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Data analytics as the key to know your customers and offer them what they really want.
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A Predictive Analytics Primer

A Predictive Analytics Primer | Big Data & Digital Marketing | Scoop.it
What you need to know and ask.
Luca Naso's insight:

Predictive analytics are gaining in popularity, but what do you—a manager, not an analyst—really need to know in order to interpret results and make better decisions? 

 

The quantitative analysis isn’t magic—but it is normally done with a lot of past data, a little statistical wizardry, and some important assumptions. Let’s talk about each of these.


1. The Data: for good predictions you need good data;

2. The Statistics: regression analysis is what is usually used;

3. The Assumptions: every model has some assumptions, beware that assumptions can be invalid sometimes ...

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Social Media's New Big Data Frontiers - Insights from Images

Social Media's New Big Data Frontiers  -  Insights from Images | Big Data & Digital Marketing | Scoop.it

Users might feel a knee-jerk suspicion at the idea of self-correcting algorithms mining their photos and thoughts for insights, but surely they’ll be happier when they see ads that they’re actually interested in, rather than spammy banner ads for weight-loss programs and random online learning courses.

Luca Naso's insight:

Great piece with lots of information and links about Big Data's new frontiers on images.

 

Takeaways:

1. According to an IBM survey, 70% of CMOs feel unprepared to deal with Big Data

2. IDC predicts data tidal ways keeps increasing, with social media being leaders

3. Machine learning and AI are more and more commonly applied to marketing, not just for text but also for images

4. Targeted advertisement is expected to benefit the most out of data mining

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Big Data in Real Estate: The Power Of Predictive Analytics

Big Data in Real Estate: The Power Of Predictive Analytics | Big Data & Digital Marketing | Scoop.it

"We have built a model that can predict with 75% accuracy the likelihood that a home will sell in the next 30, 60 or 90 days," says Scott Bailey, EVP of strategy and analytics for Target Data, a marketing firm that combines big data and analytics to help businesses target consumers during the major life event of moving."

Luca Naso's insight:

We are just applying the same principles used in CRM systems to houses as opposed to consumers.

 

By matching geo-demographic scoring with listing data, we were able to better leverage the money PODS was spending on direct marketing throughout the year, not just during the traditional peak season.


What happened ten years ago is important, but now taking into account what happened yesterday (even earlier today), is what I see really driving predictive models in the next decade.

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Glenn Cooley's comment, September 13, 2013 12:29 PM
Predictive analytics can be expanded to tourism areas as well.
Pritesh Chauhan's curator insight, September 18, 2013 1:12 AM

Big data analysis for real estate will make clear way for achieving bigger dreams.

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5 basic rules for Big Data analysis

5 basic rules for Big Data analysis | Big Data & Digital Marketing | Scoop.it

Thomas Zoëga Ramsøy uses neuroscience and he makes 5 good points an analyst/data scientist must consider while dealing with big data. The author is a PhD in Neurobiology and provides a fascinating example from Neuroscience.

Luca Naso's insight:

"If you have an enormous statistical power, any test you run can easily turn out to be significant. Everything is significant in the land of Big Data!"


In the article you can find 5 simple suggestion on how to avoid significant false insights.

 

I suggest the following approach:

1. Never stop once you find a relation (try to confirm your idea in several different ways);

and, most importantly

2. Always look for ways to disapprove your idea (and not for ways to make it stick).

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General Electric joins the 'big data' party

General Electric joins the 'big data' party | Big Data & Digital Marketing | Scoop.it
GE just announced a new "big-data" and analytics platform it calls “Predictivity," and it has some big partners on board to give it reach.
Luca Naso's insight:

Megacorporation General Electric has just announced a new big-data and analytics platform named “Predictivity”, whose main features are providing real-time insight and analytics.
 
GE also firmed up partnerships with Pivotal, Amazon, and Accenture. The EMC-backed Pivotal partnership might be the biggest of the three. Pivotal is the recent high-profile spin-off of EMC and VMware that got $105 million in funding from GE in late April.

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Business Intelligence Is Transforming Into Intelligent Businesses

Business Intelligence Is Transforming Into Intelligent Businesses | Big Data & Digital Marketing | Scoop.it
NEWS ANALYSIS: Business Intelligence is being transformed by the ability to use massive cloud computing services, big data analytics and huge external data sources.
Luca Naso's insight:

What I find interesting in this article is the idea that performing simple queries over extremly large data set can actually produce better result than using complex analyses over not-so-large data.


 "Creating simple queries over huge data sets can provide insights much more quickly and with more accuracy than trying to create sophisticated algorithms narrowed toward smaller samples."


On the basis of this idea business intelligence is shifting from making better use of the data inside one's own company to using those vast pools of data outside the firm (big data if you will) to capitalize on customer sentiment, buying patterns and economic indicators.

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Tribeca 2013: How Big Data Can Save Movie Marketing

Tribeca 2013: How Big Data Can Save Movie Marketing | Big Data & Digital Marketing | Scoop.it

...and why it could also kill creativity

Luca Naso's insight:

Big data, to use the industry buzzword for these sprawling streams of information, is potentially so valuable that moderator Richard Whittington, SAP Labs senior VP/general manager of media industry solutions, likened the drill down potential to historical oil booms.

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Big Data in Retail: Examples in Action

Big Data in Retail: Examples in Action | Big Data & Digital Marketing | Scoop.it
Savvy retailers use big data analytics from web browsing, social media, industry forecasts, existing customer records to predict trends, prepare for demand, pinpoint customers, optimize pricing and promotions.
Luca Naso's insight:

Top retailers are using Big Data to gain a competitive advantage:
predicting trends and preparing for future demand.

 

Synchronize prices hourly with demand, inventory and the competition.

 

Pinpoint customers who will likely buy your product and contact them as they wish to be reached, when they are in the right location, and engaging them with personalized real-time offers.

 

Retailers using big data technology are able to provide a smarter shopping experience to influence purchase decisions and edge out the competition.

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Could iPhones and Big Data make us healthier?

Could iPhones and Big Data make us healthier? | Big Data & Digital Marketing | Scoop.it

we talk a lot about how gadgets are changing how we communicate and so on - but could the devices we all carry around with us now also be about to make us a whole lot healthier?

Luca Naso's insight:

Collecting lots of data isn't just about making more accurate Netflix recommendations.

 

Rather than just judge us on what we say in an eight minute consultation with our GPs, maybe they'll be able to pull up our health data and analyse it properly?


Scientists would be able to more easily identify the effects and side-effects of different treatments, and more quickly develop and bring new treatments to patients.


Of course - there is one awkwardly massive downside to this. Privacy concerns.

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Andy Collett's curator insight, November 25, 2013 10:43 AM

these devices have great potential to keep us all well, however we do have to use them regularly and then ajust our behaviour. Otherwise it's just another interesting gadget.

Fàtima Galan's curator insight, November 26, 2013 11:50 AM

"

Luca Naso's insight:

Collecting lots of data isn't just about making more accurate Netflix recommendations.

 

Rather than just judge us on what we say in an eight minute consultation with our GPs, maybe they'll be able to pull up our health data and analyse it properly?

 

Scientists would be able to more easily identify the effects and side-effects of different treatments, and more quickly develop and bring new treatments to patients.

 

Of course - there is one awkwardly massive downside to this. Privacy concerns.

"

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Do You Know Where You’ll Be 285 Days From Now At 2 P.M.? These Data-Masters Do

Do You Know Where You’ll Be 285 Days From Now At 2 P.M.? These Data-Masters Do | Big Data & Digital Marketing | Scoop.it

Microsoft researchers have developed a mobility prediction system that knows where you will be even years down the road. What does this mean for the future of business?

Luca Naso's insight:

Using Big Data to make prediction is quite normal.

However this is not about guessing your _next_ purchase, or next next.

This is about where you will be _years_ from now. If you will be planning for a trip to Europe, or going for a running workout, or just buying some cheese at the grocery downtown.

 

Probably the reason why this is possibles lies in the following comment:

 

"No matter how spontaneous we think we are, humans are actually quite predictable in our movements"

 

Do you agree?

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Big Data & Predictive Analytics

Big Data & Predictive Analytics | Big Data & Digital Marketing | Scoop.it
Predictive analysts usually think of doing predictive modeling on structured data pulled from a database.
Luca Naso's insight:

Most of the power of Big Data lies in its predictive capability.

 

1. Big Data provides the information,

2. domain experts provide the structure for how to set up the data for modeling,

3. predictive analytics provides the muscle to open the doors to what is hidden in the data.

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Bringing ‘Big Data’ to Horse Racing

Bringing ‘Big Data’ to Horse Racing | Big Data & Digital Marketing | Scoop.it
Horse racing seems like a perfect candidate for the “big data” treatment: If more information about horses’ movements, their bodies and behavior were collected and analyzed, wouldn’t it be easier to handicap?
Luca Naso's insight:

The big-thinkers call that “messy data” because it’s difficult read, but that may be where racing should dig in, just as happened with baseball when some new metrics were introduced. “If you look at the things that actually count in the long run statistically, then you can predict much better"

 

When you are dealing with Big Data, it _always_ looks messy at the beginning.

 

You then need some Big Brains to turn the mess into a gold mine.

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Big Data is Hollywood's New Rising Star

Big Data is Hollywood's New Rising Star | Big Data & Digital Marketing | Scoop.it
With huge troves of data available to mine, marketers are becoming increasingly sophisticated at targeting movies.
Luca Naso's insight:

Data Analytics can be used to make predictions on the fortune of a movie and to make a better targeting of the advertisments.

 

It seems to me that the movie industry is seeing the great power of Big Data, but is not taking full advatange of it.

 

Big Data does not consist just in counting clicks or shares, and it does not have to miss "film that has tremendous artistic value but has tough subject matter".

 

Maybe such a kind of movie will not create much buzz on the web and will not get many positive reviews, but it will create some and in some web communities it will be greatly appreciated.

 

If used properly (for example with cluster analysis) Big Data is able to identify succesful movies with a limited audience.

 

 

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