Social Media Monitoring needs Motifs and Relationships

Been meaning to post all week though I am so busy tying up my initial manuscript for Social Media Analytics there is little left for me to write blog posts with (all of my angst and insights are going into the chapters of the book, and that would be OK but I had an insight building up over the last 6 days I need to share; and after all, I am an artist,  self expression is a key part of what makes me want to write, draw and paint).   Actually, what I’m trying to describe is a thought process for which there isn’t an exact analogy – by writing it down I’m trying to visualize and communicate it at the same time.

Here goes.

Tired of being part of lousy analytics reporting, Social Media Monitoring and otherwise, I see it too often and also feel locked into patterns and methodologies that do not work well.   I want to replace what I take to be a bad approach with one that is better, more personal, but workable, at least for me (and maybe for you).  I’m starting with a story:

The Empire State Building

empire state building

When I left the subway several days ago,  immediately looked up and saw the Empire State Building and knew where I was,  in New York (obviously).   But it’s quite possible, that without the context of seeing a familiar site, something so much a part of New York City (like the Statue of Liberty or the Empire State Building) I could have been in almost any large city in the United States, Canada or Europe.

I started thinking about that on the way up to Providence, RI, where I’m editing and finishing up my manuscript this week.

It dawned on me  Social Media Analytics, Monitoring and Insights (vs. Reporting)  need the same things that I, visually, need, in order to know where I am located, namely a reference point and the context of  the relationships between what surrounds a reference point and the reference point, itself (thinking visually now).

Kinda hard to get that sort of thing in Analytics … how do I translate a model of visual thinking into something so different, namely, a bunch of platforms that crawl the web using boolean equations and attempt to represent it in a bunch of pie charts, line graphs and word clouds along with a pretty standard “news ticker”.   I think it’s possible, indulge me a little bit more here.

I don’t think it’s enough to listen for dominant conversions, communities, channels, influencers (which might be able to be automated at some point in the future, anyway, should the profiles and searches were set up well enough and platforms become more intelligent than they are today) because they is missing two important things, reference points and  context.

Going back to visual, somehow, I know the Empire State Building below isn’t in New York City.

A lot of the same elements are in both pictures  but the relationships, context, are all off in the second image, almost as if it is a dream of New York, taken from someone’s mind, and thrown all together (almost like a listening report – ha!).   Not sure how much of New York City anyone learns from a diorama of it in Las Vegas (but there sure is a lot of screaming going on, at least in the Vegas version of NYC).

Going back towards Listening Platforms, the kind of stuff I’m writing about in my book, reminds me of when a patient goes to see a doctor, there is usually some issue to discuss (illness, checkup, drugs, etc) and the first thing a doctor does is listen to the patient along with taking some blood tests (at least, if they are a good physician).

Once the listening and tests are compared, along with the doctor’s own knowledge of health and disease, along with the patient (history) and what they see and hear, they can make a diagnosis and provide insight (to the patient). It’s the relationship of all the information, verbal, visual, tests and inner knowledge that are synthesized together to form a diagnosis.

If the “clients” of a set of deliverables is thought of as the “patient(s)”  what would be the reference points and context – what does that translate into for a Social Media listening report?

The nearest correlation I can come up with is something to do with the brand, of what is being monitored.  Say, it’s a over the counter drug, a movie, or an action hero, a situation, a disease or even a food item, there is some landmark, something that is recognizable, a reference point, beyond the name or keyword phrases.

Reportblogmodel

Nearest thing I’ve seen to my mental imagery is not anything I got out of a listening system, rather it came from Gary Angel’s blog in a post that is 3 years old on modeling traffic.  The chart above shows a synthesis of 4 other charts presented earlier in the post, but it wasn’t just the relationships that mattered, it was the application of knowledge through a new chart Gary created that embodied in an analytic model.   Well, read the post including the last few lines…

To get the same intelligence from any non-model based report set would take big chunk of work and a fair amount of knowledge about web analytics. The two things that a good report set is supposed to make unnecessary!

The more I work on reporting, the more I think that the distinction between analysis and reporting is meaningless. Because unless you embody good analysis in your reporting, you’ll never deliver a good report set.

By “embody” analysis in your reporting ….. the diagram above says it all – that diagram is far superior to the four that preceded it because it embodied the relationships of that information.

I have yet to see any Social Media Reporting, outside Semphonic’s own dashboards (see embedded presentation below (from Monitoring Social Media San Francisco last October #msm10) that does anything close to what the modeling chart does/did.

At least Gary Angel’s approach gets me a lot closer to the where the real work of Social Media Analytics should be.

- Context:  look at Slide 9 of the presentation (above)

In order to get context for a listening report we need to have  business objectives connected to the listening report in mind before us.

- Point of Reference(s): look at Slide 16 of the presentation, it would be, in this case, a specific website.

The problem is, a lot of listening reports aren’t about a specific website or even a specific set of websites, rather, they are about a brand and how it the online audience interacts with it.

Again, I haven’t figured out the entire parallels between reference points, context and listening though the information I pulled together so far gets part of the way there.   One more thing might be that the reference point (what I call a “motif” thought it may be the wrong term) needs to be interesting.

Look at this picture immediately below – there’s nothing interesting to look at, nothing to draw attention to it, nothing to catch the eye – its just a boring landscape (at least to me – since “boring” is a subjective term – what is boring to me might be interesting to someone else … but still, it’s a stretch to call this landscape “interesting”).

Boring landscape

On the other hand, the picture below is much more interesting because the eye has something to look at.

Semiframe

If my analogies hold true, we need something interesting to listen for.  I have maintained we need to know “what” to listen for and we also need, according to Gary Angel, a good deal of classification of data in order to make “interesting” relationships that provide some real insight and tell a story.

And here’s a little hint from my book on Social Media Analytics – just a glimpse of what you’ll see next summer

The classifications above are meant to be additional and should  be mixed and superimposed with the classifications below, which are the basic ones you can cull out of Radian6, but  whichare, alone, not sufficient to tell a story (btw, you will probably want to muck around, try some stuff out while creating a listening report before you decide what “the story” your trying to tell, “is”).

I asked Gary Angel to produce a chart of “keyword groupings” – the kind of groupings you would set up in a “topic profile” in a platform such as Radian6, with specific industries – here’s the first two (see chart with “financial services” of several you’ll see in chapter 10, that is, when you read chapter 10).


Like anything else, you can have the colors on a palette, but it’s the artist who paints a picture by taking the colors and making it do something, convey some idea or feeling.

The last thing I want to talk about is Engagement – again, I am thinking this through.

- someone sitting in the backseat of a car may be driven past past a route several times but generally won’t remember how to get there, though the route will seem familar.

- someone who has to drive a route will generally learn to remember it, once they drive it.

What’s different?  Same route – different levels of involvement – what I decided to call “engagement”.

I think engagement, for the purposes of analytics measurement, is the tangible application of effort to make a decision (where there is something to make a decision on).  It may be difficult to measure “engagement”, but not impossible though “time spent on page” alone will not get you anywhere, nor will “specific link clicked on” or “specific PDF file downloaded” – clearly, as in Social Media Analytics, interesting data and insight comes with Synthesis, the ability to combine several points of data and embody them in a model, as Gary Angel did when he modeled traffic to a website.

The very same modeling could have been done with “likes”, “votes”, “shares”, “tweets”, “retweets” – the data set is different but the concept is very similar and I hope Gary ends up doing something like that chart on modeling, but with Social Data instead of or in addition to Web Analytics data.

And to end this post it should be obvious by now why this kind of analytics is literally impossible to imagine in just about any marketing/PR/MarCom firm even though what it delivers is actually what clients want and need in the first place - true insight … it takes a bit more time to do than firms are willing to commit to, or let the analysts devote,  and the vocabulary of PR (based on Spin) is antagonistic to analytics which essential nature is a search for the  truth of a situation, often by triangulation.

Time for bed, at least I got these ideas out … hope they made some sense.  If not, at least it  helped me to understand my own ideas a little better – but I’d be happy to hear some feedback from readers on this post.

6 replies
  1. Michelle C says:

    Interesting article, Marshall. I’m glad that you pointed this out because it’s something I’ve wrestled with lately, as well. When you look for articles about social media monitoring online there seem to be two major camps : articles from online reputation agencies that talk about creating relationships, raising brand awareness, “engagement ratios”, etc. and another set of articles that focus on the metrics of the dashboards and the analytics behind them.
    Monitoring social media reports should have both types of content and provide multiples ways to look at the data : both as data, and also as a story that pulls out the main focus points for whomever is looking at the report. If there are multiple departments that are going to be working with the same set of data, their reports are naturally going to be different because they are not looking for the same thing.
    Gartner also predicts that social analytics is reaching its “peak of inflated expectations” according to the 2011 Hype Cycle for Social Media (http://on.fb.me/edjo6U), so I think we can all expect to see failed expectations as marketers and brands realize what can and cannot be measured and what is and isn’t important for their use of social media.

    A pleasure, as always, Marshall :)

    Michelle @Synthesio

  2. 40deuce says:

    Interesting thoughts as usual, Marshall.
    Coming from a PR background myself, I more than understand the need to tell compelling stories to make people understand your point. I think that monitoring software companies, such as mine, recognize this need and are working on ways to make it more easy and viable for people to tell these stories. I think tools you’ll find in our Sysomos software such as our buzzgraph and key conversations tools are the beginning of this. Yes, they still use boolean search to help find mentions of your brand, but from there we link them to key words being used in conjunction with the search or key sentences that are found around the search. While they’re not fully to the level you explained above, getting some of this information like prevalent sentences and words used in conjunction with our search terms does help to show more of a story of what people are saying than just sifting through all the mentions of your brand we pulled in.
    I think you’re going to see a lot more tools like this coming to light in the next year as people move from just wanting to know what is being said to wanting to be able to make actionable objectives based around what people have said. Seeing the story helps to show direction towards what these actionable items may be.

    Cheers,
    Sheldon, community manager for Sysomos

  3. Kathie says:

    Loved the post and the thoughts. I too have been struggling with analytics as I find most of what is available is not getting at what I am after…brand recognition, brand reputation, and relationships. So context and engagement do mean a lot when thinking of these things and trying to measure them. I hope to hear more on this!

  4. Rina Wallace says:

    I was talking to my sister about this earlier today and we tried to distill it down to the main consumer segments to look for and I found this article which really opened my eyes to who I was marketing towards.

    Here are the segments defined:

    1) Strivers: Place more emphasis on material and professional goals.
    2) Devouts: Tradition & duty are very important.
    3) Altruists: Interested in social issues & social welfare.
    4) Intimates: Value close personal & family relationships.
    5) Fun Seekers: High consumption of restaurants, bars, & movies.
    6) Creatives: Strong interest in education, knowledge, & technology.

    See the article here http://outtoown.com/2010/11/02/strategic-marketing-segmentation-the-6-consumer-segments/

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