Handling Social Media – Part 1: The Awakening.

Wednesday, July 28th, 2010

By Fernando, Conversition’s Lead Evolisten Engineer

(Our tech team writes too!)

Have you ever complained about something? Or given your honest opinion? Or answered a question? Only to be completely ignored? Because, after all, you’re just one guy, and there’s not much you can do about it.

Here’s another scenario. Was someone listening to you but you weren’t really telling the truth because you were being nice and polite, because you really didn’t care about the subject, because they were expecting an answer, so you just said the first thing that popped into your mind?

No matter how you slice and dice it, it’s not an easy thing for the little guy to be heard.

But, what if you get to speak about something you care about, only when you feel like it, and you don’t have to worry about hurting anyone’s feelings, and you just let it all out. Wouldn’t that be nice? And then you do it again, and again, and again. You share your thoughts with the whole world, nonstop, 24/7, loudly and with brutal honesty. You’re angry, or ecstatic, or surprised, and you let everyone know about it. You will make them know. Well, then you’re probably a really strange person.

But, even if you are this strange person, there is still a bright side. Now, you can’t be easily dismissed. You must be dealt with. You can’t be ignored because ignoring you will not make you go away. And strange people can do  a lot damage when left unattended. You say whatever you want to say, whenever you want, to whomever you want, as loudly as you want. And it feels great.

Photo credit: mzacha from morguefile.com

Back in the real world, there aren’t many people like that, probably because it’s so exhausting. But a task that is too much for just one person can easily be done by a thousand people if they just all pull the same way.

Social Media, the ultimate strange person.

Social Media is honest and blunt and does not stop. It speaks with a thousand different voices, from a thousand different viewpoints, for a thousand different reasons, and it will speak about you. It will tell you exactly what it thinks of you. It will tell everyone exactly what it thinks of you. You may think this is either a good thing or a terrifying thing but, at the end of the day, the fact remains that this is indeed a very real thing. It is happening right now, it has been happening for a while, and it will happen more and more in the future. The little guy is out of the bottle, and he and his millions of friends are merrily typing away telling the world what they feel.

You can ignore social media at your own peril, or you can do something about it. What is going to be?

How to overcome your fear of social media research

Thursday, July 22nd, 2010

Photo credit: chelle from morguefile.com

Social media research has stepped out of the shadows and into the limelight. Phrases like sentiment analysis, content analysis, text analysis, microblogs,  and web 2.0 have begun to clog up our already over-flowing research dictionaries and caused us to question this strange beast. How can market researchers possibly make sense of it given that it is completely different than anything we’ve seen before?

Let’s consider a few points:

• If you have uploaded survey data into SPSS, you already know how to upload social media research data into SPSS
• If you have used survey data sets with numeric and string variables, you already know what a social media research data set looks like
• If you have selected variables, grouped cases, and run SPSS crosstabs with survey data, you already know how to do those things with social media research data
• If you have built a frequency bar chart or tracking line chart using survey data, you already know how to do it for social media research data
• If you have read survey verbatims before, you already know what you’re looking for in social media research verbatims
• If you have drawn conclusions from survey data before….. why haven’t you transferred your expertise to social media research yet?

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Bet you didn’t know you’re already an expert in analyzing social media data.

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Other blogs that might interest you:
10 things you need to know about social media research
Annie Pettit Discusses Social Media Research at the ARF Audience Measurement conference
Social Media Research: Conversition’s Presentation at MRA Boston
Conversition on Facebook

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IMRO guidelines for research based on social media data

Tuesday, July 20th, 2010

A committee has been formed and brainstorming is underway!

With the realization that research using social media data is quickly gaining in popularity, the IMRO division within the MRA has put together a committee to help define and guide users and providers in this space. Over the next couple of months, a team of 17 or so researchers, including Annie Pettit (@LoveStats) of Conversition Strategies, and led by Jim Longo (@LongoMR) of iTracks, will be putting their heads together to build a short document that will be made publicly available.
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The committee will address a number of issues including what is social media research, how should users evaluate it, what are the essential components for consideration, as well as other key topics. The goal is not to provide rules that must be followed but rather to ensure users and providers are aware of all of the issues when considering and conducting social media research.
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Your opinions are important. Share your thoughts, questions and concerns with us by leaving comments here, emailing Annie (LinkIn) or by emailing Jim Longo.

10 things you need to know about social media research

Monday, July 19th, 2010

The Good

1. Anyone can benefit from social media research even if you have no social media presence. You can research your own brand, your competitors’ brand, the category, or the industry.
2. You can measure far more types of information than the longest survey can. When your survey must be cut-off at 60 questions or 60 minutes, social media research answers questions that might require a 10 hour survey.
3. You can listen to the voice of the consumer in their own, real, unfiltered words. Unlike surveys and focus groups where consumers may clean up their voice, or try to conceal hatred or indifference, genuineness is clear and strong in social media research.
4. You can measure data using any scale imaginable. 2 points, 5 points, 10 points, 100 points. Your wish is our command.
5. You can impress your boss with the statement that you are using data fusion technologies to combine the insights of survey research with those of social media research.

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Photo credit: snowbear from morguefile.com
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The Bad

1. You need to sample your data sources properly, or you won’t be able to predict to the general population of internet users
2. You can’t measure incidence. Just because people don’t say they are using your brand, doesn’t mean they aren’t using it. They just haven’t said so.
3. You can’t measure awareness. Just because people aren’t talking about your brand online, doesn’t mean they haven’t heard of it. They just don’t talk about it.
4. Because most people don’t share their personally identifying information when they contribute online, demographic and geographic is less precise than what you are used to with surveys or focus groups.
5. The validity of sentiment and text analysis differs by vendor. Users of social media research need to ask their provider how they validate their results.

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Buyer beware. Buyer be smart.

The Conversition Hierarchy of Social Media Insight

Thursday, July 15th, 2010

Maslow’s Hierarchy of Needs is a well known theory of human motivation that starts with meeting our basic physiological needs for food and water, and ups the ante to needs of safety, love, self-esteem and self-actualization. The theory behind Maslow’s hierarchy can be used to understand other processes as well, including the application of the scientific method to terabytes, petabytes, and yottabytes of social media data to create social media insight.

No matter the size of your business, social media matters to you. You want and need to know what consumers are saying about you. There are many different approaches to this learning, each building on the previous stage.

This, we have outlined in the Conversition Hierarchy of Social Media Insight.
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Conversition's Hierarchy of Social Media Insight

1. Stage 1 Happenstance reflects the most basic level of social media data understanding wherein social media information is consumed if and when it happens to come your way. Perhaps employees email YouTube comments to you, or consumers leave postings on your website. What you learn depends upon what you happen to hear.
2. Stage 2 Searching reflects active seeking out of information, such as through the use of an internet search engine like Yahoo, Bing, or Google. The search may be a one time occurrence and likely isn’t exhaustive or representative of all the information that actually exists. This is our ‘Need to Hear.’
3. Stage 3 Alerts is the first attempt to gather information using an unbiased and standardized method. Setting up an alert system through a third party, such as Google Alerts,  gives you access to data from a wide range of sources on a regular basis. Though all relevant data will not be identified, at least the data won’t be biased due to the constraints associated with manual searches. This is our ‘Need to Hear Regularly.’
4. Stage 4 Monitoring is the first attempt to put some rules around the data collection. Search terms are now broader, more comprehensive and higher quality. Data is automatically added to databases which allow you to track the volume and source of data over time. Some offerings even include sentiment analysis such that you can determine overall levels of positive and negative sentiment of the opinions collected. This is our ‘Need to Hear the Masses.’
5. Stage 5 Research is the stage that finally turns data into knowledge. By applying strict scientific principles to the collection and analysis of the gathered opinions, valid and reliable generalizations can be made from data which may otherwise be biased, skewed, and unrepresentative of any population other than itself. Regardless of how much or where the data comes from, it has been assembled in ways that allow you to grasp the opinions of the average online consumer, not just the most talkative online consumer. This is our ‘Need to Hear Validly.’
6. Stage 6 Insight is the last stage, the one that all data fans aspire to. This is where data, which has been properly assembled and analyzed, empowers analysts to create insight, that amazing and powerful idea that comes out of nowhere to guide action plans and strategy.

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May your insights be valid and reliable.

Coke it is! Or not. I’m not sure. I can’t tell.

Tuesday, July 13th, 2010

Last but not least, here is our third installment of social media research data quality blunders. Whether you prefer Coke or Pepsi, this one is sure to tickle your fancy.
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After gathering thousands of verbatims from all across the internet, we created a word cloud that would help us determine what are the other types of beverages and brands of beverages that Coke drinkers mention a lot. Obviously, Diet Coke and Cherry Coke are bigs hits, as are Pepsi and Minute Maid. But if you’ve read the last two blogs, you know where we’re going with this.

What exactly would the word cloud look like if we only used words that didn’t actually mean Coca-Cola the delightful bubbly beverage? Prepare to look away if you’re easily shocked. Somehow, if we don’t put any effort into collecting quality, relevant data, we collect a lot of data referencing illegal drugs. Cocaine, marijuana, heroin, and meth rise to the top of the data. I can’t say for sure, but my guess is that Coca-Cola wouldn’t care to have this data affect their results. But that’s just my opinion.

Like this blog? Here are two others in a similar vein.
Apple pie, Apple orchard, Apple cider, or Apple iPad
British Petroleum, Brad Pitt, Blood Pressure, or Basis Points?

Annie Pettit Discusses Social Media Research at the ARF Audience Measurement conference

Wednesday, July 7th, 2010

If you haven’t met Annie before, here’s your chance! At the recent ARF AM5 conference, Annie and Stacey Hall of Peanut Labs spoke about leveraging social media research in the arena of television audience measurement. In this video, filmed and presented by ScribeMedia.org, she discusses some of the unique aspects associated with Conversition’s social media research product, evolisten.

If you were unable to ask questions at the conference, now is your chance!

Conversition speaks! Wed, 2pm, Boston, MRA – Will you listen?

Sunday, June 6th, 2010

Research In The Cloud
From Buzz to Biz – Social Media Research for Results

Wednesday, June 9
2:00 – 3:15 p.m. Educational Sessions
PRC: 1.25 Contact Hours in Research

This session will discuss a new methodology for marketing research. Though the Internet has made data collection via online surveys and focus groups a practical marketing research tool for over a decade, it is only in recent months that this data source has become viable. Using real data, the presenter will demonstrate how gathering and analyzing existing data from the Internet, such as is available through Facebook, Twitter, or Blogger, can reach beyond simple ‘buzz’ features to become actionable marketing research data. Pros and cons of the method will be demonstrated including research fundamentals and data quality.

How to choose between human coders and automated coders

Thursday, June 3rd, 2010

Photo credit: cohdra from morguefile.com

In the right hands, text analytics can turn a nightmare into a dream come true. With the increasing popularity of social media research, companies are regularly collecting thousands, and even millions, of verbatims that require analysis. On the other hand, human coders have been carrying out text analytics for decades now, and in particular, why use automated systems when humans are doing the job so well?

Here are some guidelines to help you decide which method is right for you.

1. Sample sizes – Sample size will likely be the most prominent variable in choosing a method. If you’re working with thousands or millions of verbatims, automated systems are your best friend. On the other hand, databases of several hundred verbatims are best done by hand. Remember, even if an automated system is used on a small dataset, you would still end up reading every verbatim to get a human flavor for the data. If you’re going to read every verbatim, you might as well do the analysis by hand.
2. Number of constructs – If you normally use only a small number of predefined constructs, the human method is works great. Coders can easily remember all the intricacies of the coding scheme if it is strict and well-defined. And of course, it’s fun and interesting to get your hands right in there. But, if the research plan uses coding systems with hundreds or thousands of constructs, it is simply impossible for coders to remember all of them with sufficient within or between-rater reliability. Automated systems can really ease this process.
3. New constructs – Are you open to discovering and implementing any number of new constructs? If you’re open to adding a handful of new constructs, then automated systems won’t make it much easier for you and you will be happy with your standard manual processes. But, if you want to be surprised and see where the data takes you, automated systems can provide that.
4. Timing – This is the business world, after all. Are you in a rush? Are the results required yesterday? Well, if the data is already in a clean, computerized format, an automated system will work nicely. But, if your data consists of 20 sets of handwritten notes, most of which are barely legible, you might prefer the brain power of human coders who can turn scribbles into codes without any intervening translations.
5. Coder reliability – Are you able to train and retain enough reliable coders? If you have a good team of trusty reliable coders, then keep them happy. They are valuable people who should be treated with kid gloves! But, if you’re having trouble finding those gems, an automated system will ensure that a high level of within-rater and between-rater reliability is maintained. It will even eliminate within-pair compromise.

In the end, you must choose the system that works best for you. Whether automated or human, one method with have the pros and cons that suit your specific needs. Choose well!

SocialVoice – A Social Media Research Product By Conversition and Peanut Labs

Thursday, May 13th, 2010