Showing posts with label Future. Show all posts
Showing posts with label Future. Show all posts

Wednesday, February 13, 2013

Five Analytics Points You’ll Wish You Knew


When taking on the task of introducing or reforming analytics within any organization, there are a few things that the experts recommend making sure you are aware of. I’ve compiled the ideas and sentiments into five points:

No Silver Bullet

There is no silver bullet 

There is no one specific tool or process that will work for everything or everyone. At the same time, obsessing about tools and which one will work the best will only have you chasing your tail with no success. Avanish Kaushik mentions in his blog that 10% of your time should be spent implementing tools, whereas the other 90% should be used to make sure you have the structure and organization to support and derive the correct information from what the tool as well as other mediums give you. (Kaushik A. , 2011)



It’s not about the Data, it’s about how you use it

Data is where everything starts. It is the iron ore of the digital world. Without it, nothing of value could be derived. Just as with iron ore; however, it is not helpful to gather as much as you can of everything you can if you are not prepared to use it. Success will not come by how much data you’ve collected, by how well you can use a tool, but more from your business savvy and your soft skills. (Kaushik A. , 2011) Turning data into something a business leader can use is key. Ovetta Sampson in a comment to Sean McGinnis on his blog stated:  “people lie…not on purpose but unconsciously and incrementally. So when you look at analytics you have to account for the whole human thing. Correlation DOES NOT equal causation and if you really want to extrapolate your analytics and measurements to account for consumer behavior then you better brush up on your scientific methodology or hire a Ph.D. scientist because you can’t do it with data alone. A lot of marketers get the data and have no idea what to do with it and use junk science methodologies to make decisions that have no basis in proven reality. Data alone doesn’t tell the story. Humans are known to act against type for all number of untold reasons. Data is better than ever today but it isn’t the whole picture. It isn’t the holy grail and if you aren’t a student of the behavioral sciences – anthropology, psychology, sociology- you won’t know what to do with it.” (McGinnis, 2012)

Start With Outcomes, invest in metrics that matter


Data, Data, Data, It's how you use it. If how you use the data is key, how do you best use it? You start with clear outcomes and invest in metrics that matter. Augie Ray while commenting to Sean McGinnis on his blog stated: “ I wish earlier in my career I’d realized that people will settle for ILLUSION of metrics rather than invest in the metrics that matter.” Aaron Biebert in the same blog mentioned: “What gets measured gets done. If you measure and distribute meaningless stats to your team, they will work on improving them. Measure what matters.”  (McGinnis, 2012)

It helps no one when you measure how many times birds flew past your window on the way to work. Find those things that drive value.  No one will care about data six months from now when nothing has changed. Money is normally one of the best outcomes to tie metrics to for businesses. Non-profits may care more about impact, governments about reduced costs. Find what drives value, and then measure it, use the metrics to drive change and you will be more successful because of it. (Kaushik A. , 2011) (50 Resources for Getting the Most Out of Google Analytics)

Be Pragmatic

Being pragmatic means to deal with things sensibly and realistically and to look at the world based more on the practical rather than the theoretical. Theory is great at times, but practicality is where business is done. Some things cannot be measured, tracked, or accounted for. Some things are impossible to do, to know, etc. The human contribution to the science of analytics can throw the whole train off the track. No one is perfect in the world so don’t anchor to what should be able to be done, measured, etc. in a perfect world. Focus on the small ways you can improve business priorities and outcomes. Knowing that and realizing that analytics is not the end all be all will keep you afloat when the world turns upside down. (Kaushik A. , 2011) (Ben, 2010)

Jack be nimble, Jack be quick

Jack be nimble, Jack be quick

The field is constantly changing, adapting, and evolving.  Don’t be afraid of change, of using multiple tools. The questions we are searching for so we can answer are hard to find and changing every day. Be willing to be nimble and quick on your feet as you look for ways to improve. Don’t get stuck in a rut just because it has been working. That all can change in a blink of an eye. (Kaushik A. , 2011)

Don’t be afraid of elbow grease

There is a lot of work involved in analytics. Malcollm Gladwell said that it takes 10,000 hours to become an expert, and he was right. Dane Findley stated in Sean McGinnis’ blog post: “My best analytics coming from simply being in the trenches — working on my site every day for 4 years, you just start to get a sense of what will work and what won’t, before you even have to try it. ALSO: I wish I could have told myself years ago that everything works a little bit, but there aren’t enough hours in the day to try “everything” so you have to just pick a couple of key areas, create a strategy, and throw your weight behind those exclusively. Community Management is an essential piece of the puzzle, but it’s a huge time sponge. The more important piece is to keep Google happy (even though no one likes to say it directly like that, it’s so politically incorrect, yet true). The 3 analytics I look at each week are: uniques, average time on site, and referring sites (In that exact order).” (McGinnis, 2012)

Don't be afraid of a little elbow grease with analytics
To become good, you have to put in your time. It may not be actual elbow grease, but the more you put into it, the more you will get out. Avinash Kaushik suggests finding 5 hours a week outside of work, family, school, church, or whatever to devote to yourself to learn, experiment, and seek to become that expert in whatever you desire. (Kaushik A. , 2011)

What are your thoughts? For those of you already in the Digital Analytics industry, do you share the same opinion? What have you seen?


Works Cited

50 Resources for Getting the Most Out of Google Analytics. (n.d.). Retrieved February 12, 2013, from KISSmetrics: http://blog.kissmetrics.com/50-resources-for-getting-the-most-out-of-google-analytics/
Ben, W. (2010, July). Experience Marketers - What are 3 things you know now that you wish you knew when you 1st started. Retrieved February 12, 2013, from Warrior Forum: http://www.warriorforum.com/main-internet-marketing-discussion-forum/741889-experienced-marketers-what-3-things-you-know-now-you-wish-you-knew-when-you-1st-started.html
Kaushik, A. (2011, January 10). I Wish I Had Known That - Digital Web Analytics Edition. Retrieved February 12, 2013, from Occam's Razor: http://www.kaushik.net/avinash/i-wish-i-had-known-that-digital-web-analytics/
McGinnis, S. (2012, December 19). Learning Analytics: What I Wish I Knew Then. Retrieved February 12, 2013, from 321digital: http://312digital.com/learning-analytics-knew/

Saturday, January 26, 2013

Predicting the Future with Digital Analytics

Think of the enormous amount of data that we are generating and collecting from text and tweets to web traffic patterns and search trends. A lot of our conversations occur digitally and leave some sort of trail that if analyzed could lead to an understanding and prediction of the future.

We could predict things like potential disease outbreaks to the outcome of elections and the direction of the financial markets. We could be moving closer to the sci fi movie Minority Report where we could predict crime before it even occurs.

If all that data could be dropped into a black box and analysed using past data and real time data what could we learn and predict? In a discussion with BBC, Eyal Gever a digital visionary describes a crystal ball app that could change the world.

Potential Problems

One of the problems we have is the processing power needed for all that data, but that’s exponentially excelerating. The next problem is being able to get to all that data and the privacy concerns surrounding it. And what of all the power that someone would have that holds that data and can accurately predict the futue or if that data could be manipulated for the wrong reasons.

A few companies are already leveraging our data to better the world and predict future events. Lets look at some examples of the power that can be found within all that data.

Data Behind Texting Could Save More Lives Then Penicillin

Nancy of DoSomething.org describes the data behind texting and the lives that could be saved, policies that could be made, the effects of a hatefull speech or bad legislation and using trends and anlysis in that data to help better the lives of our children. She points out one example about noticing bad things occurring around 3pm in which a school could then change policies to fix this trend. She even goes on to say that Texting could save more lives than penicillin.

Disease and Health Prediction

A website called Sickweather uses social media to correctly predict and map disease outbreaks and in fact predicted six weeks earlier then the cdc in October 2012 about the early outbreak of this years flu season. Using Social media to predict disease outbreaks

Google Flu Trends uses flu related search terms as indicators of flu activity. There work is based on research described in an article in the Nature scientific journal titled ‘Detecting influenza epidemics using search engine query data’.

Another attempt at uncovering health trends and public health concerns using twitter was a study run by two researchers from John Hopkins. They uncovered interesting patterns that showed medications and home treatments being used by people to treat their  symptoms. One helpful trend they noticed was that people were trying to treat the flu with antibiotics, raising a public health concern that should be addressed.

Financial Market Prediction

Topsy Labs, a company that has access to twitters historical data and has a real time search engine for twitter mining finds that there is a statistically significant correlation between Twitter sentiment and Market prices.

Predicting Election Outcomes

In an article about Big Data in the 2012 election Forbes points out that were not quite there yet with using big data to accuratly predict ellection outcomes. One of the reasons they point out is that there are paralels to 1948 when Dewey was innacturatly predicted to win over Truman based on phone polling. The majority of people did not own phones and those that did tended to skew toward a particular demographic. Similar to today we dont have 80 year old Grandmas tweeting about there party favorites.

But Forbes concludes that it does add some useful information even though we still need to figure out how to process all that data effectively and filter out the signal from the noise.

Sources

  • http://www.bbc.com/future/story/20121010-app-could-predict-the-future
  • http://gigaom.com/2011/07/07/can-you-crowdsource-health-information-via-twitter/
  • http://www.nature.com/nature/journal/v457/n7232/full/nature07634.html
  • http://www.ted.com/talks/nancy_lublin_texting_that_saves_lives.html
  • http://about.topsy.com/2012/01/16/predicting-stock-prices-using-topsy-social-sentiment/
  • http://www.bbc.com/future/story/20121010-app-could-predict-the-future
  • http://www.forbes.com/sites/netapp/2012/08/29/big-data-takes-center-stage-in-the-2012-presidential-election/
  •  http://www.modernhealthcare.com/article/20130119/MAGAZINE/301199964