Posts Tagged ‘social media analytics’

Conversition Presents Mobile Mixed-Mode at MRA in Washington

Wednesday, April 27th, 2011

Mobile Mixed-Mode Research Workshop

Date: 06/06/2011
Time: 9:00 AM – 12:00 PM
Room: Palladian Ballroom

Technology has forever changed the way people live their lives and how businesses do business. Gone are the days of conducting a single mode, landline telephone survey to reach a representative sample. Using multiple data collection methods creates many challenges for marketing research. It also provides new opportunities for reaching and understanding different populations. With the advent of new technologies, researchers now have a wide range of options available to them. But what works and what doesn’t? How do we implement those new and still widely debated methods and provide reliable results?
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In this three hour immersion workshop, attendees will first get detailed explanations of four separate case studies that provide practical applications of online panels, cell phones, smart phones, SMS texting, IVR, social media, mobile web surveys, and tablets in actual mixed mode research studies.
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Attendees will then be challenged to put together an effective research plan using a variety of methods to collect opinions and sentiment from various “hard to reach” populations in less than ideal locations. This “hands on” session will provide participants with the knowledge of how to implement different data collection methods while understanding how each method augments and complements the others.
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Conversition at the MRIA In Kelowna BC

Thursday, April 21st, 2011

I have to admit – I’m pretty excited! Kelowna BC looks to be a gorgeous site for this year’s annual MRIA conference. Add to that a ton of great speakers and it doesn’t get much better. We were lucky enough to be selected to speak at the conference and look forward to sharing what we’ve learned since we presented at last year’s conference. We hope to see you on Monday May 30, at 2:30 in the Chilcotin room!
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Side by Side by Side: The Survey, Cell, SMR Study You’ve Been Waiting For

In 2010, we saw sample social media research results, and we learned about the pros, cons, ethical implications of the method. Now, it’s about time we saw some real examples of how SMR works in cooperation with other methodologies. This presentation will showcase a cooperative study using results from three different methodologies, online panel surveys (fielded by global online sampling and data collection company, Research Now), cell phone surveys, and social media research. We will see where the results are similar and where they differ. We will discover how the strengths of one method build on the weaknesses of another method. We will discover data fusion at its finest.

Chief Research Officer Conversition Strategies

Annie Pettit, PhD is the Chief Research Officer of Conversition Strategies, a boutique market research company that specializes in social media research.

She has more than 15 years of experience as an online market researcher and specializes in survey research, data quality, and social media market research. Annie is a member of the CASRO, MRA, and ESOMAR social media research committees. She was previously the VP of Online Panel Analytics at Ipsos where she created their proprietary survey panel data quality system.

Annie tweets at @LoveStats and maintains the LoveStats marketing research blog where she occasionally showcases her attempts at being a better baker and gardener.

Recherche sur les réseaux sociaux pour les personne #MRX

Tuesday, April 19th, 2011

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Nintendo 3DS: Pilotwing vs Dead or Alive

Wednesday, April 13th, 2011

If I could make this post 3D I would, but until that day, just imagine that the charts you see below are bursting out of the screen and poking you in the eyes. Unless you’re wearing glasses. Then you’re safe.

Consumers have had some time now to try out the 3D system and decide whether they like it. Many people have already experienced the headaches, sickness, and vomiting that has accompanied this new form of brain candy. And if you’ve decided the headaches are worth it, or you’ve already trained the headaches away, you’re ready to pick out a new game.

Based on thousands of verbatims from across the internet – blogs, microblogs, forums, video sites, photo sites, and much more – that mentioned the Nintendo 3DS system, we coded and scored verbatims that mentioned these specific games to determine which one should be first on your shopping list.

In the first chart, you can see just how much chatter takes place about each of the games. Games at the top of the list generate the most chatter and that includes Pilotwing, Street Fighter, and Ghost Recon. In fact, these three games generate more chatter than the remaining 13 games put together.

On the other hand, games at the bottom of the chart generate the least chatter and that includes Dead or Alive, Bust-a-move, and The Sims. The six games as the bottom of the list aren’t that much different from each other in terms of the amount of chatter they generate.

But you know very well that volume of chatter does not mean a game is great. It could, in fact, mean a game is so bad that everyone is having a great time making fun of it. We all know about the Double Rainbow and poor Rebecca Black. So let’s make sure we’ve got it straight.

nintendo 3ds conversition social media measure

One of the tricky things with sentiment as that gross, violent, and scary games have a lot of negative words in them that erroneously lead to negative scores. So we took care of that right away. Those words had no influence on our scoring system.

The chart you see here shows the percentage of comments/status updates/messages that were scored as either negative (red), neutral (blue), or positive (green).

First of all, you can see that within Nintendo 3DS conversations, the game generating the most positive sentiment (55% of the messages were positive) was the Dead or Alive game. It may not generate the most chatter but it sure generates a lot of positive chatter.

On the other hand, Bust-a-move, which also didn’t generate a lot of chatter also failed to circumvent it with sentiment. Only about 25% of those verbatims fell into the positive side of the scale. Fortunately, though, almost none of the verbatims about Bus-a-move are negative. These aren’t bad scores but if you can only choose one game, maybe this isn’t the game for you.

nintendo 3ds conversition social media measure

Now that you have the scoop, you’ll have to decide which games are going to make the trip from the store to your home. Lego Star Wars is on its way to mine!
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The Sharks and Icebergs of Social Media Measurement

Friday, March 25th, 2011

It’s all very deceiving. Social media measurement is superquick and feeds everyone’s desire for instant gratification. Want to measure something right now, lickety split? Here you go!

Unfortunately, it’s not that simple, nor do you want it be that simple. Behind every “instant analysis” are hundreds and thousands of hours of tedious, painstaking work. Let’s take a brief climb up the social media measurement iceberg and check out where the data quality sharks are hiding.

Taking much of the time, the bulk of the iceberg, and many of the data quality sharks is sentiment analysis. There’s no point in being amazed at how quick your measurements were generated if those numbers have no bearing on the true sentiment of a brand.  The data quality sharks biting at the validity of your data include things like failing to measure  “the bomb” correctly and forgetting to measure “FTW.” If these sharks aren’t addressed, your amazingly quick measurement will be wrong.

The next chunk of the iceberg that rarely gets seen is the work that goes into developing variables. The data quality sharks here include recognizing that “tasting success” and “tastes in music” aren’t discussions of how deliciously yummy something is. Behind the scenes, people must spend icebergs of time making sure those invalid mentions are identified and ignored. Otherwise, your instant measure of whether people are happy with the new flavour of Doritos will be wrong.

Now we’re actually ready to gather YOUR data. As always, you can go online and quickly gather a ton of information about Ford or Sears or Harley, but your data quality sharks try to stuff in mentions of “my mayor, Mr. Rob Ford” and “sear the meat quickly” and “my dog Harley.”  If you don’t take the time to kill those data quality sharks, your instant analysis will, once again, be wrong.

The last chunk of work goes into removing spam and irrelevant data. Of course, you can easily set up an automated system to detect and delete spam but you must always be on the lookout for new and improved spam. This data quality shark sneaks in when you least expect it. No checking means no validity.

And now, we’ve climbed to the top of the iceberg, to the last tiny percent of data work that is visible to the outside world. Enjoy your magical, instant measurement. It wasn’t that instant after-all, was it!

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Forgive me, for I have sinned

Wednesday, March 23rd, 2011

Forgive me for I have sinned. Without permission, I used company property for my own personal gain.

Earlier this year, I saw some ads on the subway system for a glasses and contact lens company. The ad proclaimed, “FREE GLASSES.” I proclaimed, “HOAX.”

But it wasn’t a hoax, it was just a very effective and provocative advertising campaign. Glasses cost me at least $400 every time so free glasses were extremely tempting. But, I also didn’t want want to be mentioned on the evening news as “Annie was one of 300 stupid people who fell for the glasses scam.”

So, after seeing ads for really cheap glasses from the same company a few more times, I broke down. I, um… borrowed company property. I used Conversition’s proprietary social media measurement system to collect a few thousand tweets and blogs, and forum and photo comments that mentioned the company and their ads. You see, thousands of independent opinions from people who have already conducted business with the company couldn’t be wrong.

The system cleaned the data of irrelevant spam, scored the sentiment on a continuous scale, and coded all of the comments into the one thousand, most relevant variables. Just a couple hours after I finally decided I wanted in on cheap glasses, I had valid and reliable, quantitative and qualitative social media data at my fingertips. And here’s what I learned.

  • When people talked about whether they would recommend ClearlyContacts, 54% of those recommendations were positive, as opposed to middle of the road neutral or negative.
  • 44% of comments about pricing were positive
  • 37% of comments about the choice of products were positive
  • 57% of comments about the customer service were positive
  • 50% of comments about the shipping were positive
  • Overall, about 46% of people liked this phantom internet company and less than 6% did not like the company.

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Of course, you do have to listen to the people who aren’t happy if you want a balanced opinion, so I also checked out what the biggest complaints were.

  • 11% of comments about the frames were negative
  • 10% of comments about the lenses were negative
  • 8% of comments about the check out process were negative

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Given survey research norms call for about 10% to 15% of results to fall into the negative side of things, these negative comments were not out of the ordinary and were nothing for me to be concerned with. And since norms dictate that about 30% of results fall into the positive side of things, I felt even better.

Social media research did its job well and proved to me that the company was legit! So I bought a way cool pair of glasses for way cheap. Actually, because they were so cheap, I bought two pairs. Like ‘em?

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Global Voices, Local Choices: A Social Media Research Case Study

Monday, March 21st, 2011

Every country has their own brands and services. The thing about the internet though, is that we can read about services that are available in other countries. No matter whether the options are available to us, we can see who is being offered better, or worse, products than we are and demand those things where we live. This case study, in the telephone/television/internet space, illustrates consumer opinions towards several services, some of which are available only in Canada, only in the US, or in both countries. Let’s compare AT&T, Rogers, Comcast, T-mobile, and Virgin.

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Justin Bieber vs. Katy Perry vs. Metallica: A social media research case study
Fail #1 Google, Fail #2 Superbowl Tibet, and Groupon Hangs in the Wings
Which pain relief medication for which pain? An SMR case study #MRX
Snickers Bars and Breakfast: A social media case study
Battle of the Burgers: Big Mac vs Whopper

Which pain relief medication for which pain? An SMR case study #MRX

Friday, March 11th, 2011

Your local pharmacy is chock full of pain relief medications and every box says it’s best for something different. This case study illustrates how real people think about five brands, including Tylenol, Advil, Aleve, Aspirin, and Excedrin. We explore the psychographics associated with each brand as well as what types of pain lead people to use specific brands.

Listen to what hundreds of thousands of people have to say in the online space.

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Quick and Dirty or Slow and Careful: Conversition’s #NewMR Presentation

Wednesday, March 9th, 2011

Social media analysis is so simple. Do a keyword search on Google, find some data mentioning your brand name, whip up some cool analytical results. But wait – have you ever wondered why different people end up with such different results when they research or monitor the same topic? This presentation, created for the #NewMR festival on Listening, will share just a few of those reasons with real examples. Mmmm…. real data!

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Conversition on LinkedIn

The #Klout of @Klout

Wednesday, March 2nd, 2011

Not many folks liked the popularity contests of highschool, but we still like to be popular, whether in the face-to-face space or the online space. Klout is one of the available measures of online influence and it takes into account the size of your engaged audience, the likelihood that people will retweet or message or like you, and how influential your engaged audience is.

The folks at Klout have even built an extension for the Chrome browser that lets you see the Klout score of each tweeter in your stream. According to the screencap of our twitterstream, these research folks are doing pretty well with scores ranging from 42 to 66.

But let’s not worry about what Klout does, or how it does it or even whether it is actually accurate it is. Let’s consider, instead, people’s perceptions of the tool. Do we love it or hate it?

First of all, the obvious notes – This dataset does not include tweets or blogs or messages sourced from Klout or KloutPerks. And, the measurement was not confounded with Klout terminology such as “specialist” or “influenced” or “perk.” And lastly, we’re basing our results from a random sample of about 5000 messages that were written in 2011.

Now that we’re all on board, let’s look at some numbers.

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Overall, do people like Klout?
Overall, people are fond of Klout. Around 40% of people like it while only 6% of people dislike it. But, that leaves an awfully large group of people who are undecided, unsure, or couldn’t care less. Common ways to talk about Klout include  “best,” “love,” “thank,” “amazing,” “impressive,” and “fun” but we also speak of “sadly,” “dislike,” “wtf,” “rant,” “scary,” and “shame.”
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Among people recommending tools, is Klout recommended?
We’re doing pretty good here! About 66% of people would recommend Klout. In fact, they say they not only “recommend” Klout, but they “endorse it,” “cheer for it,” and are “addicted to it.” That does leave another 30% of people who are pretty neutral about the whole thing, as well as a 4% who would never recommend it.
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Among people talking about favorites, is Klout their favorite influence tool?
In this case, we have a ton of people talking about Klout being their favorite tool. Being the favorite of 67% of people is pretty darn good. But, of course, about 32% of people don’t really care, and a tiny percent say it’s not their favorite at all.
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Among people talking about accuracy, do people feel that Klout is accurate?
Lastly, and possibly the most important item for a small number of researchers who are most concerned with validity, we come to accuracy. In this case, only 14% of people gave Klout a positive score. And, more than 22% gave Klout a negative score.  While many people say Klout is “accurate,”  even more say it is “wrong” or it’s a “fail.”

So, it seems that regardless of accuracy being less than desirable, people are still fond of the tool.  Our Klout score is 50. What’s yours?
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#MRX MRA IMRO SMR Guidelines #10: Qualifications
Fail #1 Google, Fail #2 Superbowl Tibet, and Groupon Hangs in the Wings
The Fantasy of Representative Samples
WeightWatchers or Jenny Craig: Social Media Research Knows the Answer
Who am I? Contributor, author, participant, responder?
Super Bowl = Beer + Wings + Hooters