Well, Steve Jobs died yesterday and I wanted to write something but was too exhausted, jet-lagged to do it.   Was thinking of some of the things Steve Jobs said and did and here’s what stands out, according to David Henderson (and I could have picked almost anyone’s post, GigaOM, TechCrunch or a dozen others ..

Steve Jobs once said:

Here’s to the crazy ones, the misfits, the rebels, the troublemakers, the round pegs in the square holes… the ones who see things differently — they’re not fond of rules… You can quote them, disagree with them, glorify or vilify them, but the only thing you can’t do is ignore them because they change things… they push the human race forward, and while some may see them as the crazy ones, we see genius, because the ones who are crazy enough to think that they can change the world, are the ones who do.

 

But I can also relate to Steve Jobs, having grown up at the same time.    As I was reading a book on my iPad today, I remembered that was made possible by the work of Steve Jobs.  A lot of other stuff too.

We’ll all miss him.

Gary Angel wrote a post on 9/23 (while I was in London) on Repeatable Analytics - which is part of scaling analytics work.  He said …

… I lamented that good attribution systems were forking off from Web analytics. As I’ve thought about this, however, I’ve begun to think that this process may be inevitable. Web analytics systems (and other general purpose analysis tools) are the systems we use for broad exploration. When we find a technique that really works, it’s often more convenient and more elegant to split that system off into a dedicated tool.

Angel then goes on to outline 3 standardized approaches he uses at Semphonic.com that, in and of themselves, could produce insight; they are Site Navigational Structure Analysis, Media or Publishing Site Content Correlation Analysis and Customer Support Content Effectiveness Analysis and he goes on to describe each in the post with a paragraph or two, well worth reading. What I get in this post is, that while deep dive analysis, using the “broader tools” of Web Analytics or Social Analytics (ie; Radian6, etc) is good for an overall view, examining specific types of issues, as identified here, often is best done with a seporate tool. Gary thinks this is inevitable.

Also Chris Brogan interviews Aaron Strout (who I also work with at WCG) on 9/23, I have a copy of the book and intend to review it one of these days, after I get done reading Philip Sheldrake’s book (behind in my reading, actually).  Also, on 9/26 an excellent post on Optimizing the use of QR Codes was published in Search Engine Watch- How To Create QR Codes With Optimal URL Strategies In Mind and there is a guide to making QR codes that work – here.  Also on 9/28 I read a post on Globalizing Your Business Using Social Media  which was pretty good in that I don’t see this kind of readout of information often, and reminds me of chapter 3 of my book.  I also found some of the ideas here facinating – and they make a lot of sense, such as … :

Your biggest investment in social media should be at the beginning of your campaign: It is very important to remember that you are in it for the long haul. When you choose to use social media for your business, it means that you are committing to investing time on a very consistent and regular basis. The more top-quality content you are able to share with other people, the more valuable your relationships with others will be. It is critical that you keep on top of your social media channels consistently and monitor the interactions. It is all about interactions—on a domestic and a global level.

Then the Kindle Fire came out and I was in Rome, looking at stories on it like this one at GigaOM, and was thinking the pre-caching of the entire web experience and what it would do to Analytics down the line (a year or two), certainly the next two years are going to drive more change than the last 20, so hang on for the ride. In fact, Leaked Sales Data Puts Kindle Fire Sales At 250,000 Over Five Days suggesting in a few months there will be plenty of Kindle Fire tablets around, and plenty of data to aggregate and do research with.  Meanwhile the Apple iPhone 4s just came out – I’ll upgrade to it as soon as I can.  Besides, according to GigaOm, the iPhone is a  Cheap medical super microscope, I wonder if the 4s will improve it even more.

Also, while in Italy I was reading about Private Clouds and Micro Clouds -here’s what MicroStrategy’s new platform does:

Cloud Personal makes it easy to spot trends, identify outliers, and uncover insights that lay buried in a range of sources, from your own Excel data to public databases such as Data.gov. Users can also share their dashboards via email, or publish them to an unlimited audience via Facebook, Twitter, blogs, and more. The site link above has a gallery of public visualizations and you are welcome to share you own there as well.

Then on 9/29, the day of my book signing in Rome, I saw a post on Text Analytics (What’s in it for me) at Smart Data Collective - the paper being examined was by Seth Grimes and is worth downloading – but as we all know, Text Analytics rarely gives us results worth talking about or going to the bank with.  I think in 8-10 years, that might no longer be the case, but for the time being …. the article says

….Text analytics is no walk in the park. Even humans find it difficult to clearly determine the meaning and implications of every bit of text they view, and this is a task that machines don’t do as well as humans. The current state of the art is far from perfect, as the best practitioners and vendors will surely admit. So why is the market growing 25% per year, now reaching $835 million annually? That’s not curiosity spending.Decision makers are shelling out the money because there is something in it for them.

 The question is: what’s in it for you?

Probably nothing, at this point – and if you really care about the quality of the verbatim your reading – you’ll have to do just that … read them – I know people are resisting doing that, and many platforms are putting forward data that, when read by a human, has a much different meaning – making it hard to have confidence in Social Analytics data if you need precision.

And Google Analytics Gets New Design, Real Time Feature and Paid Premium Service (as mentioned by Frank Reed in Marketing Pilgrim) – I have yet to take it all in as I haven’t looked at my Google Analytics for a few weeks (no time) but the most significant thing, to me is not the real time part (which was expected) but the top tier service (which cuts into Adobe Omniture, WebTrends, etc revenues if it takes off); also Privacy issues that dogged earlier versions of Google Analytics have been resolved, as the post explains.  And K.D. Paine weighs in and also downplays the importance of Real Time Analytics, since most companies can’t really respond in Real Time, anyway. Meanwhile, Facebook Analytics continues to improve by doing more bucketing of user data - read Facebook Launches “People Talking About This” Metric, Premium Ad Unit & More.

I also thought the post on The Future of the Social Web: Social Graphs Vs. Interest Graphs by David Rogers (who I have met) made interesting points such as:

In order for social networks to truly reshape our experience of the rest of the Web, developers must first understand the relationship between our social graphs and our interest graphs.

A social graph is a digital map that says, “This is who I know.” It may reflect people who the user knows in various ways: as family members, work colleagues, peers met at a conference, high school classmates, fellow cycling club members, friend of a friend, etc. Social graphs are mostly created on social networking sites like Facebook and LinkedIn, where users send reciprocal invites to those they know, in order to map out and maintain their social ties.

An interest graph is a digital map that says, “This is what I like.” As Twitter’s CEO has remarked, if you see that I follow the San Francisco Giants on Twitter, that doesn’t tell you if I know the team’s players, but it does tell you a lot about my interest in baseball. Interest graphs are generated by the feeds customers follow (e.g. on Twitter), products they buy (e.g. on Amazon), ratings they create (e.g. on Netflix), searches they run (e.g. on Google), or questions they answer about their tastes (e.g. on services like Hunch).

Occupy Wall Street is all the news and on 9/3 Washington Post put out a primer on it.

But on 9/3 I saw a post by good friend and mentor Bill Hunt on his  New Venture Annoucement – Voice of Consumer Data Management System – having worked with Bill at IBM and seen him at various search conferences I know how his mind works and the approaches he tends to take, and can well imagine what led to the development of this new offering of his.  Here’s what his new platform does today – and it’s really only for big players – enterprise companies running large paid search campaigns – the sweet spot – along with organic search campaigns.  Much of this platform takes from his earlier work, which I’ve seen parts of, and some of it by far, surpasses what I have seen him show me, before.  If you are in the audience for an enterprise based BI Search tool – this may be the one for you (again, you probably won’t find much here unless your company is Dell, IBM, etc, etc) – but even smaller companies have complex business units – who are often competing with each other – who’s to say this platform can’t help them, as well.   Here’s more information:

This is not a mainstream consumer site product. It is designed for a site with a large base of keywords typically more than 500,000 of them that want to get more out of the product. We are looking to develop a mainstream version of the application but seems those customers want something cheap, that does a lot of automated analysis and does not require them to think.
We are not quite thee yet and when we are we will roll that version out.

What can we do today?

1. Aggregate all of your keyword data into a single searchable repository with role-based login access by different roles in the company.
2. Conduct paid and organic co-optimization analysis – are they cannibalizing or complimenting each other.
3. Preferred Landing Page Analysis – is the page you “want to rank” the one that is ranking?
4. Rank Analysis – same as everyone else but we allow you to sort by priority words, line of business and any keyword cluster or classification
5. HitWise Integration – if you have a HitWise account we can pull in the API feed and compare HitWise trends to your actual data
6. Data mine and Report on any of 55 different keyword variables
7. Develop Searcher Intent and Persona Segmentation – using any of 50 performance or segmentation factors cluster keywords into logical segments
8. Store, sort and report on data across business units, lines of business or countries
9. Understand performance by keyword length, position and paid and organic assists
10. ROI Modeling based on multiple variables

Bill Hunt and his team are now talking about DATA – not keywords – DATA – and so he joins our language now – and he talks about the challenges of creating this magnificent platform and what he found out when he did it – outright fraud by some agencies – not surprising to me at all.

Data Integration - The biggest challenge was integrating and managing the data. Readers, there is some messed up data out there. I found that there are a lot of agencies and people that should be fired for incompetence if not fraud. This was the biggest challenge of integrating the data. There are large volumes of it and we needed to suck them in and align them.

Nuff said.  Contact Bill Hunt if you want to know more.  There was also a good post on Mobile SEO that I need to take a deeper look at, and on the eve of Steve Jobs death, his invention of the iPad may also be helping to save the world in terms of energy -Is It Really True The iPad Makes Flying More Fuel Efficient? actually, the answer is yes.

And not Microsoft considers bidding for Yahoo, as if anyone cares anymore.