#contextual data

The 5 Best Practices For Personalized Video Marketing

getty What makes personalized video marketing work? As we await the expanding impact of AI, marketers are using platforms to draw on their data for increasingly targeted messages. At the personalized video platform Idomoo, CMO Yotam Benami believes five best practices can determine the difference between failure and success. Paul Talbot: What have we learned about how to use data to personalize…

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How Hyperlocal Mobile Advertising Changes Everything

One of 2014’s biggest stories is the rise of hyperlocal advertising. Hyperlocal, as it’s called in ad tech circles, allows marketers to use a smartphone’s GPS to geographically target audiences for the purpose of delivering relevant ads.

The post How Hyperlocal Mobile Advertising Changes…

New Project & Importance of Contextual and Real Time Data

Our team was quite busy (yes, I know, as always!) recently, working on our client piece of work and developing new exciting idea, which soon will be ready for your testing, comments and feedback. 

We are launching new mobile app with an ambitious goal to provide users information on demand - contextual information or as we call it real time info.

One of the great writers Irene Ng emphasizes interesting facts in her book. We currently have 6 billion mobile phones around the world and 68% of their users claim they sleep with them by their heads. And yes, since I got my first smartphone, I also sleep with it by my head. This is really amusing, but also very important fact. Ben Hammersley from Wired makes fun of us and says that smartphones took away 20% of our brain and even made us a little bit retarded. 

This small device incredibly changed our behaviour in recent years. First, it gave us opportunity to play - take pictures, edit videos, write posts, check in or measure our blood pressure on the go.  And yes, we loved it! We loved it so much that Big Data became one of the biggest buzzwords around. Marketers love it, tech entrepreneurs love it, researchers hate it, saying that it is impossible to make sense in this huge noise of meaningless numbers, locations, words and vague facts.  

But we always know, that when humans get problem, they love finding solution. So, we saw how smart folks used this mess of data for practises such as predicting flu outbreak following Google Trends, managing earthquakes using social media or even predicting election results looking at viral videos. Not to mention, recent trend in using sensors and tapping into many more ways to make our life easier when we need it.

Our team wants to be a part of this data curating and problem solving as well. We believe that in a few years it will be ancient to find out the current venue atmosphere by physically going there and checking it out. We believe that standing in a queue might sometimes be fun, but usually it is not and you should be able to find out about the queue itself before you are in the place.

We dream that one day we will be able to see how venue looks like NOW live. And that we will be able to explore all places real time on our phones.

We also believe in micro localised content. It is incredible feeling to imagine how many things are going on at the same time in the same area. You might think that venues are the same every day, but just look - that coffeeshop just got new cake, and this small venue is running a free workshop and your favourite market has a brand new stall you will love. We all know this extraordinary feeling when you unexpectedly notice graffiti artist drawing live or when you rush after work and stop for a cigarette just because this street musician caught your ear. Places, areas and people change every day and exploring them is such a great experience!

We decided to use available data, gather data ourselves, write algorithms and partnership with others to let everyone know what is going on around them in real time.

Moreover, we strive to make this experience contextual. We won't recommend you a rooftop bar on a rainy day and we will definitely encourage you to go out and have a picnic in a local park when it is sunny! Technology should be smart and we believe that best solutions come from technology being in partnership with humans.  

To make this story short, we started from Shoreditch area. We went out ourselves, we explore, record, hear what others say, we talk and sometimes we just enjoy exploring local real time. 

We also spent so many hours trying to find real time information locally. We downloaded around 200 mobile applications, we constantly check Facebook and Twitter and we check venue websites every day. So we know what you feel when it is Friday 9pm and you are in the area and you want something and the only one available option is 'just go, be spontaneous and try everything you see in front of you, maybe you will find something'. None of us like spending 30 minutes browsing and trying to find info on the go. Neither, we like to find out that all pubs we tried are completely full! We also hate to miss best events nearby especially when we are in the area and we get jealous when our friends discover something amazing we've just missed!

So, we are Shoreditch Hype and we will give you real time information in Shoreditch. We soon might come to other areas or even start using real time information for solving bigger problems. But currently, we are coding, discussing and finishing our first app which we really believe is great.

If you would like to contribute in any way, please get in touch [email protected]

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Dr. Hansen said the problem of data without context could be summed up in a quote from the playwright Eugène Ionesco: “Of course, not everything is unsayable in words, only the living truth.”

- NYTimes

In an interesting blog post on the NYTimes on February 24, Nick Bilton briefly explains the problem with making decisions based on "Big Data."  

Google has a really cool property that predicts the severity of the flu season based on Google Searches and a fancy algorithm (I definitely checked it this winter when I heard that this would be a record flu season).  Bilton explains why Google's flu algorithm was off by a magnitude of almost 2x when it predicted that 11% of the US was infected with the flu at the height of the flu season this year.  Humans and even the smartest algorithms in the world do not understand the story that a data set is telling if they don't understand the context of that story.

It is extremely important for an analyst to know the contextual information about a data point to come to a conclusion about what it says.  

In another funny anecdote from the article, the author explains how a professor misinterpreted a data set and came to a completely incorrect conclusion about the habits of his college students.  His class used Arduino computers to conduct a small study on when students took an elevator versus walking down the stairs at a dorm.  The computers produced data that lead to a surprising result.  The students changed their behavior during the day - they took the elevator in the morning and the stairs in the afternoon.  The conclusion was that students preferred the stairs over the elevator in the afternoon and vice versa in the morning.

Fortunately, the professor started talking to a security guard about his conclusions from the study.  The guard laughed and informed the professor that he was wrong.  One of the elevators was broken in the afternoon, so the students had no choice but to take the stairs.

This very trivial example from the article demonstrates how valuable context is to interpreting data.  Without the context, we can make many different conclusions based on the same information.  

Google's futuristic map plan

Google's vision for geospatial information: "We don't want a monoculture where there is just one map of the world. There never has been; there never will be."