Video: How Advanced Conjoint Improves Innovation and Profitable Growth

By David Wilson | Aug 2, 2015 6:02:00 PM

Explainer Video: Improve Your Innovation Results

Every company relies on some form of research to understand consumer choices, preferences and buyer journeys. Unfortunately, many companies are still failing to tap into the amazing power of conjoint analysis to help them dramatically improve their innovation results.

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How Adaptive Conjoint Improves Your New Product Development Results

By FGI Marketing Team | Apr 29, 2015 3:33:00 PM

New Product Failure Rates Are High

New products fail at an alarming rate. Dozens of studies put failure rates at 60% to 80%.

So, why do so many new products fail?

Most companies rely on some form of product research to understand their consumers' choices, preferences and buyer journeys. However, fewer companies dig deeper to understand how these preferences differ across multiple segments and how they change in response to new competitive offerings, prices and disruptions.

In addition, many decision makers don't have good information to determine if investments in new product features will earn a suitable return in market share and margins. Finally, even when you launch an innovative new product at a very aggressive price point, you cannot expect your competitors to sit still. They will counter your move with price reductions and/or new product features of their own. These and other challenges contribute to the high failure rates of new products.

These innovation challenges put a great deal of pressure on brand managers, product managers and other marketing decision makers. To survive and thrive in this environment, decision makers must rely on the right kinds of new product development research throughout the innovation process.

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10 Advantages of Online Communities vs. Traditional Focus Groups (Part 1)

By FGI Marketing Team | Mar 20, 2015 11:27:00 AM

 

Editor's Notes:

1) This post has already generated a tremendous number of comments and ideas on various social media sites. Thanks to everyone who has taken time to contribute. Please keep your ideas and thoughts coming.

2) To be clear, this is Part I of a two-part post. So, while the title says "10 Advantages," Part I has just the first five advantages. Stay tuned for the next five in Part II.

3) While we extol the virtues of online communities (MROCs) in this post, we could easily write a post entitled "10 Advantages of Focus Groups vs. Online Communities." [And come to think of it, we may do just that in the near future.] We want to make it very clear that both solutions deserve a prominent place in everyone's MR toolbox. Focus groups continue to be extremely valuable. That said, the purpose of this post is to challenge your thinking and open your eyes to some truly unique and powerful advantages of online communities.

 


 

Introduction

The venerable focus group has been a go-to market research solution since first invented by Robert Merton at the Bureau of Applied Social Research. But, times change and innovation marches on. Today, online communities are clearly a much better choice for many important market research projects. In Part 1 of this 2-part blog post, we'll cover five important advantages of online communities vs. focus groups.

First, let's establish a baseline definition for focus groups and online communities.

Focus Groups

A focus group is a form of qualitative research where a group of people are asked about their opinions, perceptions, ideas and feedback about a product, service or any topic of interest. Questions are asked in an interactive group setting where participants are free to interact with each other and the moderator. Focus groups are typically conducted in person at a central location (or online), last two hours, and include 8-12 participants from a single segment.

Online Communities

An online community, also known as a "Market Research Online Community" (or MROC), is also a form of qualitative research where a group of people are asked about their opinions, perceptions, ideas and feedback about a product, service or any topic of interest. Questions are posed to the entire group of participants and/or in private, one on one exchanges through a series of interactive research activities such as polls, image markups, discussion boards, and multimedia exercises. Participants interact with each other and the moderator via their computer, tablet and/or mobile phone. Online communities are conducted virtually, last one to two weeks, and include 50-150 participants (often from multiple segments).

As you can see from a simple comparison of the definitions, online communities offer many advantages over focus groups. So, let's briefly touch on the first five.

Ask an expert

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Introduction to FGI Video

By David Wilson | Oct 6, 2014 3:43:00 PM

Introduction to FGI:

Below is a brief (2:23) explainer video that introduces FGI. It touches on our innovative solutions for product testing, package testing and other critical marketing needs.

Here's the transcript...

Today, marketers are under intense pressure to produce better and better results. They must launch winning products, grow revenue and profits, and create a better customer experience.

The problem is, many critical marketing decision are still being made with oversimplied research tools, outdated methods, or last-minute guesswork. Even worse, many viatal source of big data are stuck in their own silos, or abandoned altogether.

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Ohio Meets the 2014 FIFA World Cup -- What Twitter Big Data Mining & Visual Analytics Reveal About Who Really Cares in the USA

By Dino Fire | Jul 18, 2014 9:25:00 AM

by Dino Fire, Chief Science Officer, FGI Research & Analytics

*** Important Note to Readers: Some of the graphics in this blog post can be hard to read based on their native form from r. However, I wanted to illustrate what gets produced from these public domain solutions. They must be reproduced with other packages to yield client-ready reports. In any event, you will "get the picture" based on my analyses and commentaries associated with each graph. Thanks in advance for your understanding. ***

Growing up in Northeast Ohio, I do not recall ever seeing, let alone actually kicking, a soccer ball.  In those times and in that place the term “football” meant something entirely different.  It meant an oblong, leather-clad, brown inflated ball.  It meant glorious Friday nights at Mollenkopf Stadium.  It meant watching the Ohio State Buckeyes stomp on the University of the Sisters of the Poor every Saturday afternoon.  And it meant exploring new and exciting ways to express one’s displeasure and disgust at the Cleveland Browns every Sunday.  So naturally I wondered how the 2014 FIFA World Cup was playing in this nether world of chauvinistic American sport.

"I wondered how the 2014 FIFA World Cup was playing in this nether world of chauvinistic American sport."

Through the magic of the Twitter API, R code, and a few extra moments of time on my hands, I set forth on the journey to find out.

The Twitter REST API enables users to set a geographic parameter to limit searches to a specific geographical area.  The search terms were limited to #WorldCup, #worldcup2014, or #Brazil.  These terms were subsequently eliminated from the analyses, because we’re interested in what people are saying about those terms, not about counts of the terms themselves.

I started with the latitude and longitude of Columbus, Ohio, and specified a 200-mile radius.  A word cloud, of course, yields larger, more prominent displays of words with higher frequencies.  The basic word cloud of Ohioans’ tweets demonstrate some interest in the Spanish and Croatian futbol teams.  Speaker of the House John Boehner garnered a few honorable mentions as well.  What that has to do with the World Cup, I do not know.

Next I made a little side excursion that explored the tweets from the Youngstown/Warren area with those of residents of Youngstown’s sister city, Salerno, Italy.  The outcomes were predictable but nuanced. The Youngstown and Warren folks tweeted about the generic USA.  Could’ve been the soccer team, could’ve been native cuisine, like hot dogs, and could’ve been anything.  Not so with the Italians, though; the national football club was front and center.

Ohioans are people of few words, at least as far as tweeting about the World Cup is concerned.  The vast majority of Ohioans’ tweets comprised 8 or 10 unique words.  The base R program provides a nice histogram.

"What’s the difference between England and a teabag? The teabag stays in the Cup longer."

Before we get into the deeper statistical analysis, I should point out that THE BIG BUZZ at the time was about England getting unceremoniously booted from the tournament in the opening round.

What’s the difference between England and a teabag? The teabag stays in the Cup longer.

A hierarchical cluster analysis of Ohioans’ tweets is intended to depict how words tend to cluster together in Euclidean space.  It’s a fancy way of seeing how words correlate.  And here are the results.

One group of tweets centered on England’s demise, and another seemed to be about who was showing up in Rio de Janeiro.  Yet another group of words dealt with the Italy – Costa Rica match, while a fourth cluster seemed to inquire about who was supporting US soccer.

Disregarding the clustering of words, we can review the correlations themselves.  I’m proud to say that Ohioans are expert analysts of English soccer.

Despite a seemingly infinite number of startups claiming to do better social media mining better than anyone else, sentiment analysis is an iffy proposition at best.  For those who aren’t blessed with 50 unsolicited emails a day from social media mining companies, sentiment analysis refers to an evaluation of a tweet from a subjective, qualitative standpoint.  The analysis tries to classify tweets or other textual content “scraped” from various websites into “good” or “bad,”  “happy” or “sad,” or other such bipolar sentiments.  But often that’s where the problem arises.  For example, the following tweet would be classified as “good:”

Well, England, that was a good effort.

But unfortunately, so would this one:

Well, England, THAT was a good effort.

He or she whom invents a sentiment algorithm that can accurately interpret sarcasm wins the prize.  Yeah, THAT will happen.  Scrape THAT, you bums.

Nevertheless, I’ll hop upon the sentiment analysis bandwagon and see how Ohioans feel about the World Cup so far. First of all, we see that there is no transformation of the sentiment-scored data required.  The results reflect a very normal distribution, not skewing one way or another too badly.

We see that the sentiment scores are more positive than not, but as of this writing, the USA team is 1 – 0.  Those scores are subject to shift later, to be sure.

In this case, the sentiment scoring algorithm freely admits that it is clueless about the context of many of the words it encountered.  Still, it seemed predisposed to find and tag joyful comments.

"In this case, the sentiment scoring algorithm freely admits that it is clueless about the context of many of the words it encountered."

The sentiment scoring algorithm output a nice comparison word cloud, which visually demonstrates the words and their respective classifications based on frequency.  Yes, I always associate the term “snapshot” with “disgust.”  Interestingly, “Redskins” got lumped into that classification as well.

So are Ohioan’s beliefs about the World Cup different from other, surrounding, and, some would believe, inferior types of people (based on their state of residence)?  Well, let’s see.

Sentiment scores in Ohio, Michigan, West Virginia, Pennsylvania, and Indiana lean uniformly positive.  But a careful look at the boxplots show that Ohioans and Indianans opinions tend to cluster in the middle:  not too positive, and not too negative.  That’s not the case among Michiganders, who tend to be extremely more positive or extremely more negative.  Those Michigan folks represent very nicely the dangerous reality about averages: You can be standing with your feet in a bucket of ice water and your head in a roasting hot oven.  But on average you feel just fine.

"Ohioans are losing interest, and starting to turn their attention toward Wimbledon. And West Virginians don’t seem to care much about the World Cup at all."

A comparison cloud shows just how different the tweets from these separate states really are.  Michiganders seem obsessed with the Italy – Costa Rica match.  Indianans seem strangely interested in the Forza Italia political movement.  Pennsylvanians are engrossed in a game of “where’s Ronaldo?”  Ohioans are losing interest, and starting to turn their attention toward Wimbledon.  And West Virginians don’t seem to care much about the World Cup at all.

 

What do you think about the ability of Twitter, r, and visual analytics to shed light on USA's real and lasting interest "the beautiful game?" Let me know with your comments below.

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Retaining and Growing Super Consumers

By Taylor Chronis | Apr 9, 2014 9:10:00 AM

Many companies aspire to grow and maintain their brand loyalists—the customers who purchase their products time and time again. After all, this small segment of heavy users often accounts for the majority of a company’s sales. But within this group of loyalists, there’s an even smaller—and more powerful—segment of consumers that is often overlooked. This group, known as “Super Consumers,” might just hold the secret to success for your company. 

The Harvard Business Review recently published an article from the Cambridge Group and Nielsen about the power of Super Consumers. We’ve broken down some of the main points and explained how you can use research to effectively retain and grow your Super Consumer segment.

Who are “Super Consumers?”

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Measuring Customer Experience with Net Promoter Score

By Taylor Chronis | Feb 28, 2014 9:14:00 AM

By: John Blunk, Director of Client Services

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