Jackie Rousseau-Anderson, the Consumer Insights Analyst on the Technographics team at Forrester, recently met with Conversition to review our Evolisten product. In her blog, she says “I have seen the future.” She goes on to say, “the data-loving geek in me was completely mesmerized.”
All we can say is we’re glad you liked it! To our readers, do email us at sales @ conversition.com if you’d like your own personalized demo. We’d like to try to mesmerize you too!
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.
.
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.
.
Your opinions are important. Share your thoughts, questions and concerns with us by leaving comments here, emailing Annie (LinkIn) or by emailing Jim Longo.
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.
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.
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.
You can measure data using any scale imaginable. 2 points, 5 points, 10 points, 100 points. Your wish is our command.
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.
You need to sample your data sources properly, or you won’t be able to predict to the general population of internet users
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.
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.
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.
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.
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.
.
Conversition's Hierarchy of Social Media Insight
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.
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.’
Stage 3 Alertsis 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.’
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.’
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.’
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.
If you thought Old Spice was just for your grandfather, the brand is working hard to change your mind with a series of commercials starring @IsaiahMustafa. The commercials have become a viral hit and have expanded into short videos, each one a unique hilarious reply to people’s online tweets, youtube comments, and questions. Questions from real people, and celebrities like The Ellen Show, Alyssa Milano, and Ryan Seacrest, are all getting individual attention.
How are people describing this campaign? The top words include funny, original, hilarious, brilliant, and genius, definitely words I’d like my brand associated with. But on an aggregate level, the campaign has far surpassed any standards of making the grade. Compared to the average brand which generates about 30% positive opinions, the Old Spice campaign is achieving positive opinions in the 40%, 50%, and 60% ranges.
People appreciate the business side of things, including the product launch (66% positive), the creativity (59% positive), and that it’s a new and different approach (57% positive). But, they are also expressing their appreciation for Isaiah, a manly man himself, giving him top marks for his smile (59% positive), his teeth (57% positive) and his sex appeal (54%).
What isn’t so positive? The ever present fear factor associated with sexuality and homophobia, comments which generate 25% negative opinions. Fortunately though, this small minority of people can’t compete with the millions of people who are loving every minute.
Isaiah, keep on smelling like the man our men could smell like.
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.
.
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.
On to part 2 of data quality! Ok, so BP was a bad example. Obviously, a lot of different brands and people and things will have the initials BP. It’s an isolated case. But is it? Here is another great example of how data quality begins at the very beginning of any social media research project.
The scenario is the same. We gathered thousands of verbatims from thousands of websites and created a word cloud of all things related to Apple. The usual suspects are all there. Competitive brands like HP, Hitachi, and Toshiba are well represented. And, since the iPad is the greatest discovery in all of mankind EVER, it is the most prominent feature of the cloud.
.
But wait. Isn’t there more to Apple than just computers? Here is a second word cloud we created from the very same data. No manipulations and no sneaky subsampling. What’s with all this apple pie, apple cider, and apple cinnamon deliciousness? This is simply another great example of poor quality workmanship inviting terribly incorrect confounds.
Is social media research fast? Sure it is. It’s even faster if you ignore the annoying stage of data quality.
The time is now. Spain vs Netherlands. Who will win? Who can say? Paul the Octopus can say as evidenced by his 80% accurate predictions. Science always comes through in the end.
Given Paul’s extraordinary celebrity status, we decided to do some scientific research of our own. We gathered thousands of conversations from thousands of different websites and conducted our own version of science, social media research, that is.
Right now, Paul is viewed quite favorably by those who feel he is important enough to talk about. Opinions towards Paul are 34% positive, including 5.5% of people who just love him.
However, about 54% of conversations are neutral with another 4.5% being negative, possibly people who love him literally to death. We should assume those negative opinions are from people who are now regretting cheering for the losing teams. They are regretting their choices so much that they have selected a specific use for poor Paul, and have overwhelming chosen to cook him for dinner. What are the preferred cooking methods you ask? Frying has taken the lead position and is preferred by 56% of the nellys followed by grilling, boiling, and barbequing.
But who do the people think will win? Spain is generating about 52% of the conversation while the Netherlands is generating about 48% of the conversation. But, the Netherlands is generating 42% positive scores (of whom 8% would bet their life) compared to Spain’s 37% positive scores (of whom 7% would bet their life).
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!
Unlike other types of research, social media research has the potential to provide brands with millions of relevant datapoints. That is, of course, as long as sufficient work is put into gathering the right data. What exactly is the right data? If you do Google “BP,” about 200 million records will be found. And given the severity around the situation in the Gulf, the first few hundreds of pages are all about British Petroleum. We carefully gathered thousands of records that specifically related to British Petroleum and created a quick word cloud of the types of companies that were mentioned. Not surprising, energy and finance companies were top of the list.
However, just two months ago, if you had googled “BP,” chances are you would have returned very different data. Perhaps it would have been about Brad Pitt or Basis Points or Blood Pressure, who’s to say? Well, we created a second word cloud that was based on sloppy data collection. Any mention of BP in social media was collected regardless of the context. As you can see in the cloud, BP most commonly stands for Blood Pressure. This is a huge confound that absolutely must be avoided.
Imagine how the research results would be affected if blood pressure data was included with British Petroleum data. We would be astonished that fishermen were using Zocor to try and calm down after watching Inglourious Basterds.
