Tag Archives: social media research

Social noise – cacophony or symphony #MRSlive @TweetMRS #MRX 

Live blogged at MRS in London. Any errors or bad jokes are my own.

The art of noise by Tom Ewing

  • #IPAsocialworksinitiative – to guide effective use of social media data
  • It’s all about measuring not counting, Ray Poynter wrote this part
  • The insight guide  is being written by Tom Ewing and he is interviewing people for it
  • Five basic questions
  1. What questions do you need to answer, what decisions will betaken because of it
  2. What do you know already, existing research, behavioural
  3. What social behaviora are you looking for, what data sources, do you need aggregate data or granular level
  4. What is the relevant timescale, ad hoc or continuous, how do you know yyou’re finished
  5. Do you need quant metrics, what are they, it’s more than likes follows
  • We have reached the peak of social tech
  • Seth Grimes says the state of social insight is “confused,” it’s not really a mature technology, widely adopted, but not fully integrated
  • It’s the early majority now, tactical, silos, unstructured text, the future is here but it is unevenly distributed
  • We need to clear out the cliches, integrate with methodologies, integrate with insights and business and people 
  • Different poll results would arise if you use Twitter vs Facebook [i see this as a sampling problem, you don’t just take any church or school or company and say it is representative]
  • UK Facebook data is closer to a census than a sample [but it is still very much a sample!]
  • You can join insights with other methodologies [data fusion is ALWAYS wise, every method reveals different insights]
  • Provide more file and predictive tracking systems and an ability to get granular and specific
  • Who owns social insight? Is it marketing? Analytics? Insights? PR? Sales? It’s more about collaborating  [why must one group OWN it, everyone can benefit hugely from it]
  • Finding common ground – we’re all working toward the same goal, emotional understanding of people
  • Limits of real time means it’s more tactical but there is indeed strategic value
  • How do you get insight about a topic when you know nothing about it [oh goodness, I could go on about this. I was asked to draw insights about cars and trucks. I know NOTHING about them and couldn’t understand anything people were talking about. Expertise in the topic is a MUST! Put me on the food/outdoors/music research.]
  • AI is already doing so much work that people would have done – collecting data, sorting and coding, analyzing, prepping, reporting
  • Social insight begins with social practice, use new platforms like Whatsapp and snapchat, look beyond the brand level to the topic level, consider pictures and video, look for patterns at the network level
  • Different things come out via text and images but you wno’t know unless you plan and look for differences in different types of content
  • We are working towards general use, stratégie, cooperation, seamless integration among people, rich media as well as unstructured text
  • Tom asks people to submit their social media case studies to him for publication in the book

Finding insight in 140 characters by Jake Steadman

  • Jake [not from Statefarm] speaks
  • Story about Star Wars, in 1977, need to tap into mainstream media, tap into core group of fans, went on TV and publications. FOr second movie he went to com icon. Fans went in the hundreds to see them in person for Q and A.
  • Today, mobile is eating other media time.everyone has a mobile phone. December of last year, new Star Wars came out. Still need media and interest and fan base. THey launched on Twitter. That tweet drove all the other media. Drove coverage in print. Access to the stars still applies but they did it more directly and personal on Twitter. Stars did this on the red carpet, backstage, White House visits, all on Twitter. 1.2 billion tweets on opening weekend.
  • All social data can drive insight
  • There are culture issues and there are tools. 
  • Rise of the machines, machines allow you to become storytellers and consultants, it allows you to be a leader not a methodological policeman
  • Let’s you do same day insights and be agility, we need to get over our obsession with precision, forget statistical precision [agreed, don’t create precision with decimal places, know when your data is directional and don’t make it more than it is ]
  • Social is the democratization of data, client side is more like to be using social, agencies are more likely to be using big data, agencies need to be more for less and quicker
  • Look for your soggy fries – customers were starting be less loyal with a restaurant, you could run a large research project, or you could look at social data immediately, found many uses of the word ‘soggy fries’, it didn’t need precision but rather it needed recognition

Panel with Jenny Burns, Christopher Wellbelove, Jess Owens, James Devon

  • Some people jump at social media because it’s cheaper than things like focus groups [be cautious, cheaper means you need to spend more time thinking and analyzing it]
  • Lots of people are analyzing social media without ever using it, you need to use the tools to really understand them [the speaker has now gone through three pairs of google glasses, and might be tweeting as we speak 🙂 ]
  • Social media is still treated as a slightly dangerous cousin
  • 67% of people using social media puts it really into late adoption, it is not new nor early adopter territory 
  • It says more about the market research industry being years behind to be so late in using this technology
  • Privacy and ethics still matter, some companies get individual permission to review Twitter accounts
  • People need to understand how their data is being used, whether it’s aggregated, Facebook data is fully anonymized and aggregated and great for ethics and privacy

[I kind of like have a couple presentations followed by a separate panel]


    Opening plenary session: Trends, Mobile Surveys, and Hacking Data #IIeX

    Live blogged at #IIeX Atlanta. Any errors or bad jokes are my own. 

    Using future trends to change business outcomes by J. Walker Smith

    • we should focus more on the vanishing point, turning points that look like cliffs not hockey sticks
    • we always look for the next best thing, weak signals getting stronger, before things become mainstream
    • its a coding problem, how do you know what to look for if you’ve never seen it, we don’t know how to look for it, is it just luck

    • experts are worse than chance at predicting the future
    • start with things you know how to code for, the obvious big things that you can’t ignore, what are the strong signals that are weakening because these are where innovation opportunities are opening up
    • narrow field of view to zero in on one spot where we know change is going to occur, these are unrecognized things that are already eroding.
    • big things have to make room for smaller things to spread
    • single households/solo living is the next big thing approach, we need products and services to allow people to live solo livestyles. but this is wrong. single households are just one small piece of a major dynamic. Bigger dynamic is actually shift from marrying early to marrying later. Vanishing point is marrying early. Many reasons for this. Result is not no marriage or solo living. People still get married but it’s just later. Longer transition to a married lifestyle.
    • In USA, 7 year increase, China 1 year, Russia, 2 years, India 3 years, [sorry, can’t read the others but some countries look like marrying up to 10 years later!]
    • People are not learning how to live alone but how to connect. How do you replace the lost family connections around things like eating a meal. Zipbob is a website where single people make restaurant reservations to share a meal with strangers. Mokbang is a website where you livestream with foodporn stars eating meals.  Use technology to live together in a different way.
    • The Kinship economy – data is always a secondary consideration of technology. Its always been about connecting people.
    • We spend all our time trying to get people to connect with our brand. We brought this to social media in the last ten years. But people don’t want a relationship with your brand but rather with people.
    • we need to be in the business of social currency, give people a way to connect with other people.
    • the bigger opportunity space is togetherness not single-ness.
    • [interesting talk, never really thought about it like that]

    Who needs to ask a question? Using social media data to predict behavior by Vesselin Popov

    • digital footprints are a new way of doing psychometrics [i LOVE psychometrics. that was my career goal that led me to MR]
    • started with a facebook app mypersonality, among many other test games. They let people take them for free. Asked people to opt in to share the data with them. 6 million people shared their data. They share this data with 18 universities. They also have people’s status updates and facebook demos likes etc.
    • Is there a relatinship between your likes and your personality profile. Massively.
    • Compared friend ratings to computer model. Computer is better than a human judge once you have 300 likes. Used the Big 5 Index.
    • Can predict intelligence, life satisfaction, and more
    • Can compare profiles of people who like tom cruise vs frank sinatra – sinatra is more liberal and artistic. Artistic people like oscar wilde, banhause, plato, jon waters, Leonard Cohen. Try targeting on these criteria
    • introverts use different words than extraverts who talk about parties, night, tonight, weekend, excited where introverts talk about computers, anime [seriously? anime suggests a very skewed sample of introverts participated. Or we’re looking at differences due to decimal places not reality]
    • you can reach the hard to reach through their digital footprint [if you have permission to do so, just because you have a facebook profile doesn’t mean you’ve opted in to research]

    It’s not me, It’s you: Research participants and data speak on mobile design and data quality by Melanie Courtright

    • we take participants for granted, we make promises to them and disappoint them

    •  we promise that they can answer the surveys, that we’ll be device agnostic but we’re now. More than half of surveys fail when taken on a mobile device. Enrollment via mobile device as increased by 300%
    • Most often a grid is turned into a set of vertical scale single questions
    • PC style surveys on a smartphone take ridiculous amount of time. people speed through once they’ve had enough. Speeding or quiting – what’s your preference.
    • Enjoyability scores are massively lower. Ease scores are a lot lower as well. When it’s fun and easy, people use the variability that is present in the scale.
    • people stop using the end of scale because it’s too difficult to do all the scrolling
    • when all the data is living together, you only need to ask questions about what isn’t already in that data. we must ask less and track more. don’t ask everything you can think of. stop ‘just adding one more question’
    • right isn’t always easy.

    Hacking insights to drive innovation and ROI by Rolfe Swinton

    • cracker is someone who hacks with malicious intent
    • playful solving of technical work that requires deep understanding especially of a computer system
    • do you want your parole board meeting at 9am or 4pm? It’s just data right? the best time is first thing in the morning, immediately after lunch, or immediately after break. Never just before break time or home time.
    • sensor technology is becoming ubiquitous and nearly free. first gps cost $120000, now it’s $50
    • are companies changing at the same rate? digital video growth is 3 times in the last 3 years, across all age groups
    • hacking reason – tackling big problems requires a lot of components coming together
    • hacking reason – needs to be an act of play, need to take risks and have fun
    • when should you reach car buyers? peeople think about hair cuts near the end of the week,  cars they think about at the beginning of the week and go at the end of the wee

    The Book of Blogs: Social Media Research Chords and Lyrics #NSMNSS

    Book of Blogs social media in social research kindleAre you ready kids!

    For the musicians among us, let’s celebrate the launch of “Social Media in Social Research: Blogs on Blurring the Boundaries” edited by Kandy Woodfield with a little song. Please enjoy this slight adjustment to Peter Gabriel’s song. I couldn’t help myself!

    If you take a video of yourself playing the song, I’ll post it here for everyone to enjoy. And if you’re lucky (unlucky?), I might post one of myself playing the ukulele.


    The Book Of Blogs by Annie Pettit

    (Better known as the Book of Love by Peter Gabriel, from the 2004 Movie “Shall We Dance”)

    *** Capo on Fret 1
    *** Actual Key Is Ab / Play in Key of G

    Each line transitions through G C D G

    Intro – G/C/D/G — G/C/D/G —  G/C/D/G  — G/C/D/G

    The book of blogs is long and helpful
    You can learn social research from it
    It’s full of charts and facts and figures
    and instructions on new methods

    And I……..
    I love it when you read it to me
    And you……….
    You can buy me the Book of Blogs

    The book of blogs has insight in it
    In fact that’s where insight comes from
    Some of it is just transcendental
    Some of it is up for debate

    And I……..
    I love it when you read to me
    And you……….
    You can buy me the Book of Blogs

    Bridge: G/C/D/G  — G/C/D/G  — G/C/D/G  — G/C/D/G

    The book of blogs inspires to try it
    It’s written by such great authors
    It’s got advice on social research
    You should try to implement

    And I……..
    I love it when you read to me
    And you……….
    You can buy me the Book of Blogs

    And I……..
    I love it when you read to me
    And you……….
    You can buy me the Book of Blogs

    And I……..
    I love it when you read to me
    And you……….
    You ought to buy the Book of Blogs
    You ought to buy the book for me

    Launching Today! Social Media in Social Research: Blogs on Blurring the Boundaries #NSMNSS

    Book of Blogs social media in social research kindleOn Wednesday October 29, 2014, a brand new book is being released including a chapter by moi! It’s called “Social Media in Social Research: Blogs on Blurring the Boundaries” and it’s edited by Kandy Woodfield who is the Learning and Enterprise Director at NatCen Social Research, and the co-founder of the NSMNSS network. Buy the book on Amazon and leave a review!

    Social research as a craft, a profession, is all about making sense of the worlds and networks we and others live in, how strange would it be then if the methods and tools we use to navigate these new social worlds were not also changing and flexing.  Our network set out to give researchers a space to reflect on how social media and new forms of data were challenging conventional research practice and how we engage with research participants and audiences. If we had found little to discuss and little change it would have been worrying, I am relieved to report the opposite, researchers have been eager to share their experiences, dissect their success at using new methods and explore knotty questions about robustness, ethics and methods.

    Our forthcoming  book of blogs is our members take on what that changing methodological world feels like to them, it’s about where the boundaries are blurring between disciplines and methods, roles and realities. It is not a peer reviewed collection and it’s not meant to be used as a text book, what we hope it offers is a series of challenging, interesting, topical perspectives on how social research is adapting, or not, in the face of huge technological and social change.

    You can join us for the virtual launch by following the tweets here or the blog posts here. I won’t be able to attend the launch but you just might catch me in a quick video. I’ll see you there virtually!

    book of blogs blurring boundaries social media research

    Building a Social Spine in Tracking Research by Larry Friedman #FOCI14 #MRX

    Live blogging from the #FOCI14 conference in Universal City. Any errors or bad jokes are my own.foci14

    Building a Social Spine in Tracking Research
    Larry Friedman, TNS

    • turn tracking research from a rear-view mirror into something that is windshield oriented, looks to the future
    • historically tracking is survey research
    • lots of information is observable, passive, that we didn’t have available before – social data
    • we need to use obtrusive (surveys) and unobtrusive research together, MR rarely uses unobtrusive methods
    • The Trouble With Tracking – insights not actionable, flat-line metrics, far from real time, long vague surveys
    • is social media data a real alternative? real time, sensitive to events real consumers talking to each other in their own words at their own pace
    • has social worked? hasn’t made the case yet, mostly because there is a lot of discussion and it’s not always what we’re interested in, hard to find the signal over all the noise. hard to understand what the metrics really mean. people want a one-to-one metric with external measures as in how we compare survey metrics
    • what does the number of negative mentions in social really mean? how does it compare and to what?
    • some worry that social isn’t representative because not everyone is online, not everyone uses these tools [and everyone participate in surveys??]
    • the real issue however is predictability. even if it’s not representative, if it predicts it’s got value [heck yeah! first time I’ve ever heard someone other than myself shout this out]
    • should social data look the same as survey data? why should it? shouldn’t it really be different?
    • great success in predicting brand health by putting social and search data in the model
    • data cleaning is extremely essential, discussion must come from the correct geography – avoid english conversations around the world, avoid the coupon and sales bots, ensure you are getting apple computers not apple pie
    • social lets your track your brand equity today instead of 3 weeks from now when something major could have happened and been dealt with
    • make the social equity score a leading indicator, plan for several weeks ahead, prevent problems sooner
    • most social analyses are mass market analyses, we can’t throw away surveys just yet. surveys are needed for deep dives
    • models need to be updated more frequently – pinterest and vine are brand new and suddenly huge, social sites will come and go very quickly
    • google modeled trends in flu reporting, people search for flu symptoms online – model could anticipate trends in flu that CDC was reporting, model worked well for a couple years. model is no longer active perhaps because google changed how it does it’s search terms, changing their own data changed their own model
    • old tracking model was a project on it’s own, you discussed not changing the tracker so as not to change the trend.
    • new tracking model is an integrated program from a variety of sources to give a forward look into the market place
    • need to consider what consumers say (survey), think (social), and do (POS)
    • able to predict car registrations by using all forms of data together
    • difficult part – we see a trend that is decreasing and so take action to improve it… and then the trend increases. but was your prediction accurate? did you fix the problem or did the trend just increase as it was going to anyways?
    • why do you use tracking surveys if you make no changes to affect those ratings? why bother tracking numbers that never change [fabulous point]
    • we need to learn more about which and when spikes matter

    Other Posts

    Social listening is just a keyword search #mrx

    Social media listening is easy. You type in your keywords and data magically appears. Yup, it’s as simple as writing a survey or putting together a discussion guide. Anyone can do it with great results.

    Users of listening research see how easy keyword searches are by doing simple keyword searches in google. But what they don’t see is the massive programming effort that google puts into interpreting your simple search, imagining what you really want, comparing your words with those of billions of other searches to tease out the garbage that ought to have shown up but didn’t.

    In fact, these are the same smarts that your listening expert uses on your behalf that you never see. These are the smarts that turn your ubiquitous words into something meaningful, consumer typos into brand names, consumer slang into brand names. These are the same smarts that know your favourite associated word brings in more spam than real data, your preferred hashtag brings in competitor data, and your most important product feature is used by pornographers around the world.

    It’s not just a keyword search. It’s 4 or 8 and sometimes even 16 hours working on a intricate algorithm that collects the most and most relevant, high quality data possible. It’s not just a keyword search. It’s the art and science of social listening research.

    –Written on the go

    Truth about Social Media Research by Mallios and Smithee, Spych #MRA_National #MRX

    … Live blogging from Disney Orlando, any errors are my own…

    The Truth About Social Media Research… Peeking Behind the Curtain

    Katy Mallios, Research Consultant; SPYCHBen Smithee, CEO, SPYCH


    • People are willing to put their deeply personal life on social media, because they want to not because they’re being paid for it
    • Social listening is the foundation of social research, it’s more observing than listening, focus on vanity metrics such as likes, followers, sentiment
    • Old style was just a whole lot of people screaming, seemed like we couldn’t hear for all the noise
    • We wonder if we can really learn anything, if they’re real people,what are they supposed to do with the data, is it just a fad
    • How did we use the data? comment pathways, manually review blog data, basic facebook searches and all this just leads to basic monitoring, high level awareness, ideas to build better discussion guides
    • Most people are in the general listening stage right now
    • We need knowledge and understanding, not just awareness, we need context not just content, we now have more advanced and embedded metrics that help us build better stories; this is where the dollar value is
    • But the data isn’t representative!!!!  Well, it’s representative of certain things. Is it qual or quant?
    • What defines value to a client?
    • Sentiment is a revolving door longitudinal measure, there is still human input needed. Humans are required to do it right
    • The numbers don’t matter, comparisons matter
    • Brand health is measured on every project. Aggregated brand metrics matter, industry specific measures as well
    • New layer of life insights – understand product integration, at what stage and for how long, when does it exit the consumer’s life
    • People talk about commercials and will share them on their facebook, twitter pages, and hit the like buttons on YouTube and elsewhere
    A selfie I took last week in vancouver - but no brands in the background. "This responder likes the outdoors"

    A selfie I took last week in vancouver – but no brands in the background. “This responder likes the outdoors”

    • What is social intelligence? Cross platform measurement, not just number of tweets and likes.  It’s actionability.
    • How does social tie in with CRM and sales data. Dirty fixes are required to get to this level of actionability. see how tweets compare to purchase behaviour. Why don’t people “check-in” every time they visit our establishment?
    •  In the future, major clients will drive changes in technology so that all software systems talk together, listening and CRM and sales all in one
    • Automated actionability – based on XYZ in automated sentiment, we will create marketing strategy A or B
    • Human actionability – someone still needs to interpret everything, do the gut check, make the big decisions
    • Get past the “flash” and go back to basics, he who asks the best questions wins, the brands that do this best are winning
    • What other life aspects can we tap into that will help increase our own loyalty – e.g., send them coupons based on what is in the background of their selfie
    • Move from competitor comparison to competitors identification, where are the next two moms who got upset with my brand
    • What dynamic content can we put into place based on our sentiment and lagging sentiment
    • How can we incorporate current content into our next media launch, in a measureable way?  Ask questions on their facebook page, on their blogging page.
    • The Ripple Effect – length of time for an action to have a digital impact, e.g., time between campaign launch and consumers chatting about it, optimize positive, minimize negative, measure duration
    • This data informs marketing and other groups within the brand organization
    • MOM metrics – missed opportunity metrics – these are opportunities for positive re-engagement, opportunities for brand expansion, opportunities for negative conversions
    • Optimize your key words, most important things [in other words, don’t name your brand something like gap, target, apple]
    • Be careful to separate data out by type – sponsorships, paid bloggers, contests, you can look at each part as need be

    The four toughest questions you must ask #MRX

    Question dog

    What exactly are the toughest questions when it comes to social media listening research? They’re the ones that force you to admit your weaknesses, your faults, your errors. So if you’re going to take the plunge, here are five questions that could make vendors squirm.

    1. What percentage of your social media data is associated with gender? age? country?  It’s really easy to say “We have demographic data.” It’s really hard to say “Only 1% of our data has age.” If you need demographic information, you need to get an honest answer before you sign the deal.
    2. How much time does a human being spend cleaning out the spam? It’s easy to say “Humans review all of our data.” It’s a lot harder to say “Humans will spend about 2 minutes on your data.” If you need your data cleaned of spam and completely relevant, you’d better hear numbers like 8 hours per brand.
    3. What happens when data comes from a ten year old? It’s easy to say “They’re all grouped together.” It’s really hard to say “We delete all data from children aged 13 and under.”
    4. How valid is your sentiment scoring? It’s really easy to say “Our validity scores are 90% and higher.” It’s really hard to say “Because of sarcasm, evolving language, poor grammar,and many other problems, our validity scores are around 70%.”

    Go ahead. Make them squirm.

    Why social media listening research hasn’t lived up to the hype #MRX

    Tales of the Teenage Mutant Ninja Turtles #3. ...

    It’s quite simple really.

    Vendors have been over-stating the advantages and under-stating the disadvantages.

    Is demographic data available for social media data. YES! Absolutely!  We’ve got tons of demographic data! Come buy our data! Of course, you don’t realize until you get your hands in the data that only a tiny percentage of verbatims actually have demos, and it’s only age or gender or region. Forget income, education, household size, religion, race, and all the other demographics you are used to seeing in survey research. But did you ask your vendor what percentage of verbatims had demographic data? Probably not. But you shouldn’t have had to.

    Is there data for my brand? YES! Absolutely! What was your brand again? Some tiny, obscure brand that has a generic name like Target, Gap, or Apple? No problem! Here’s your 5 million records of which only 1000 actually reference your brand. Of course, you won’t know that until you get your hands in the data and realize it’s mostly garbage. Should that have happened? Absolutely not.

    Is the sentiment scoring accurate? YES! Absolutely! We ran some tests to prove that our data is scored 99.9999% accurately, especially when we delete all the data we aren’t sure about so you aren’t actually getting to see all your data. Of course, once you get your hands in the data, you will find big, huge chunks of data that are scored completely wrong. Should it be a surprise to you that much of your data was deleted or scored incorrectly? Most definitely not.

    You know, this is probably no different than getting a new Barbie or a new Teenage Mutant Ninja Turtle for your birthday. When a bright and shiny new toy is placed in front of us, it’s hard to see the negatives. It’s pretty, it looks fun, and we just want to play with it. It’s not until we rip off the wrapper and remove the marketing curtain that we  truly see for ourselves what’s going on. Barbie’s lipstick is on crooked, she’s missing a shoe, and unlike the commercial, not a single one of the Turtles can jump 50 feet in the air without the aid of a firecracker.

    Perhaps this is a call to action. If you find yourself in the trough of disillusionment, ask yourself why. Were you eager to believe something that was too good to be true? Did you use your market research skills to thoroughly probe and analyze and critique the messages you heard when you were in the process of buying listening research? Did you fall for marketing hype over good sense? Did your vendor make false promises? Sigh. False promises.

    %d bloggers like this: