The title to this post is the same as one of my short columns in the September Premium Newsletter, which went out yesterday. It was the search issue.
Since there have been updates in the last several hours, I wanted to follow up with a couple of thoughts on new developments. A testament to how rapidly technology changes - or at least information about what we think we know.
Google+ search
Do you have it yet? You will know if you do by looking at what is written on the search bar up top. As I just predicted 24 hours ago for newsletter readers, the integration of share and search data produces some interesting results.
You will see them labeled "best of" instead of "most recent".
This puts more information at your disposal. And I would venture an educated guess that businesses will make use of it just as soon as they can launch accounts officially.
Also, if you have not heard. Google+ is now open to everyone.
Social data targeting
There is another company that is quietly doing some work with social data. Last week, Walmart acquired a company that provides mobile ad targeting technology One Riot, to integrate to Walmart Labs, the old Kosmix.
Here's how OneRiot describes its social targeting engine for mobile ads, through a Twitter ID (slight editing):
Based on public social data that we license via our friends at Gnip, we’ve generated user interest maps for just north of 75MM active Twitter users.
This number gets bigger every day as we suck in more Tweets from the licensed hose. Meanwhile, our demographic coverage is 80% accurate for about 80% of the Twitter population.
These stats improve with every new release (approx every 3 weeks).
How to do we determine this information? We start at two points. The first is to create language models that breakdown how users tweet. The second is to study follow-graphs that reveal who users are influenced by.
By fusing these two approaches, we can find discriminating characteristics that identify a specific user as belonging to a certain demographic group or a certain interest-category group.
[...]
broader-based influencers such as @barackobama offer few discriminatory clues about their followers – as many users in many demographic groups follow the US President, to the point where any signal is drowned out by noise.
Our system spots literally tens of millions of similar subtle patterns.
These patterns then “compete” inside an artificial intelligence system that results in an accurate rendering of “who you are” according to your Twitter activity.
Pattern recognition
Search and social data targeting both take advantage of automated pattern recognition. Extract data out from the data that was put in according to specific parameters. When looking to work with data, the most important piece is the query set.
Machines driven by algorithms, operating on massive amounts of data mostly operate by exclusion - this is not - they just do it incredibly fast. Although, there are reports of some machines being programmed to learn from past queries.
The human brain, on the other hand, does pattern recognition in the opposite fashion: by inferring meaning or connection from the minimum amount of information possible. It is a marvel of engineering. Try it.
At the next dinner party, pull together a list of first names of musicians. Only the first names. Then flash them in a random sequence from most common to increasingly least common, and see how quickly your guests guess what they all have in common.
My guess is very fast.
In search of certainty
Why is search so important? We search for answers.
My friend Jonathan is working on providing context around his upcoming book: Uncertainty. He's doing that by telling the story that moved him to write it.
I left a comment on his latest post titled have a little faith: we never let down the people who believe in us. Part of it is also believing in yourself and your business - the value of your trade.
To me, certainty is in asking the right questions, or better ones. It's about relevance and the query set. It's in the discipline, structure, and drill of identifying the model businesses and individuals trade on, and the consistency of helping make those connections work.
Results follow.
[image courtesy of Simon Law]
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