The Rise and Evolution of Social Media Research
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Just a few years ago, social media research was hailed as the panacea of all marketing research. The ridiculous quantities of brand opinions and opinionators available in social media would mean that focus groups would die, surveys would die, and all research questions would have instant answers. Fast forward to today and surveys continue to thrive. Learn why social media research didn’t hold up to expectations and why it’s finally breaking through. Presented at #IIEXap14 #IIEX
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The Rise and Evolution of Social Media Research
- 1. The RISE and FALL, and RISE Again of Social Media Research Annie Pettit VP Research Standards Please tweet! #IIeX @LoveStats
- 2. 2 ©2014 Please tweet! #IIeX @LoveStats 0 23 46 69 92 Jan-08 May-08 Sep-08 Jan-09 May-09 Sep-09 Jan-10 May-10 Sep-10 Jan-11 May-11 Sep-11 Jan-12 May-12 Sep-12 Jan-13 May-13 Sep-13 Jan-14 May-14 Sep-14 Social Media Monitoring
- 3. 3 ©2014 Please tweet! #IIeX @LoveStats 0 6 12 18 24 Jan-08 May-08 Sep-08 Jan-09 May-09 Sep-09 Jan-10 May-10 Sep-10 Jan-11 May-11 Sep-11 Jan-12 May-12 Sep-12 Jan-13 May-13 Sep-13 Jan-14 May-14 Sep-14 Social Media Tracking
- 4. Where did the fall come from? 4 ©2014 Please tweet! #IIeX @LoveStats
- 5. looking isn’t learning 5 ©2014 Please tweet! #IIeX @LoveStats
- 6. 6 ©2014 Please tweet! #IIeX @LoveStats 0 5 10 15 20 Jan-08 May-08 Sep-08 Jan-09 May-09 Sep-09 Jan-10 May-10 Sep-10 Jan-11 May-11 Sep-11 Jan-12 May-12 Sep-12 Jan-13 May-13 Sep-13 Jan-14 May-14 Sep-14 Social Media Listening
- 7. 7 ©2014 Please tweet! #IIeX @LoveStats 0 27 54 81 108 Jan-08 May-08 Sep-08 Jan-09 May-09 Sep-09 Jan-10 May-10 Sep-10 Jan-11 May-11 Sep-11 Jan-12 May-12 Sep-12 Jan-13 May-13 Sep-13 Jan-14 May-14 Sep-14 Social Media Research
- 8. 8 ©2014 Please tweet! #IIeX @LoveStats Rolling 4 months 0 22 44 66 88 110 Jan-08 Apr-08 Jul-08 Oct-08 Jan-09 Apr-09 Jul-09 Oct-09 Jan-10 Apr-10 Jul-10 Oct-10 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Oct-13 Jan-14 Apr-14 Jul-14 Oct-14 SM Monitor SM Listen SM Research SM Track
- 9. Research 9 ©2014 Please tweet! #IIeX @LoveStats
- 10. Track 10 ©2014 Please tweet! #IIeX @LoveStats Monitor Listen Research Technology Trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Gartner Hype Cycle T I M E V I S I B I L I T Y
- 11. Gartner Hype Cycle We keep getting mentioned! 40% like the blue one! 11 ©2014 Please tweet! #IIeX @LoveStats We were mentioned! They mentioned the blue one! T I M E V I S I B I L I T Y
- 12. But WHY?! 12 ©2014 Please tweet! #IIeX @LoveStats
- 13. More Need 40 30 20 10 0 Public Opinion Survey Response Rates (PEW) 13 ©2014 Please tweet! #IIeX @LoveStats -10 1997 2000 2003 2006 2009 2012 2015 2018 http://www.people-press.org/2012/05/15/assessing-the-representativeness-of-public-opinion-surveys/
- 14. More Comfort http://www.pewinternet.org/2014/04/03/attitudes-impacts-and-barriers-to-adoption/ 14 ©2014 Please tweet! #IIeX @LoveStats
- 15. Social networking site use over time, by age group % of internet users in each age group who use social networking sites 50-64 18-29 2006 2007 2008 2009 2010 2011 2012 2013 http://www.pewinternet.org/2014/04/03/attitudes-impacts-and-barriers-to-adoption/ 15 ©2014 Please tweet! #IIeX @LoveStats 100% 80 60 40 20 65+ 30-49 90 78 65 46 A Lot More Comfort
- 16. More Quality Increase in use of content analysis Decrease in snake oil Increase in data quality 16 ©2014 Please tweet! #IIeX @LoveStats
- 17. More Education 17 ©2014 Please tweet! #IIeX @LoveStats
- 18. More Standards • ESOMAR Guidelines on Social Media Research • CASRO Social Media Research Guidelines • MRA/IMRO Guide to the top 16 Social Media Research Questions • MRS Online Data Collection and Privacy Discussion Paper • www.social-media-measurement-framework. org 18 ©2014 Please tweet! #IIeX @LoveStats
- 19. 19 ©2014 Please tweet! #IIeX @LoveStats More Big Research 0 105 210 315 420 Jan-08 May-08 Sep-08 Jan-09 May-09 Sep-09 Jan-10 May-10 Sep-10 Jan-11 May-11 Sep-11 Jan-12 May-12 Sep-12 Jan-13 May-13 Sep-13 Jan-14 May-14 Sep-14 SM Research big data data analytics
- 20. 20 ©2014 Please tweet! #IIeX @LoveStats
- 21. Thank You Annie Pettit annie@peanutlabs.com twitter.com/LoveStats ca.linkedin.com/in/AnniePettit/ web.peanutlabs.com/blog-timeline/ Please tweet! #IIeX @LoveStats 21
Hinweis der Redaktion
- Hello Sydney! Some of you may know that social media research is near and dear to my heart. It’s something I’ve been learning about and teaching for more than 5 years. Like anything new to market, it quickly became buzzworthy which means that google trends has some interesting data about its evolution. So, let me take you through a few trend charts to show how social media research has grown and evolved over the years.
- First, let’s take a look at how people have been searching in google for social media monitoring. There was huge growth through 2009 and 2010 when people first heard the term. When people heard that you could find out how many people are talking about your brand almost instantly, it was a dream come true. Now instead of waiting for months or weeks, you could find out in days or hours. But in early 2011, interest around social media monitoring hit its peak. In fact, its been declining in search frequencies ever since then. People are searching for social media monitoring less and less often now. What’s really interesting however.
- Here we’re looking at how often people search for social media tracking on google. It too saw a lot of growth in the latter part of 2009 and 2010. You’ll notice this time that it hasn’t necessarily declined. It’s just kind of stagnated. It’s no longer growing. So people are still thinking about social media tracking but it’s not really going anywhere. Why is that? Why is monitoring falling away and why is tracking not growing?
- First of all, many early entrants vastly over promised the quality of their data. Yes, they could tell you how many times people were searching for Target or Gap or Apple but they weren’t factoring in that target practice and apple pie weren’t what people were interested in. There was so much spam and irrelevant records in the datasets that it was nearly impossible to separate fact from fiction. People were really excited to try it and then were very quickly disappointed when they saw how bad the data was. Were? Was?
- What people realized is that seeing data and looking at data doesn’t necessarily save time or help you learn anything. A big pile of data, whether it’s social media data or focus group data or survey data, is still just a big pile of data. You can’t learn anything useful from a big pile of data. Let’s look at another phrase now.
- Here we have the growth rate for searches of the term social media listening. Unlike the previous two terms we’ve looked at, now we see a very steep upwards curve. This phrase has generated increasingly more interest as a search term over time. It hasn’t stagnated. Yet. It’s still in a growth phase. People have realized that listening to people, not just counting people, is more important and useful. Let’s take a look at one last term.
- The last term I’d like to show you is for social media research. This term also shows growth over time. No stagnation. People continue to search for social media research with greater frequency. You might have noticed that none of these trend charts show any scales. Let’s put all of these terms together on one chart and see what’s really happening.
- This chart is really quite interesting. All of the search trends are posted on the same scale so they’re directly comparable. First take at look at the red line which shows how social media monitoring rose and is now declining. Let’s think about what monitoring really is. it’s like opening a door, peeking inside, and then closing the door. Yup. I saw it. This trend line is telling us that people are less and less interested with taking a peek at the data. Now look at the two bottom lines which show social media listening and social media tracking. These terms aren’t doing particularly well either but they aren’t in decline. So now think about what those two terms mean. They aren’t just peeking or looking at something. They are listening to something. They are keeping track of something. But people have learned that that’s not enough. Finally, let’s look at social media research, the only term here that’s actually showing any continuous growth. We’re all researchers here no matter how you define that term. We all apply rigour to data to better understand consumers and markets. Social media research is the same thing. It’s the application of science to social media data for the purposes of understanding consumers. It’s not just looking at them, it’s not just listening to them, it’s understanding the data to generate insights.
- Social media research continues to grow at the expense of social media monitoring and tracking because the rigour behind it allows you to develop solid hypothesis and generalizations. Scientific research incorporates processes for data quality and sampling and measurements and validity and reliability. These are the things that turn looking at data into being able to use data. If you think about how using social media data has changed over time, a very familiar concept should come to mind.
- The nice thing is that the progression from monitoring to tracking to listening and finally to research maps really nicely onto the Hype Cycle. In the early days, most people were focused on monitoring. Let’s go online and look at what people are saying. People got really excited about this new thing they could do. But they realized that monitoring wasn’t enough. They needed more. So they moved on to tracking. Let’s record some data and see what changes over time. But again, that just wasn’t enough. We’d been stuck at looking and tracking for a few years and that got us pretty much no where. But at the same time people who were working on listening were making more headway. Let’s not just count, let’s count specific things. Now, we’re in a stage where research has finally pulled through. People realize you need to apply science and rigor to data. You can’t just look and listen or your hypotheses and conclusions won’t reflect reality. You need to make sure you’ve chosen the right data to listen to and that you consider the biases associated with that set of data. Treating it scientifically means that you can generate more meaningful hypotheses and insights.
- And don’t tell me your rates aren’t going down. Just because your panel only consists of the most professional responders and you drop people who never answer surveys doesn’t mean response rates are 20%. Response rates for people who agree to continually take surveys from you and who take surveys properly are very likely 20%. But that doesn’t generalize to the population of people who have email addresses.
- Let me take this one step further. What exactly is
- And what does that look like in google trends? We already know this. Interest in big data is going through the roof. But take a look at another interesting tidbit on this chart. While interest in data mining is decreasing, interest in data analytics is increasing. As we just saw, people are becoming less interested in simply mining or looking at data and more interested in analyzing and truly understanding what is happening with the data. People want more than seeing. They want understanding.