Digital Networking for the Skeptic Leader
This post originally appeared on the Sklar Wilton & Associates blog.
There are many reasons to love the internet but my top reason is that it shrinks the world to fit into my own backyard. Whether someone lives in Australia, India, Japan, Finland, South Africa, Venezuela, Mexico, or even in another province of Canada, I can communicate with all of them on a personal, one to one basis any time and any day I want. Networking with a global community of industry experts has never been easier and, given global accessibility and the accelerated rate of technological innovations, never more essential.
One of the main problems people have with social media networks and digital networking, however, is that the tools are boring, irrelevant, or waste a lot of time. A few quick tips might help to improve the experience so that you too can benefit from digital networking.
1. Find the social network that’s right for you
There are hundreds of social networks but you only need to find and participate in the one that suits you best. If you are visually oriented, head off to Pinterest or Instagram. If you want to get to know people personally, Facebook is the place for you. If you like a mixture of personal and business content that is short and sweet, Twitter is the place for you. If you’re all business, all the time, LinkedIn will suit you perfectly. Indeed, anyone wishing to grow their brand or further their career should be active on LinkedIn.
There are many more networks to choose from but the bulk of English industry conversations take place on these networks. You could try QQ.com or Weibo.com if you speak Chinese, or Vk.com if you speak Russian.
2. Focus on people in your industry
Most social networks try to help new users by suggesting accounts to follow. Bad idea! Absolutely never follow their recommendations. If you are forced to do so to get your account working, be sure to unfollow those accounts as quickly as you can. Following celebrities, athletes, musicians, and pundits might be fun at first but, over time, you’ll find that type of content to be sensationalist and boring. You’ll probably even give up.
Instead, seek out people in your field, including industry experts, keeners, and hobbyists. If your industry is marketing, search for keywords like marketing, advertising, branding, retail, customers, consumers, messaging, pricing, or targeting. If your industry is market research, search for keywords like analytics, data, ethnography, focus groups, insights. Identify the relevant hashtags such as #marketing, #advertising, #branding, #MRX, or #NewMR. Find your relevant industry association. Identify the people who use those words and follow their accounts.
Even better, identify at least one expert who is well known in your industry and follow all the accounts they follow. More specifically, take care to follow personal accounts that showcase the names and photos of human beings not business accounts with names and logos of businesses.
To ensure you’ve always got a regular stream of new, interesting, and unusual ideas flowing through your stream, follow at least 1000 accounts from around the world. You aren’t supposed to read everything from these 1000 people as if they’re emails or personal messages. Rather, glance at whatever is passing through your stream when you happen to feel like taking a peek.
3. Go beyond surfing and lurking
Social networks are supposed to be social but that doesn’t mean you have to share photos of your dinner or your kids (actually, give your kids the gift of privacy and don’t share any information about them online). You also don’t have to fill up the interweebs with random chatter just for the sake of being able to say you participated.
In the digital space, you are encouraged and expected to communicate with anyone, even world renowned, industry gurus, about anything. When you do see a post that is interesting or thought provoking, reply or leave a comment for the author. Let them know you liked their idea or share your own experience with the topic.
In addition to replying to comments, be sure to share your own ideas. Many people think they have nothing interesting to say, nothing new to say, or simply nothing worth sharing. I can 100% assure you that this is wrong. Everyone is an expert in something. Everyone has a unique perspective on even the most ordinary topics. The trick is simply to recognize when one of those opinions has popped into your head.
When you do share and comment, you’ll quickly become part of a conversation with people you’ve never talked to before but who now look forward to hearing from you. You never know who you’ll become fast friends with, who might ask you to speak at a conference, or who might turn into your best client.
4. Communicate on a personal level
Networks like LinkedIn try to be helpful by giving users templated responses, sometimes suggesting phrases such as “I’ll be in touch” or “thank you” as one-click responses. Unless you need to reply to a hundred messages in the next five minutes, don’t take the bait. Take the time to respond to every person individually with a relevant thought or comment, even if it is simply a more personal way of saying “thanks a bunch!”
Some networks allow you to send automated messages. For instance, Twitter can be set up so that any new follower automatically receives a private message thanking them for the follow. Some people create longer private messages that include further contact information about their products and services. Don’t do that. Most automated messages are unwelcome. In fact, they might even encourage someone to stop following you. If you truly want to thank people for following your account, take the time to do it personally.
5. Social media is for social not selling
If your title begins with a C (e.g., Chief, Consultant) or has the word “business” or “sales” in it, chances are every time you talk to someone, your brain tries to force you to offer a sales pitch or to invite someone to review your products and services. Don’t do it. Turn off that part of your brain. Beginning any new relationship with a sales pitch is a sure fire way to encourage someone to click on the mute/unfriend/unfollow/block button.
Instead, get to know people. Simply chat with people. Engage in some genuine conversation about the state of the industry. Learn what industry topics are important to them and what their challenges are. As part of a normal conversation between friends. Over time, you might experience the ultimate metric of success… you might find that you are asked for a pitch.
6. Keep your profile current
Over time, you`ll learn more about your industry, and your interests and experiences will evolve. The profile you set up on a social media account 3 years ago may have been fun and relevant then, but it certainly doesn’t describe who you are today. Sometimes, that very short profile is all that people will see about you so make sure it reflects who you are today, not the young and uninformed kid you were 3 years ago. Current photos help new friends recognize you in the conference crowd, and current websites help potential clients learn more about your services on their own initiative. Make it a habit to update, or at least check, your information once each year.
Above all, don’t stress. If you find a social network to be overwhelming or unhelpful, find a buddy who can guide you through the intricacies and help you find a strategy that works for you.
Perhaps you’d like these posts too…
- 6 Tips to Build a Dashboard the C-Suite Will Want to Use
- 10 Things We Learned about Qualitative Research in 2017
This post was written in my role as a consultant for Sklar Wilton & Associates. Sklar Wilton & Associates has worked for more than 30 years with some of Canada’s most iconic brands to help them solve tough business challenges to unlock growth and build stronger brands. SW&A was recognized as a Great Workplace for Women in 2018, and the Best Workplace in Canada for Small Companies in 2017 by the Great Place To Work® Institute. Recognized as the number one Employee Recommended Workplace among small private employers by the Globe and Mail and Morneau Shepell in 2017, SW&A achieved ERW certification again in 2018.
6 reasons to connect online with people you’ve never met
Everyone has their own strategy with LinkedIn. Some people choose to only connect with people they’ve physically met. Others choose to connect with people they’ve at least spoken to, whether physically or on the phone. I, however, have a different strategy.
I like to connect with anyone who touches my industry regardless of whether we’ve ever spoken or crossed paths. I might be in market research, but if you’re in marketing, AR/VR/MR/XR, big data, analytics, data journalism, neuroscience, biometrics, polling, surveys, focus groups, mall intercepts, sampling, research panes, etc, I’ll probably be open to connecting with you.
Why?
Well, I’m not a sales or business development person so you’ll never see a pitch from me, disguised or otherwise. I don’t do sales, I won’t do sales, I’ll never do sales. But I have numerous reasons for connecting with so many people:
- Conference speakers: On occasion, I am asked to recruit and chair tracks of speakers at conferences. Having built a broad set of connections over the years, I can quickly find and invite people meeting the expertise requirements without resorting to a tried and true list of the same people I talk to everyday. And, I can even invite people based on geography as I’m careful to grow connections around the world.
- Webinar guests: You never know when someone is going to ask you to recommend an expert on a topic, or when you yourself would like an expert to join you during a webinar. Make those connections early, and you won’t waste time waiting for people to notice and approve a LinkedIn invitation.
- Article authors: Want an expert to contribute their opinions to a blog or article? You guessed it. Building up connections over the years means that I can quickly reach out to experts in many areas to see if they’d like to contribute their knowledge in a magazine or journal article.
- Job seekers: I love being connected to so many people because it allows me to be aware of job notices. I see many and share many, and hopefully this helps unemployed people find a new job just a bit more quickly. Plus, when someone comes to me personally, sometimes I can direct them to a job posting I saw just that day. (On a related note, pay your interns!)
- To put a face to a name: I like to get know people I plan to meet before I actually meet them. And, I often open a person’s LinkedIn profile when I talk to them on the phone. I like to see the face of the person and, sometimes, it helps to have a quick outline of who they are and what they do to help focus conversations. This has helped me many times over the years when I’ve participated in global standards committees where participants live on different continents.
- To be in the know: I wish I knew everything about my industry and the future of my industry but I don’t. I’ve not yet grown my psychic abilities sufficiently. Following people who live in hundreds of cities around the world means that I get to understand opinions that I would never, ever otherwise have the chance to consider. I see stories about augmented reality being used for medical training, I learn new theories about marketing, and I am amazed on a daily basis at the work happening all around me. LinkedIn connections are fabulous teachers.
The next time you see a link request from someone you don’t know. Consider whether any of these reasons would make it a worthwhile connection. It might not work for you but it certainly works for me.
How many women do you follow on Twitter? #MRX #NewMR
One of the best ways to identify lots of diverse people to speak at conferences is to follow lots of diverse people on social media. But do we?
With that question in mind, I turned to https://www.proporti.onl/, a website that says…
“Estimate the gender distribution of your followers and those you follow, based on their profile descriptions or first names. Many tech leaders follow mostly men, but I want to follow a diverse group of people. Twitter Analytics doesn’t tell me the gender distribution of those I follow, and it doesn’t try to identify gender-nonbinary people. So I built this tool for myself and put it on GitHub. It’s inaccurate and it undercounts nonbinary folk, but it’s better than making no effort at all. I want you to be able to do this, too. Estimate the distribution of those you follow and see if there’s room to improve!”
I’m cool with that so I turned to this tweet by Antonio Santos as a good place to start within the market research industry. I entered each one of these accounts (excluding @MRXblogs which is a bot that follows no one but me), in order to see how we’re doing.
On average, about 36% of the people these market research influencers follow are women.
Sadly, only 3 people follow roughly equal numbers of men and women, and only 2 people follow more women than men (you can guess who!). I’m one of them, but that’s only because I actively follow women and I’ve been using proporti.onl to monitor my status. Unfortunately, for about 43% of us, one third or fewer of the people we follow are women. The curve is far from expected and could use a lot of improvement.
Fortunately, it’s easy to change that proportion. Lots of people have created lists of women on Twitter who specialize in different areas including marketing research, data science, analytics, STEM, and more. I keep a nice selection of those lists on my twitter account right here. However, here are some of my favourite lists.
- Women in Data Science: I love this list. Search through the 1200 members and you’ll find tons of women who specialize in data visualization, statistics, neuroscience, RStats, business intelligence, artificial intelligence, and more.
- Women Game Developers: 100 women who know AI, storytelling, games, user experience, digital marketing, customer relationship management.
- BioInfo Women: 600 women who know about EEGs, fMRIs, neuroscience, computer science.
- STEM women: 500 women who know data, engineering, cybersecurity.
- Women in VR: So, um, these 150 experts know VR.
Now it’s your turn. Go check how many women you follow on Twitter, and then head on over to these lists to make some additions! Expand your world!
#MRIA2017 Opening Keynote: The Age of Disruption by Scott Stratten, Expert in Un-Marketing and NOOOOOO [Excellent!]
Live note-taking at the #MRIA2017 conference in Toronto. Any errors or bad jokes are my own.
Scott Stratten on twitter
- [100% hipster takes the stage including jeans, sloppy shirt, tattoos, beard, and man bun]
- He is known as the creator of the NOOOOOO button which gets millions of users and views with an average 27 second view. The site does pretty much nothing but say NOOOOOOO. It is the number one site on google for any version of the word ‘no’ that contains more than one o,
- Many people feel guilted, stupid, slow about being brought into the social media, digital world. Huge pressure to stay up to date with every channel but it’s impossible.
- You do NOT have to use every platform. If you don’t like it, don’t use it even if you want to feel cool and hip.
- When we say the word millenial, we mean people younger than us and we don’t like you. [yeah, i have to agree. We’ve built a wall there.]. This happens with every generation. Every newest generation is the worst generation.
We’ve created a bias of ageism that is allowed. But it’s not a good thing. We use it in hiring. We assume young people don’t know. We assume older people aren’t tech savvy. Our industry depends on this. We see younger people as a threat.- We hear things like millenials hate meetings and love to travel. Well, who doesn’t? This is just a bias of interpretation. We need to give comparative numbers. Millenials are more civial minded, cause minded, want to work for non-profits.
- The shift is not an age shift. EVERYONE is making communication changes so we need to figure out what customers want to do. Don’t say old people don’t text because they do, they just do it differently. Your customer should decide what channel they want to use. If someone emails you, then email them back instead of demanding a phone call.
- People like the written record of text, DM/PMs, emails.
- Know the speed of response expected by each method and respect those.
- Brands hop onto trends, often the surface of the trend. Put quotes on pictures, use influencers, newsjacking. But you must do it right. You CAN’T capitalize on death, terror, even if it’s ‘just a joke.’ Offer condolences, help not jokes. Consumers have the power to react, to choose where they open their wallet.
- Viral isn’t about a million views. It’s about 100 views with the exact right audience. Newsjack with originality.
- Ethics are not a renewable resource. What is the first thing that comes to mind when people think about your brand? Your horrid, distasteful ad?
- The problem with live video – most people are not filmable, don’t want to be on video, they’re modest or humble. Most people aren’t that interesting, particularly when it comes to streaming live.
- Contextual content – does the content match the sharing method – concerts, sports, backstage at awards ceremonies. Most other things do not. Interviews with your VP – NO! We want to do it to look hip because we can. But should we? Does it help your brand?
- Branding is no long real time. It’s NOW time. A response in 3 minutes vs 3 hours can make all the difference. What if an airline responded to your complaint 3 days later – you’d be even angrier. Authentic and transparent are important but speed is paramount. Great responses are disarming because most other responses are terrible.
- When people complain, they want validation and to be heard. They want the attention that they weren’t getting otherwise. At least recognize the issue immediately.
- Vanity metrics make you feel great and amount to nothing, Metrics must move the needle for your client.
- Don’t write books to sell them, write books to share knowledge.
- [Scott is a very entertaining speaker. Lots of fun stories. Look for his Unpodcast with Alison Kramer]
Like that? Read these!
Harnessing text for human insights #IIeX
Live note-taking at #IIeX in Atlanta. Any errors or bad jokes are my own.
Chaired by Seth Grimes
Automated text coding: humans and machines learning together by Stu Shulman
- It is a 2500 year old problem, Plato argued it would be frustrating and it still is.
- Coders are expensive, it’s difficult at scale, some models are easier to validation than others, don’t replace humans, no one right way to do it, validation of humans and machines is essential
- Want to efficiently code, annotate coding with shared memoirs, manage coding permissions, have unlimited collaborators, easily measure inter-rather reliability, adjudicate validity decisions
- Wanted to take the mouse out of the process, so items load efficiently for coding
- Computer science and HSF influence measure everything
- Measure how fast each annotator works, measure interacter reliability, reliability can change drastically by topic
- Adjudication – sometimes it’s clear when an error has been made, allows you to create a gold standard training set, and give feedback to coders; can identify which coders are weak at even the simplest task, there is human aptitude and not everyone has it, there is a distribution of competencies
- 25% of codes are wrong so you need to train machines to trust the people who do a better job at coding
- Pillars of text analytics – search, filtering, deduplication and clustering and works well with surveys as well, human coding or labelling or tagging which is where most of their work goes, machine learning – this gives a high quality training set
- If humans can’t do the labelling, then the machines can’t either
- Always good to keep humans in the loop
- Word sense dis ambiguities – relevant – is bridge a game or a road, it smoking a cigarette or being awesome
Automated classification interesting, at scale and depth by Ian McCarty
- Active data collection is specific and granular, as well as standardized; but it’s slow and difficult to scale, there is uncertainty, may be observer bias via social desirability, demand characteristics, Hawthorne effect [EVERY method has strength and weaknesses]
- Declared vs demonstrated interests – you can give 5 stars to a great movie and then watch Paul Blart Mall Cop 5 times a 6 months [Paul Blart is a great movie! Loved it 🙂 ]
- They replicate the experience of a specific URL to generate more specific data
- Closed network use case – examined search queries from members to recruit them into studies, segmentation was manual and company needed to automate and scale; lowered per person costs and increased accuracy, found more panelists in more specific clusters, normalized surveys if declared behaviors conflicted with demonstrated behaviors
- Open network use case: home improvement brand needed a modern shared meaning with customers, wanted to automate a manual process; distinguished brand follower end compared to competitive followers, identified where brand values and consumer values aligned, delivered map for future content creation and path to audience connection
Text analytics or social media insights by Michalis Michael
- Next gen research is here now, listening, asking questions, tracking behavior, insights experts
- Revenues don’t reflect expectations, yet.
- We’re not doing a great job of integrating insights yet, social media listening analytics is not completely integrated in our industry yet
- Homonyms are major noise, eliminating them needs humans and machines
- Machine learning is language agnostic, create a taxonomy with it, a dictionary of the product category using the words that people use in social media not marketing words
- It is possible to have 80% agreement with text analytics and the human [I believe this when the language is reasonably simple and known]
- Becks means beer and David beckham but you need training algorithms to do this, Beck Hanson is a singer, you need hundreds of clarifications to identify the exact Becks that is beer
- Beer is related to appearance and occasions, break down occasions into in home or out of home, then at a BBQ or club
- What do you say about a beer when they do a commercial that has nothing to do with the beer
- English has s a lot of sarcasm, more than a lot of other languages [yeah right, sure, I believe you]
- Break down sentiment into emotions – anger, desire, disgust, hate, joy, love, sadness – can benchmark brands in these categories as well
- Can benchmark NPS with social media
- Brand tracking questions can be matched to topics in a social media taxonomy, and there can be even more in the social media version than the survey version
Social media and qualitative – Respect the word! #MRIA16 #NewMR
Ask first, listen later by Lori Reiser
- Traditional research often starts with the business, product iterations, product marketing, product fine tuning
- We should put people first so you hear about unmet needs and pain points
- Case studies
- Health insurance firm – young adults getting their first insurance plan, and new retirees moving away from employer benefits; had predefined assumptions but those were based on the six people in the room, fears of these people were financial and health and being bored not really insurance, how did they define good health and how could that be protected, did focus groups and bulletin boards, retirees weren’t worried about getting sick but rather that their parents would get sick, younger people were more worried about stress as their health issue
- Meat company – what did consumers need in terms of communication needs, saved qualitative for the end of the research, started with a survey of staff members and inspection organizations, realized they needed to formalize their email address to clients so that it didn’t come from Annie Pettit but rather from the company, realized that Mennonite members didn’t have email addresses [pay attention to that anyone who says they do probability sampling via RDD]
- Pharmacist – surveyed pharmacists as well as focus groups and the focus groups were after the fact, what does patient centered care mean, many barriers in terms of how pharmacists communicate with people given what doctors and other people want them to be able to say
- You can’t ask broad questions unless you go qualitative, open ends on a survey arne’t going to cut it; give your users permission to participat in the idea making, find the trendsetters and listen to them, use skilled moderation
Classified: Research that integrates to innovate by Mark Wood
- Technology has given us an identify crisis, people challenge are traditional beliefs, anyone can do DIY research, other people are jumping into our sandbox with new types of data
- Tactics to get our mojo back
- Understand consumer dynamics in a more connected world
- Leverage expertise in a data curation to improve SML capabilities, Think both/and between traditional survey and SM, Help companies navigate path to purchase, use data to help action
- Have to work with clients better and bring in other pieces of data so we can inform them better
- Bringing MR expertise into social media listening
- We need to take SM data to the full extent just not report facts and figures
- Must get access to this data first and then we can sample and structure and clean it
- SM provides an authentic voice of the consumer, has rich detail; surveys enhance social media structure to categorize themes and related back to real initiatives
- Use social and survey together to inform each other
- Need to identify lots of buzz with lots of impact, not just lots of buzz
- Use buzz impact matrix to understand which conversations have high buzz, high impact, and then dive deeper into those issues
- Identify all the touch points that need to be assessed, identify which have the highest reach, but there are big differences in claimed versus reality
- Need to move from measurement to action [the problem of the century!]
- Opportunities are greater than ever for MR to have an impact
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
- What questions do you need to answer, what decisions will betaken because of it
- What do you know already, existing research, behavioural
- What social behaviora are you looking for, what data sources, do you need aggregate data or granular level
- What is the relevant timescale, ad hoc or continuous, how do you know yyou’re finished
- 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]
Keynote: Why Social Media “Likes” Say More Than You Might Think by Dr. Jennifer Golbeck, Human-Computer Interaction Lab, University of Maryland #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- how much do two strangers online trust each other? you need to know about the people themselves first.
- social media data can give you accurate data, even when used in a simple way
- can predict introversion, political leaning, procrastination, personal health habits from your posts
- likes on facebook are always public, can use this to predict many things
- top four likes most indicative of high intelligence include science, thunderstorms, colbert report, and liking the page for curly fries. For low intelligence, the like was for the page “i love being a mom” But these don’t truly relate to intelligence.
- homopholy – we are friends with people who are like us, our traits are more common among friends than among random people.
you just need one smart person to like a page and then it spreads like a virus to all your friends- we’re really good at predicting sexual orientation, even in places where being gay could get you executed
- how does a store like Target figure out you’re pregnant, not from pregnancy tests, – an extra bottle of vitamins, a bigger purse, brightly coloured rugs together are a statistical connection
- how can you know what these statistical combinations are?
- can your social media network figure out which friend is your spouse? you know which friends are friends with each other and nothing else. Often it is the person with the most friends in common. But look at social dispersion instead, eg., your sports friends, your school friends, your family friends, your work friends. Dispersion is who is connected to the most of your groups – that is the spouse about 75% of the time. the other 25% is a good indicator that youre going to break up your relationship
- can predict postpartum depression from social media content.
- how easy is it to get data?
- takethislollipop.com – makes a video out of your social media accounts, try it if you think all your settings are private
- we leak a lot of data, we don’t realize how much data apps are pulling
- it’s not all bad – apps recommend products you might like, google uses it to make the web easier to interact with
- we don’t have control over it – don’t know who has data or what they’re doing with it
- even though the algorithms are smart, we still don’t buy whatever the algorithm says we might like. but they tell us things we would never think about but we actually want
- treat your business algorithms as useful but realize some are wrong or shouldn’t be acted on, it’s one more piece of advice
- [jen needs no slides, she changes every 5 or 10 minutes just for the heck of it, impressive]
- how do you figure out which people like the targeting or don’t like the targeting
- you don’t want to be the creepy facebook stalker guy, it needs to be handled with care
Related articles
Digital and Social Media impact on Research with Twitter, Google, Facebook, Rogers #MRIA15 #MRX
Live blogged from the 2015 MRIA National Conference in Toronto. Any errors or bad jokes are my own.
Panel – Digital and Social Media impact on Research
Twitter/Google/Facebook/Rogers – Sponsored by Ipsos
Gayle Lunn, Ipsos UU
Industrial revolution, mass production/consumption which changed the quality of people’s lives, digital now lets us to do things differently and impacts the way we think- Luke Stringer from Twitter – startling change joining Twitter – speed of things changing is very fast, challenges the research method. Product is very different today from what it will be in one week or one month. Culture is very collaborative, work spaces are collaborative, completely open concept [booooooooooooooo!] There are tables around so people can meet and talk. Culture of failure is embraced, test and fail fast. They test every minute change to the product.
Alexandra Cohn from Google – Came from ipsos, overwhelming amount of data and knowledge. Like drinking from a firehouse. Acronyms for everything. What do you need to know and what can you ignore. Speed is overwhelming. Completely different mentally, not asking, the data is behavioural. Fully transparent and collaborative culture, always available to anyone. No one keeps data to themselves.- When you join twitter, you give your name and email. They don’t know who you are as an individual. Why do you use twitter – they don’t know that. You can apply traditional techniques to understand that. You have to ask questions.
- Not everything can be done in no time. There’s a lot of pressure to do research fast, get answers cheaply.
- Will google surveys replace traditional surveys?
Collecting too much data is a bad things, especially from consumers.- Despite all the internal knowledge, they still need to pair internal data collection with elicited data. It’s enrichment of data.
- Google surveys is only ten questions by design. Partnering with the full service companies is where they get their strength because google isn’t researchers. They provide the data, they are the platform. Still need researchers to interpret the data, researchers know how to ask the good questions. Not just anyone can ask a question.
- Twitter is a mobile first company. Rich media is limited, on purpose. There is always a place for longer form surveys, rightly or wrongly.
- Data scientist is a title that has to be earned.
- A lot of collaboration is behind the scenes, not public, and you can’t talk about it. But there is a lot of collaboration among clients. Collaboration is driven from the outside. Clients can’t operate in silos anymore, they need data from a wide range of people.
- Digital is held to a higher standard than other media. People expect you can link data but you can’t always do so. You can’t always use JUST data to complete a model. Big expectations that models will drive income.
- Right now we pay for view but maybe we will eventually pay only if someone follows or only if someone makes a purchase – pay for desired behaviour.
- Like to append their data to market data to see true ROI. Research explains why one campaign worked and another did not. Which specific type of content drove the result.
- Just “knowing” something works is not enough. They want and can get precise numbers.
- What is the value of a Twitter like versus a Facebook like? Need to be able to measure this. Models are wonderful but they don’t matter. Metrics matter.
- TV ads existed for a long time and we had ways of measuring the outcome, same with print and radio. Twitter has to figure it out for themselves instantly, not over decades.
- Industry is evolving but not fast enough. Privacy laws are very challenging. Internal struggles between product development and engineers, all have their own internal objectives.
- Rely on industry to tell them what the cool things are, where the industry is going. Partnered with academics to understand impact of being exposed to twitter versus other media in terms of how brains are reacting. Have and are exploring neuroscience to understand their product.
- Investing in machine learning and artificial intelligence. If you want to learn the direction of the company, look at who is on their board.
- How do i read irony in a google search query? 2/3 of top AI people in the world work for google.
- How can we collaborate more effectively. External partners come with ideas as opposed to we just want to work with you.
- It doesn’t have to be unique data. We just need to properly marry the data.
- It’s okay to fail in this safe space, with appropriate checks and balances
- Sometimes, retweets and shares are the right measure for you. Other times, ROI is the right measure.
- How do you attribute a click when someone saw six ads along the way and then finally clicked on one.
- Collaboration can lead to indecision because no ones in charge. Must hold everyone accountable for specific objectives. Make it directly related to reviews. Course correction is ok. Autonomy is important.
- Collaboration is not leading my consensus. One person must be responsible for the outcome.
https://twitter.com/ramblingasian/status/603208291385245696
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Interesting Infographic: Smile! Your selfie is an ad
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