Customer 360: Understanding Your Customers in the Digital Era

Dave Birckhead

Information is the oil of the 21st century, and analytics is the combustion engine.” – Peter Sondergaard, Gartner

When most people think of advertising and marketing, an image of the “Mad Men” era agency comes to mind. But with surprising speed, the rise of digital–and the accompanying explosion of customer data–has revolutionized marketing.

Using technology and data, marketers today can better understand their customers, deliver personalized one-to-one experiences, and drive significant bottom-line results. To achieve these goals, they now spend over $20 billion annually on marketing technology, a market that has grown by over 67 percent in just two years. In addition, spending on big data hardware, software and infrastructure is forecast to grow to a total market size of $114 billion by 2018.

As the strategic importance of data has increased, new approaches to customer analytics have emerged as well. As customer interactions with companies grow and diversify, the…

View original post 3,801 more words

Baidu claims deep learning breakthrough with Deep Speech

Gigaom

Chinese search engine giant Baidu says it has developed a speech recognition system, called Deep Speech, the likes of which has never been seen, especially in noisy environments. In restaurant settings and other loud places where other commercial speech recognition systems fail, the deep learning model proved accurate nearly 81 percent of the time.

That might not sound too great, but consider the alternative: commercial speech-recognition APIs against which Deep Speech was tested, including those for [company]Microsoft[/company] Bing, [company]Google[/company] and Wit.AI, topped out at nearly 65 percent accuracy in noisy environments. Those results probably underestimate the difference in accuracy, said [company]Baidu[/company] Chief Scientist Andrew Ng, who worked on Deep Speech along with colleagues at the company’s artificial intelligence lab in Palo Alto, California, because his team could only compare accuracy where the other systems all returned results rather than empty strings.

baidu1

Ng said that while the research is still just research…

View original post 365 more words

Big-data-based food startup Hampton Creek raises $90M

Gigaom

Hampton Creek, a San Francisco startup that uses advanced data analysis to develop eco-conscious, egg-free food products, has raised a $90 million series C round of venture from a collection of big-name investors. Horizons Ventures and Khosla Ventures led the round, with participation from Salesforce.com founder and CEO Marc Benioff, Facebook co-founder Eduardo Saverin, and DeepMind founders Mustafa Suleyman and Demis Hassabis, among others.

Hampton Creek has now raised $120 million since launching in 2011. Its products Just Mayo and Just Cookies are sold in grocery stores ranging from Walmart to Whole Foods. It previously sold a general-purpose egg substitute called Beyond Eggs.

According to co-founder and CEO Joshua Tetrick, Hampton Creek is based around a simple premise. “Ninety-nine point nine-nine percent of the food we eat is totally shitty for our bodies and for the environment,” he said, and the only way…

View original post 401 more words

Boston’s MFA: We’re Not Stalking Our Visitors

The picture really scared me, that’s why someone says big data is bad. Imagine you live in a world with 24 hours monitoring.

Campaign Outsider

Friday’s Wall Street Journal featured this eye-popping piece by Ellen Gamerman on museums and Big Data.

When the Art Is Watching You

Museums are mining detailed information from visitors, raising questions about the use of Big Data in the arts

AR-AI090_BigDat_12S_20141211172950

One morning last week, a team of experts at New York’s Solomon R. Guggenheim Museum searched for hidden spots in the rotunda to conceal tiny electronic transmitters. The devices will enable the museum to send messages about artworks to visitors via their smartphones while at the same time collect details about the comings and goings of those guests.

At today’s museums, all eyes aren’t just on the art. They’re on the visitors.

Across the country, museums are mining increasingly detailed layers of information about their guests, employing some of the same strategies that companies like Macy’s, Netflix and Wal-Mart have used in recent years to boost sales by tracking customer…

View original post 224 more words

Big Data, Big Opportunities for Marketing

We are marketing people; we want to know how big data effect our marketing? Big Data & Analytics is enabling companies to deliver the right message, to the right person, at the right time, for the right price. Leading marketers are using this advantage to deliver greater value and relevance to their customers. Learn how in this video from IBM.

Data plus cloud computing can do a lot more than we can imagine now!

Big Data Is Good: A CEO’s Analysis

Someone Said BigData is dangerous; they think BigData is a way to expose and invasion of privacy; however, I believe that big data is good. I found an interview with Fox Business: A CEO’s Analysis. The CEO said: “Big Data is good. Good for our economy; good for people and good for society. I know this defies the newspaper headlines and I am not diminishing some real concerns out there. However, the good that data are doing now – and the promise it holds for the future – is remarkable”
Eric Schmidt

Big Data Is Good: A CEO’s Analysis

Watch the latest video at video.foxbusiness.com

A nice Video: intro to Big Data

Watch this video, a funny video about Introducing big data, what it is, why you should care, and how companies can take advantage to uncover insight and big competitive impact.

Intro to Big Data

We are the Big Data generation; learn it and use it in the future!

Pregnant? Big data is watching you

140609_WRONG_TargetPreg.jpg.CROP.promovar-mediumlarge

Wherever we travel in our brave new digital world, we leave behind a rich and fertile trail of breadcrumbs of data. Our mobile phones continually tell the phone company where we are, our credit cards reveal how much we spent, and where, and on what — and so on.

Welcome to the world of ‘big data’, where the chain store Target has data-mined its way into my favourite organ, the uterus — and can now accurately predict when your baby will be born.

Back in the old days, a bookstore might slowly build up a base of loyal customers by offering discounts, and mailing out a brochure every month or so. But ‘big data’ is very different. So let’s look at the three ‘V’s: volume, velocity, and variety.

First, volume. In the USA, Walmart, the giant chain store, harvests some 2.5 million gigabytes of data each hour — just from customer transactions.

Second, velocity. Today, we can analyse the data in real time. For example, you can quite accurately predict the sales figures of big shopping centres by monitoring the activity of mobile phones in the parking lot — even before customers have opened their wallets.

And thirdly, variety. The data can be GPS location data from your mobile phone, or it can be the entire contents of your address book with the phone numbers and birthdays of all your friends and their families. Big data also includes everything you have ever done on Facebook, Twitter and all the other social media — and let’s not forget the good old credit card.

Back in 2002, Target in the USA wanted to know which of its shoppers had just become pregnant — because it wanted more customers. You see, shoppers tend to shop at the same place that they’ve always gone to — and it’s hard to get them to shift. But when women get pregnant, it’s a whole new world — and the pregnant woman might be lured into changing to a new shop.

So Target hired Andrew Pole (who has master’s degrees in both statistics and economics) to see if he could data-mine his way into freshly pregnant uteruses. His starting point was the so-called ‘guest ID number’. This is a number that Target assigns to each customer, and is linked to their name or email address or credit card.

It soon became clear that women (who had voluntarily put themselves on the Target Baby Registry) were buying some 25 products around the beginning of their second trimester. These included mineral supplements such as calcium, magnesium and zinc, large quantities of unscented lotions, and so on. And if they bought a little bright blue rug, the new baby was probably a boy.

And when they started buying scent-free soap, hand sanitisers, washcloths, a handbag large enough to carry a few nappies and extra-large bags of cotton balls — well obviously, they were getting close to their delivery date. Indeed, Target found it could predict their delivery date with some 83 per cent accuracy — just from their shopping habits.

So Target began sending discount coupons for various baby items to customers, according to how they rated on Target’s own “pregnancy prediction algorithm”.

But then it got messy.

An angry father walked into a Target store just outside of Minneapolis, clutching a brochure that had just come through the mail, demanding to speak to the manager. Angrily he said: “My daughter got this in the mail! She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”

Sure enough, the brochure did carry the daughter’s name and address, and had advertisements only for maternity clothing, nursery furniture, and so on. The manager apologised.

A few days later the manager called the father to apologise again. But this time, the father was a little embarrassed. He said: “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”

Now some people like their privacy. Some Target customers were annoyed by receiving brochures packed only with baby merchandise, especially when they had not told anyone they were pregnant. So Target produced new brochures that had some non-baby merchandise sprinkled around the baby goodies, so the newly pregnant mothers didn’t realise they had been data-mined.

Target is happy. Their revenue jumped from $44 billion in 2002, to $67 billion in 2010 — helped mightily by the fact that with regard to pregnancy, Target knows, before it shows.

Now it’s early days for big data. But one step might be to have more transparency and openness about what we (the customer) are giving away — and what we get back in return.

Original post by ABC science

What’s Thanksgiving Weekend Travel Really Like?

UM SI/HON/PHYS 365: Cyberscience, Fall 2014

People often talk about Thanksgiving weekend as one of the biggest travel weekends of the year, but thanks to big data it’s now possible to actually see how accurate that is in different places– at least, in terms of driving.

The popular navigation app, Waze, which lets any users report traffic and accidents that can then be viewed by any other Waze users and used to find the fastest route, looked at the data from last years Thanksgiving weekend to see what travel trends showed.

waze

It turns out that in New York, people (at least the ones who use the Waze app) actually did more driving on Thanksgiving day than on the Wednesday before Thanksgiving, contrary to popular ideas that Wednesday is the biggest travel day. This isn’t necessarily true in every city, of course. They also found that the traffic data from Black Friday, which is normally considered a…

View original post 78 more words