If you’ve been following Ray Poynter’s LinkedIn discussion, you’ve seen all the positive feedback he received in response to wondering aloud about a virtual market research conference. And all of those positive comments turned into a brand new conference!

Have you ever been disappointed that your conference budget only permitted 6 conferences per year even though there are 20?
Have you ever had needed to attend two different conferences in two parts of the country during the same week?
What crazy world do you live in?

Well, this is the conference for you! Listen in, present your research, mingle with other professionals without ever changing out of your pajamas and into your business suit! Com’on over and join us at a brand new virtual conference!

But nobody told you what. Social media is still a brand new arena for many companies. Some are just figuring out that having a Facebook account and maybe even a Twitter account is a good thing. And if these tools are new to you, trying to get a grasp on what more there is to do with social media can be an overwhelming task. Have no fear though. Here are four different things you can do.

Photo credit: clarita from morguefile.com

1) Public Relations: Social media is a great tool for communicating with the general public. Your Facebook page and your Twitter account let you have one to one conversations with people about your brand and products. Consumers – people – have fun reading postings, liking posts, and getting to learn more about who you are as a brand. And, anyone can quickly and easily jump on this wagon. This is the most popular use for social media.

2) Customer Relationship Management: Companies that are a little more savvy can build on their PR initiatives with this component. Tools like Facebook and Twitter can be used not just for general communications, but to respond to consumer questions and solve consumer problems. It’s easy enough for people to send a Facebook message or Tweet to you asking specific questions. If you’re ready to respond to them, with speed and friendliness, then this could be right for you. Companies like Dell and Comcast have Twitter accounts set up just for this and people take full advantage of them.

3) Social Media Monitoring: This use of social media takes a step away from the individual consumer to look at the wider space of the internet. Monitoring is a way for a brand to stay on top of who is saying what about your brand. The goal isn’t necessarily to communicate with individual people, but rather  to have an ear open to anyone speaking about your brand, to watch when and why the volume of conversations increases and decreases, to see what reactions are when good or bad things happen around your brand.

4) Social Media Research: For those of you wishing to expand your survey or focus group research beyond the asking and into the listening, this is the option for you. Social media research uses all of the same scientific principles as traditional research but focuses on social media as the data source rather surveys or focus groups as the source of data. Research objectives, sampling, weighting, standardized variables, norms, generalizability, and validity are the words of the day here.

In the end, you must decide on your objective. Do you want a communication channel for your consumers? Do you want to actively seek questions and solve problems? Do you want to listen to the ebb and flow of the internet? Do you have specific research problems you need to solve? You may not have the time or the budget to delve into every area but one of them probably meets a need you’re currently trying to fill.

Answer that question, and the next step is easy. Well, maybe not easy, but at least you’ve chosen a fork in the road.

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Related links
Social media monitoring vs social media research: Can you see the difference?
Coke it is! Or not. I’m not sure. I can’t tell.
How important is sampling? Well, how important is gay marriage?

Almost anywhere you turn, someone is offering social media tracking, monitoring, measurement, evaluation, or some other form of analysis of social media data. How do you know whether you’re getting quality goods? Here are six things to checkmark before you get started on the journey.

Search Quality: What are the restrictions put around the data you are seeking? Are there methods in place to ensure the right data is being selected in and the wrong data selected out? If your brand is “Target, ” you need to make sure that the data is all about clothing and consumer goods (select in) and not about target practice (select out). Ask whether the data collection processes allow complex “and” and “or” searches so that data can be easily excluded and deliberately included.

Search Population: Is data being gathered from across the entire internet or just the top sites? There are pros and cons to each method. The top sites often account for up to 80% of all of the relevant data, but who’s to say whether the other 20% reflects a unique group of consumers whose voice could change how you think about your brand. You should at least know which process is being used.

Data Volume: Being blessed with millions of online records is a sweet luxury that only a few brands can achieve. But, unlike the survey world where 500 is a great sample size, this just doesn’t cut it in social media research. Most brands fall somewhere in between these two extremes, generating from hundreds to thousands of records each month. If your brand  generates just a few hundred records every month, you might be more suited to a qualitative approach to SMR and some efforts towards building a greater online presence. Brands generating thousands of records each month can take full advantage of both quant and qual approaches.

Scoring Quality: There are many different methods for scoring the sentiment of online conversations. What systems are being used? Is the scoring a manual process, automated, or combination of the two? Is it dictionary based or mathematical based? How do the systems accommodate the rapidly evolving English language? How do the systems account for new and emerging slang? And all the while, you need to remember that no system, not even a human being, can achieve perfect scoring. In this world, perfect isn’t 100%, it’s only 85%.

Coding Quality: Data isn’t useful until it’s categorized into meaningful chunks of data. Knowing that overall sentiment towards a brand is “Very Positive” does nothing to help you decide whether you need to build your product in a different color, shape, or size. But this isn’t an easy process. When Earl Grey Tea gets categorized into a color, you have no hope of generating valid insights from your results. Ask about the process of data quality in the coding process. Find out whether Charlie Brown is a color.

Coding Flexibility: Your brand is unique like no other brand. Your research objectives are like no other brand. There’s no reason to assume that the coding structure any other brand uses should be the same as what you use. Beyond the obvious requirements of purchasing, recommendations, trial etc., you have specific needs. Be sure to ask about how the coding can be customized to meet your unique requirements.
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Related links
Social media monitoring vs social media research: Can you see the difference?
The Conversition Hierarchy of Social Media Insight
Coke it is! Or not. I’m not sure. I can’t tell.
Apple pie, Apple orchard, Apple cider, or Apple iPad

Members of the Marketing Research Association (MRA) can peruse the August issue of Alert! and learn more about social media research as practiced by Conversition. Annie Pettit’s article leads this month’s issue with some things you should consider when embarking on a social media research project.  If we may be so bold, some have called it a “Must Read.”
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On the cover is pictured Noam Raz, @raznoam on Twitter, who traveled all the way from Israel to attend the Boston MRA conference.

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Related links
Quirks: Thoughts on sampling and weighting in social media research
Social Media Research: Conversition’s Presentation at MRA Boston

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Are you in favor of gay marriage? Are you against gay marriage? One way or the other, many people have extremely strong feelings towards this topic. It’s a topic that has the ability to quickly divide us and turn normally civil people into very angry people.  There is almost no room for error.

But let’s take a quick step backwards. When a data provider gathers online conversations, or crawls the internet searching for conversations about a topic, it is impossible for them to gather every single conversation. We can’t all be Google but we can gather very large  samples of conversations. We can crawl blogs and microblogs and forums and consumer websites, searching as much as we can for relevant conversations.

Let’s say I gather my sample of gay marriage conversations by focusing on certain websites. You gather your sample by focusing on certain websites. Someone else gathers  their sample focusing on certain websites.  Though we MAY all touch the same websites, we touch them all in very different ways. The internet is one single giant database, but we now have three different completely collections of conversations about the identical topic. What are the consequences?

In a previous blog, we saw that Twitter data is unlike other online data. Twitter has much higher highs and lower lows, likely because twitter more closely resembles mouthing off, spur of the moment, off the cuff remarks.

Twitter is just one of several very popular microblogs represented by the red “Micro” line in the chart. Look at how the positive emotions towards gay marriage range from a high of about 22% of conversations in April to a low of about 1% in May.  If you had gathered a sample of conversations about gay marriage that focused heavily on microblog data, you would think people’s online opinions about gay marriage are all over the place.

(Please note: This blog only shows positive emotions. It does NOT show the % of opinions that fall in the neutral range or the negative range. Do not interpret the 1% positive to mean the other 99% is negative.)

We know that just looking at Twitter or microblog data is not a fair measure of online opinions. So how should we measure online opinions towards gay marriage? Should we let opinions from blogs count a lot more because they are well thought out  (the light blue line) or should we let blogs and microblogs contribute an equal amount toward the overall opinion (green line)? Should we let the data fall however it wants to fall (purple line) or should we make sure that each website contributes an even or consistent amount of results each month (black line).

What is clear from this chart is that the way you gather conversations from the internet determines what your results will be. You can create a more positive or more negative average opinion easily enough through careless or unthoughtful sampling.

We’ll let you ponder which method of sampling produced the correct answer, and whether we’ve even provided the correct answer here. (We haven’t.) But the conclusion to draw from this demonstration could not be more serious or important. If you’re going to tackle social media research from a social policy point of view, you had better be an expert in sampling.
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[Method: Over 30 000 opinions gathered from thousands of websites, processed, cleaned, validated through Evolisten]

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Related links
Quirks Magazine: Thoughts on sampling and weighting in social media research
Tracking the mood of Americans: Use Twitter if you want to prove they’re happy

It’s a question that tugs at the heart strings of many researchers. Are you a quant person or are you a qual person? You must choose only one, and you must choose wisely, because it will define who you are as a researcher for the rest of your professional career.

Your decision will determine which market research methodologies you are permitted to use.

Surveys – Just for quant people
Focus groups – Just for qualis (like @BenSmithee and @LongoMR)
MROCs – More stuff for qualis
SMR  – Now we’re stuck…

Actually, there is no such as thing as a researcher or a method that is just quant or just qual. When was the last time you analyzed survey data and didn’t read a single verbatim? Reading those verbatims and trying to organize them into meaningful pieces of information counts as qual. When was the last time you put together a focus group without regard for who or how many participated and then proceeded without a carefully designed discussion guide? Counting those people, counting those opinions, measuring the intensity of those opinions counts as quant. Certainly every research method, whether quant or qual, has a leaning, but every method dips its toes into each bucket, sometimes more deeply than other times.

The same holds true for social media research (SMR). Your personal style probably has you leaning on the quant side or the qual side but SMR is almost by definition a beautiful combination of the two. For those with qual leanings, you can individually review hundreds or thousands of online conversations, sort them, categorize them, and treat them as you would any qualitatively focused study.

For those whose personal leanings are in the quant direction, you can take advantage of systems which transform hundreds, thousands, or millions of verbatims into datasets that look surprisingly the same as what you would generate with a survey. Box scores, percentage scores, norms, crosstabs, and t-tests are all just waiting to be admired.

Even better, imagine the insight, yes the dreaded word insight, that you would achieve by letting both your quant and qual sides show. A qualitative approach to quantitative research. A thorough, individualized analysis of social media data subsequently quantified using standardized procedures for maximum generalizability.

How nice it is to lean both ways.

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Related links
A 300 year history of text analysis
Goodbye static, Hello dynamic

Norms are among the most commonly used and sought after features of market research. They are a great way to compare how your brand is doing relative to other brands in the same space. You need them to see where the entire market place sits relative to your brand. You need them to see in which areas the entire industry is weak, areas where perhaps you could strive to excel. You need them to see where the entire industry is strong, areas where you must ensure you do well.

Most companies have spent years and decades creating enormous norms databases that allow any brand to instantly determine where their brand fits in without having to expand their research dollars to 10 or 20 competitive brands outside of their own brand. There is no doubt that norms are an essential part of our work.

But here’s something to ponder. What exactly is a ‘norm’?

Norms reflect the average of many brands. It’s a watering down of the fabulous brand in the upper 2% of the normal curve, the great brands in the upper 16% of the curve, and the 2% and 16% of brands at the bottom of the curve, those that desperately need to pull up their socks. Norms reflect the good, the bad, and the average, unassuming, nothing special brands.

Are those really the brands you want to compare your brand with? Is your ultimate goal to tell your boss that your brand is achieving consumer satisfaction scores that are better than all of the really terrible and somewhat terrible brands? Congratulations, our brand is beating all of the brands that went out of business last week! I suspect not.

Instead, is your ultimate goal to be the Coke of soft drinks, the Starbucks of coffee shops, or the Apple of computers? Wouldn’t you rather strive to beat the brands in the top 2% of the curve? The brands that are stealing market share and consumer awareness and consumer engagement? Wouldn’t you rather tell your boss that your customer satisfaction scores are better than the top contenders in your category? I suspect yes.

Perhaps market researchers ought to focus first on the category leader and then see how the losers are doing.

We would love to hear your thoughts on norms! Please share your comments.

Social media research has officially burst onto the scene and we are pleased that Quirks has devoted the entire August issue to it. Included in this month’s magazine is an article on sampling by Annie Pettit, our Chief Research Officer. The abstract follows and if you want to read more, simply click here and head on over to page 42.

Article Abstract
When analyzing data from social media, the choice of a sampling plan depends on the purpose of the research and how those results will be used afterwards. The author discusses three options and some of the issues surrounding the use of data from social media.

Article ID: 20100806

Today’s Battle of the Brands is inspired by @SurveyGizmo

Using only the thousands of social media opinions generated by their fans as their weapons, we have analyzed, samplized, sentimentalyzed, and contentalyzed Homer Simpson and Dunkin Donuts. Whomever wins the most matches will be declared the victor. Let us begin.

Cool factor:
Even though Dunkin Donuts scores 27% positive, Homer proves that wearing the same clothes every day of your life is even more cool. Homer beats Dunkin by a mile with a score of 45% positive.

Favorite:
Favorite cartoon or favorite donut, you simply must choose one. And a 52% positive score for Dunkin Donuts (watch out Tim Horton’s and Krispy Kreme!) means it beats Homer’s 38% positive.

Funny:
Wow. Donuts are funnier than Homer! Dunkin Donuts scores 33% positive while Homer only generates a 26% positive score. Looks like Dunkin needs to keep up their great sense of advertising humor and Homer needs another Spiderpig!

Intelligence:
Though a donut has no brain, the people have spoken and decided that Dunkin Donuts has more business smarts than does Homer. The donut shop scores 22% positive while a cartoon character with a cartoon brain only scores 16% positive.

Reputation:
While Dunkin is a shining example of a retailer with a great reputation, Homer is a shining example of  why reputations don’t always matter. Dunkin Donuts scores a fabulous 55% positive score while Homer scores stunning 61% positive score.

Overall emotions:
Mmmm donuts, I guess we have our winner! Dunkin Donuts scores 30% positive while Homer scores 25% positive. I could sure go for a Boston Creme donut right now!

Though Homer Simpson is usually the one eating the donuts, this time, good ol’ Dunkin showed Homer who’s boss!

Next Battle of the Brands? Completely up to you. Leave your requests in the comment box!

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Related links
Battle of the Brands: Angelina Jolie vs Bacon
Homer Simpson and Dunkin Donuts on Evoplay