Last week I joined the new PeekYou Advisory Board in order to provide strategic and networking help, provide feedback on PeekYou’s products or services and  assist spreading information and insights about the company.  This is the first, but certainly will not the last as others are in the works, Advisory role I have taken in the Social Listening Space.  I also updated my LinkedIn profile to include a reference to PeekYou’s Advisory Board.

It’s also nice that in PeekYou I have found receptive ears and people who understand the value they have and what I can add.

In so far as I have written about PeekYou previously with the StarBucks Case Study, Geo-Location Snapshots, StarBucks Geo-Location Case Study, The UnMarketer -Reverse Lookup Case Study and Initial Review, all of these I will update (when I get around to it) to state I am also an advisory board member (but was not at the time I wrote the posts).

I look forward to helping PeekYou move forward in providing immense value and insight to the public and to business  in 2011 (and 2012).

Heard about Google Ngram Viewer?  Interesting to compare citations of terms in books  (Google Ngram) with web search (Google Insights for Search) and see what we come up with.

While the charts above do not cover past 2008 I noticed Social Media appears to have been written about less in print during the 5 years examined than it was searched upon, online.  Web Analytics, while searches are quite flat, seemed to be getting more content in print.   My sense is these charts appear to confirm that different mediums have different speeds of adoption and warmth/coolness (this goes back to my communications background and has been well documented over the years, though most references of “hot” and “cold” mediums have gotten less attention since the Web and Internet are the ultimate “Hot” medium (at least it seems that way based on the past).

Now to the Web Journal Part of this post and going back to December 1st (these days I’m so busy writing it’s hard to keep up – once my book is done I’ll get back to my regular schedule of posting daily).  My journals give me a chance to curate the content I found most interesting and by writing it down, feel better able to hold on to it, Marshalling it (ha, ha), so to speak!

First, a post from ReadWriteWeb detailing research showing when people comment online it’s usually motivated by “negative” emotions.

“… According to the researchers, “negative emotions are a motivation that incline forum participants to express their opinion (as well as emotion) writing a post. The active users are those characterized with negative emotions and they seem to be the key agents that sustain discussion in the thread. Finally, we have shown that negative emotions accelerate user’s local activity in the thread,” something that doesn’t mean they participate the same way on a global level.

Researchers do admit that this dataset has a strong bias towards negative emotional content. It is, after all, only a study on those posting on a BBC news forum. The rest of the world’s Internet commenters are much more rational and positive, right?”

An interesting caveat is Social Media Monitoring platforms that collect posts and comments and rate them on Sentiment.  We all know the Sentiment Analysis of Listening Platforms is immature but consider that what we listen for might now be a distorted window for what is really going on within your audiences minds and with their emotions.  Then again, DecorMyEyes debacle happened earlier this month and Google is trying to adjust search rankings by monitor negative reviews, but search is a different medium than Forum reviews, hmm.

Personality Analytics is apparently an overlay of information, an additional classification or segmentation that is added to call center calls in some cases but till this month I never considered this might be possible to do – and now it is – see Personality Analytics – The Next Must-Have Feature for Social CRM? for more information.

…. according to Fast Company, the PCM method is showing results. “A banking client saw the attrition rate among customers struggling with the most serious issues drop from 7% to 1%,” according to the magazine.

That shows me, given the right framework and IT infrastructure setup a lot of communications can be leveraged.

Jacob Morgan, one of the smartest people I have read online, had an great post on the gap between Social Media Searches on Indeed.com and the way companies are using Social Media and how they hire people for those positions.

“… Clearly this whole “social media” thing is pretty big if the growth is THAT big and if THAT many job postings online are looking for “social media” help.  It will be interesting to see how this trend continues and shifts over the next year or two.  I’m still not convinced that most of the companies looking for social media are looking at this strategically, I think most organizations are looking at social as a way to sell more stuff, spam more customers, and market to a wider audience.  I also think that too often, social is being associate specifically with a tool or channel such as Twitter and Facebook.”

BillBoard started getting with Social Media finally this month by “adding the Social 50 chart, which ranks the most active artists on the world’s leading social-networking sites”.  Not into this so much myself, it seems like a play at artists with the biggest fan bases.

I just finished my chapter on Influence for THE Social Media Analytics Book I’m authoring for McGraw Hill, but a curious post that Stowe Boyd referenced earlier this month might mean more than all the Klout scores in the world.

Best Connected Individuals Are Not the Most Influential Spreaders in Social Networks

Who are the best spreaders of information in a social network? The answer may surprise you.

“…”In contrast to common belief, the most influential spreaders in a social network do not correspond to the best connected people or to the most central people,”

“By contrast, a less connected person who is strategically placed in the core of the network will have a significant effect that leads to dissemination through a large fraction of the population.”

Of course, most Influencer Analysis is working on sequential rankings using Authority Scores, Peek Sources, PageRank and so on, entirely miss the contextual analysis that makes true influence more apparent – it’s not who you know, as Stowe Boyd likes to say, but “where you know” them.

I happened to come across an old post by Net-Savvy that directly ties into chapter 5 of my Social Media Analytics Book which will be published next spring by McGraw Hill. In Chapter 5 Giles Palmer of Brandwatch gives me a full explanation of his platform and how it differs from others that are based more on data aggregation.    Net-Savvy’s post gives a full list of the Data Aggregation Services where data that is captured off the web can be bought (if you don’t want to crawl it yourself).  Here’s the list.

• 80legs
• Beevolve
• Collecta – for public apps only
• Collective Intellect
• Context Voice (UberVU)
• CyberAlert
• Dow Jones
• Effyis (Boardreader)
• Extractiv
• Gnip
• Kapow
• Moreover
• PostRank
• SocialMention
• Spinn3r
• Superfeedr
• Viralheat
• Yahoo

Front Loading - it’s something that Governments have in common with  MarComs as Paul Krugman eloquently states.  The problem with front loading is the results fall apart once it’s time to deliver on “expectations”.   I’ll say no more.

I liked a post about Ted Ulle of Converseon (I’m a fan of Converseon and they are contributing a Case Study and a few more bits of information for my book).

More WebProNews Videos

I suggested much the same thing in my Rainbow Analytics paper with Compete.com a few months ago.

Found a new search tool called Hitsplitter.com that does something I think is unique for a search tool – it works like a Web Analytics data mining application … here, take a look.  It’s intriguing what you can do with this application and it might replace some cumbersome Google searches some people I know have sold themselves into, even though Google only indexes less than 1% of all the data online.

Here’s a cool video of Hitsplitter.com which goes way beyond what I just did with my name.

I also like a post at RWW on The Secrets Behind Blekko’s Search Technology which suggested the way they have set up their infrastructure is superior even, to Google.

Meanwhile, last weekend I wrote about The Future and gave my 2011 Predictions.

Also, Amazon’s Mechanical Turk used increasingly for spam was a wake up call.

Meanwhile the web was in uproar with the threat of Delicious being closed down, which now appears to be a non-threat – it will only be sold to someone else – ha!

And my friend Dennis Mortensen new company Visual Revenue just launched though I knew about his new startup since last spring. See  Predicting the future performance of Content – versus a Product and I’ll have an entire blog post and, hopefully, interview with Dennis, soon.

But the single most interesting thing that came out recently (I know it defies logic) is the Official Thor Trailer for 2011 (see below).

Being that I was in Norway a few weeks ago (and will be visiting again in February 2011) it was interesting that no one there knew about the movie – well, stranger things have happened.

Nuff for now – one of my longer posts – hopefully will keep readers busy for a couple of days trying out all the stuff like Hitsplitter.com and maybe NodeXL if they want to play with Influencer Maps – hey … people could do worse than that and spend tons of money on influencer lists and still not get at the true root of Influence.

I’ll stop here.

…. but I would like to know more about how extensive the data set is for the 101 Marketing Charts (embedded below).   My sense is the information almost always just confirms what we already know.

Blogs:

The words “Insights” and “Analysis” seem to generate the most views of blog content (I guess that’s because people are looking for insights and analysis – the big picture, no surprise here) according to slide 11 in the deck.  If your giving away something (slide 13) you’ll get a better response than if your not (common sense) while the best time to get your content seen is 10AM (but in what time zone – ha!) according to slide 24.

If you have a blog it positively increases your Twitter Reach (Slide 70) by close to doubling your number of followers and for some reason if a B2B business blogs regularly it’s more helpful (Slide 72) than if a B2C business does it (for followers).  Let’s assume your doing all the right things and your a B2B business that has a blog – the more you blog (Slide 73) the more you will have content indexed in search engines (that makes a lot of sense), again, no surprises here.  And in Slide 74 it’s shown your business will double it’s inbound links if it blogs regularly which will help search engine ranking, of course.

Twitter

If you put a picture of yourself on your Twitter Page (Slide 75) it very strongly impacts in a positive way the number of followers you get by as much as a factor of 10.  The more followers you have the more leads you’ll get (Slide 81)

Lead Generation:

Slide 29 contradicts my own findings that Email Marketing provides the highest return on investment – HubSpot says it’s Paid Search, but I’m wondering if the data set being used is much smaller.  Having a webinar (slide 31) is helpful to lead generation (makes sense as your providing immediate content via the webinar and asking for leads, in a way) but the gains are not that much.  Suppose if enough people attend the webinar it can make a difference in the leads generated.

In slide 35 it’s shown a form having 3 fields (first name, last name, email address, for example) convert at a better rate than anything else, with 5 fields being only slightly worse for getting a form filled out.  Again, expected since the less information you ask for, the more likely people will bother to compete an online form.   In Slide 38 putting in a “locational” noun such as Click “Here” produces a better CTR than phrases for a button that just have one word, and the word not including a location.

Facebook

On Slide 60 it’s shown people like to fan food pages and movie pages (Slide 61) but Government, Local Businesses and Musicians have a much harder time getting “liked”.  Ha!  Most content on Facebook is shared on Saturday (according to the chart on Slide 64) anyway (probably because people have more time “off” during the weekend to play.

An amazing chart on Slide 104 shows France and UK have the rest of the world beat when it comes to Facebook Fans to Business Page sites (Wow!).

The Future

In 2010, according to Slide 107,  Google and Facebook drove 3/4 of the business value of services that business offered while in 2013 it is expected Google will contribute less than half of the value and the market is looking for something new it hasn’t seen yet (or is barely aware of).  The tables will be reversed for channels offering value, today it’s Organic and Paid Search while in 2013 it is expected to be Social Media Marketing (what about Social Media Analytics)?

In Slide 118 David Meerman Scott tells us that brands that positively engage (Fortune 500) are able to positively impact Social Media ROI (however it’s defined) than those who don’t – a very interesting chart indeed, and one I’d like more clarification on.  In fact, in Slide 119 Scott tells us that Fortune 500 companies that respond online right away are almost twice as likely to be profitable as those that don’t (again, we need to know how that is defined, but it sure looks good).  And in Slide 125 Small and Medium Sized Businesses favor AD Hoc experimentation in order to find and beat competitors while Large Companies do it for Long Term Strategies in mind – again a very interesting finding that makes a lot of sense.

To sum it up, the charts were a grouping of previous presentations but I found several good charts in there that lead to interesting discussions, some that may end up landing in my book.

Thanks HubSpot!