook blog was also included in the survey which asked something like “Q. What three things first come to mind when you hear each of these names/personal brands?”.

Though this sample is a bit on the small side for OdinText I quickly visualized the comments to give us some idea of how similar/different each of these 5 ‘brands’ are and what specific topics most frequently co-occur with each of them.

tom2

 

I’m sure all of us were equally interested in the findings, because let’s face it, while EVERYONE has a personal brand (even if unfortunately not everyone recognizes it), few of us ever get an insight into what it really means to people in this unaided top-of-mind market research sort of way.

We agreed not to share any of each other’s raw data, but I’m fine sharing the first 40 responses I received (both good, bad and ugly) below, sorted alphabetically:

 

American linked in conversationalist
Analytical, ever-present, helpful analytics omnipresent
analytics geek
Arrogant
beard, omnipresence and self publicity
Clever
controversial
Cool Guy
Entreprenuer
Fun honest text analytics
Hans Christian Anderson
He’s all about new, cool & hip in the quant world
His banner ads pursue me remorselessly around the web marketing
inconsiderate
Innovative
know his name but can’t recall…
Lover of anything that reminds him of the Swedish socialist utopia
money-face
MR. NGMR!
next gen guy
odin text – text pro
OdinText Text Analytics, smart, trustworthy
Opinionated
rebel
Research
respected, helpful, innovative smart
Self promoter
Social media junkie
straight shooter. willing to challenge hyped claims. maybe falling too in love with his own methodology
text analysis
text analytics
text analytics odintext
Text analytics pro
Text Analytics, expert, outspoken, industry leader,
text analytics, NGMR, vikings
Text master, text Analytics
The first to advocate Next Gen Market Research, especially Text Analytics and Data Mining,The first market researcher to truly understand social, AND bold enough to stand up against trade orgs on behalf of mid-small research firms. A true research hero
Tom is a great example of focusing on one thing you really care about and want to make better,and then actually doing that..
Tweeted this survey
up against trade orgs on behalf of mid-small research firms. A true research hero.
 

 

A first thing that struck me looking at both the responses for my ‘brand’ as well as those of the others on the panel was that the negative comments, while few overall, were also rather consistent proportionately across all of us.

I think this may have come as a surprise to some of the others, as I expected a few negative remarks related to some of the positions I’ve taken about market research, which while I know were popular among the majority of US researchers, weren’t as welcome by an outspoken few researchers more closely associated or working for these trade organizations I took issue with.

Of greater importance, and more surprising to me, was that our company brands were almost never mentioned for any of us. I’ve in fact been concerned whether my comments related to other areas of consumer insights research have taken away from what I really want to be known for, OdinText and Text Analytics. The good news was that when market researchers who know me think of me they think Text Analytics. The bad news, was that few mention the brand OdinText. But how bad is this really?

A few months ago I wrote about personal branding and Kristin Luck (someone else whom I definitely think should also have been on the panel). You can read that piece here. I think the point though really is that personal brands undoubtedly create a different and more complex association network in the minds of other people than brands or logos do.

This can’t be a bad thing, I believe they are complimentary. If people think Tom H. C. Anderson = Text Analytics, they also are likely to think Text Analytics = Tom H. C. Anderson, and so when they have a need for text analytics, some will think of me, and then OdinText (even if the brand OdinText doesn’t first come to mind).

I’m not sure what the association network is for uber personal brands like Bill Gates or the late Steve Jobs, but would venture to guess it’s similar. Surprisingly perhaps, Microsoft and Apple may well not be the first thing that comes to mind when someone first thinks about these two individual brands. Both really are far more complex than either of the company brands Microsoft and Apple. The individuals stand for so much more (philanthropy, design, success, strength, perseverance, intelligence, innovation…).

Definitely an interesting area, one that could use more research, aided by text analytics of course, OdinText Ideally 😉

My takeaway and advice to other market researcher is that personal branding is a good thing. It’s a complex thing, and that’s a good thing. Unlike a simple company product or logo we as people are deeper and have ability to encompass far more dimensions. I believe these personal brands, as I know from experience is the case for both myself and Kristin Luck, have been very beneficial to the companies we’re associated with. It’s a truism, that this is a people business, and people buy from people.

I encourage everyone to give some thought to their personal brands. Unlike corporate brands they don’t have to be perfect. If they were, they would be very boring and one dimensional. Just be you – and let others know it!

Tom

 

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Defining Innovation as Told at #IIeX Atlanta

Though you may never need or use them, researchers need to be aware of all possible research methodologies, including their strengths and weaknesses, so that we can recommend the right tool for our clients.

Innovation-Definition

 

By Annie Pettit

Innovation comes in many forms. It comes in the form of drones carrying cameras that fly over your home taking pictures of your roof and measuring it for new clay tiles (talk to Dan Ciprari at Pointivo). It comes in the form of pointing a camera at an IKEA Billy bookcase such that arrows and instructions appear on your phone to help you put it together (ask Margaret Martin at Merlin). It comes in the form of wearing virtual reality goggles that make you think you’re about to fall off the edge of a skyscraper (ask Jeff Reynolds at LRW).

What do these things have to do with marketing research? Well, you’re the researcher. You tell me. It’s time to use our brains and our research experience to turn these strange new technologies into the next research tool that generates insights we could have never had before. We need to turn “It’s too complicated to understand” and “It’s not really relevant for what I’m doing” into “I’m going to be the person who is innovative enough to make that work.”

With so much talk about innovation in the marketing research industry, you might feel like innovation is being stuffed down your throat. We know we must innovate but we just don’t have the money to go there. Wait. Let me correct myself. Many of us don’t have the inclination to go there. Innovation takes a lot of time and effort, and most of us are quite happy in our carefully maintained wheelhouses.

But not all innovation has to be expensive, strange, and unrecognizable tech. Innovation can, and most often will, come in the form of tiny incremental improvements (ask Shane Skillen at Hotspex). We need to stop trying to figure out what will be the next best thing, and be ready to notice the Vanishing Point – the ‘thing’ that is about to experience a massive decline in use/need/want (ask J.Walker Smith at The Futures Company).

For instance, tiny increments of innovation come from feeding conference attendees frozen treats that aren’t traditional orange, cherry, and grape flavours, but rather Lime Ricotta and Salted Chocolate from the King of Pops. Tiny increments come from tempting conference chairs not with traditional glazed and chocolate donuts but rather with Smores and Oreo donuts from Sublime.

Naturally, we experience tiny innovations in research all the time. Rather than worrying about maintaining norms from 30 years ago (that were only relevant up until 28 years ago), more and more of us are worrying instead about ensuring our traditional surveys reflect this decade of survey taking expectations. Ensuring that every survey question works quickly, easily, and intuitively on every device is where tiny innovations in the mobile survey space must be (ask Melanie Courtright at ResearchNow).

Most importantly, we must remember that innovation is NOT the end goal (ask Sion Agami and Steve August at Procter & Gamble and FocusVision). The end goal is not to choose the coolest research technology that generates the most ooohs and aaahhhs, but rather to better understand human behaviour. So if that means changing your strategy from asking people WHY they do something to asking people HOW they do something, then that’s an important innovation (ask Tom Ewing at Brainjuicer). If it means focusing not just on System 1 which is fast and intuitive, or just System 2 which is slow and deliberate, but rather System 1 AND System 2 as the research objectives require, then that’s a tiny important innovation.

Though you may never need or use them, researchers need to be aware of all possible research methodologies, including their strengths and weaknesses, so that we can recommend the right tool for our clients. And maybe, just maybe, the right tool isn’t one that’s in our toolbox. Maybe recommending the right research methodology to your client means you will send them on their way to a different supplier. But that’s okay. A little goodwill will bring that client right back to you when they need another honest answer and the methodology that you do provide.

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Guest Post: An IIeX Virgin Loves His First Time

Dave McCaughan kisses and tells about his first IIeX experience.

 

By David McCaughan

I get to go to a lot of conferences. I get talk at a lot of conferences, company events, workshops. The last few weeks I was the after lunch speaker at an effectiveness awards conference in Singapore, talked at a workshop for an organization that does economic infrastructure studies in Asia out of it’s Jakarta office, then a luxury personal care brand company event in Tokyo and the same day a real estate market conference. AND then I flew to Atlanta for IIeX.

It says it in the name. Ideas and Insights. It’s fast, it’s hard selling, it’s a bit brash. Most industry conferences use a form of apartheid to separate what happens in the conference hall from the trade show outside. Speakers can’t promote etc. Vendors only get to talk in the meeting rooms in breaks when most people are racing to go mingle around the snacks outside. But this IIeX virgin found the lack of such barriers refreshing. Companies presented what they wanted to sell. Speakers held back or pushed themselves as they saw fit.

But there was more. Exchange sessions that really opened up thought.

Of course there were sessions I was not that interested in, there were vendors who I can forgive for not taking much interest once they had sussed I am a self employed free lancer on the other side of the world, and as has to happen there were some speakers who did not do justice to their story, but what can you expect? There were the usual subjects. Too much regurgitation that big data and mobile and gaming are big. Sure we all know that, old news.

Having said that there was lot’s of inspiration :

  • J. Walter Smith started the first day with probably the biggest thought of the three days : the idea that is easier to track trends by looking at what is going away rather than what is coming. The latter are always likely to disappear, the former indicate big things happening. The art is in figuring what they lead too but he used the great example that the disappearance of younger marriages leads to a whole raft of needs for greater connection in new ways and hence the “kinship economy”. Hence social media, technology and flesh and blood interactions are booming.
  • Dr. Froswa Booker-Drew talked about social capital and diversity with passion. She suggested there is not enough space for “disoriented dilemma breaking”, the situations where we are forced to mix with “others”. Not our regular circles but expanded networks. The risk of the digital world is that we accidentally encounter less. She suggests we need to do less “bonding ( with those like us ) and more “bridging” ( with new relationships ) … which seemed very much in the IIeX spirit to me.
  • Rick West was a passionate proselytiser for the internet of everything and how that will bring us closer to understanding what people are thinking now rather than what they thought. In his formal presentation and then the next day in discussion sessions we had great discussions about my toilet stories and his ideas on how to use linked devices of all kinds to paint better pictures of behavior.
  • David Brudenell raised the well worn subject of dealing with Millennials and asking “ are you a good employer brand”. The research was not terribly new but the conclusion that understanding what they think is good leadership will be a key investment in staff happiness but also advice to clients.
  • Holly Demuro inspired with a simple thought : in an omni-channel world the voice of the customer get’s harder to track because we have quite simply to now start listening to all their conversations. And hence most VOC programs start with a rush of success in fixing “a” problem and then plateau as they fail to deal with the intricacies of reported and non reported, off-line/on-line needs
  • Mary Tarczynski mentioned that there are now 1.8 billion photos posted somewhere every day and then explained technology to spot trends across them. Given my own interest in the movement back to the historically normal form of literacy and the boom of graphic literacy in mediums like LINE I was inspired to find out more about her approach.

And much much more. Of course I could complain that there was not enough on other subjects I work in like cross culture analysis and the absence of discussion and new work with the 65-90 year olds is frustrating. But I did not expect IIeX to cover everything. I thought I would get some new ideas and see some cool technology … it was there in spades.

Glad I went, looking forward to going again and hoping Lenny and the team get the format to Asia soon!

Dave McCaughan IIeX NA 2015 Dave McCaughan, Bibliosexual

After 28 years with world leading advertising agency McCann as planning director first in Australia and then across Asia dave has now embarked on a new adventure in provoking new thoughts and telling stories for companies across the Asia Pacific region. Dave has lived in Bangkok, Hong Kong, Tokyo and now Hong Kong again, made hundreds of business trips across the region, dealt with dozens of major brands and spoken at over 500 conferences. He is a bibliosexual and wants to explain what that really means to you. He is also currently the editor of Research World Connect.

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