Global out look for the entertainment and media industry from PWC. Interesting video highlighting areas for growth.
One of the under-appreciated points about Big Data is that as consumers we also act as producers. In each transaction, we contribute bits of analyzable data to the corporate information stockpile. Data hungry companies then draw non-obvious connections by mining zillions of data points. For example, if you are Walmart, you’ve learned that stores in the path of a hurricane often see a spike in demand for Pop-Tarts.
Walmart’s response after spotting this correlation is to now always make sure affected outlets are well stocked in advance with this easy-to-prepare food item. Data mining has been a powerful business decision tool for big box stores, but what about everyone else: can we as consumers directly benefit from all the data we’ve helped to create?
Online retailers and social media sites have led in this area. They have returned to the consumer some of their insights by providing customer-specific recommendations that are based on a global analysis of behaviors. Special collaborative filtering algorithms hunt through the data to find similarities between your own purchasing patterns and larger groups or clusters. These statistically-based recommendations are at the heart of Amazon’s book and Netflix’s movie suggestions.
But outside of e-commerce, companies have generally been reluctant to share their Big Data.
This lack of transparency was taken up in an article recently in The New York Times, If My Data Is an Open Book, Why Can’t I Read It? The writer tells about the frustrations in getting detailed data about cell phone and electric usage from each of her respective providers. She was hoping to see the geo-location data her carrier records (and, by the way, does make available to third-party marketers), but was told that the company doesn’t share customers’ own location logs with them without a subpoena. Her energy utility had similar reservations.
One of the stumbling blocks mentioned in the Times article is that old-economy companies feel they play the role of a benevolent data owner that shares just enough data to be a little helpful. It turns out that consumers are also uncomfortable with the idea that their long-time vendors might be analyzing, categorizing, and sharing conclusions from their personal data.
But attitudes are changing for both consumers and corporate data collectors.
For example, many of us have probably engaged in on-line banking through third-party applications, using desktop software to pay bills and analyze spending trends. Recently my stodgy bank began to offer direct online bill paying—yours probably has done the same long before mine– and so I transitioned to their cloud-based software.
I lost some of the convenience of instant analysis that I had when I was accessing my data on mydesktop computer. But then I noticed the bank was adding modest features—alerts that could be configured when my balance reached certain limits. I suspect there’ll be more features and reporting capabilities in the near future in their cloud-based service.
And in the equally conservative credit card space, start-ups have emerged to analyze millions of transactions for fraudulent charges. The key innovation here was to borrow a cue from Amazon’s book reviews: crowdsource vendor evaluation based on feedback from the service’s subscribers. I count myself as a customer of one of these credit card fraud detection services. It was clear in the terms of service that I was allowing my credit card data to be used in a collective fashion to help spot fraudsters.
The key mindset change for companies is that they have to recognize that consumers own their data, and consumers must realize that they are granting access to their data with (hopefully) suitable guarantees of privacy.
Once these data ownership understandings are formalized and accepted by both parties, it won’t be long before consumers have their own Pop-Tarts realizations as they reap benefits from Big Data.
POSTED ON APRIL 23, 2013 BY SANDER DUIVESTEIN
“BIG DATA: A Revolution That Will Transform How We Live, Work, and Think,” is a revelatory exploration of the hottest trend in technology and the dramatic impact it will have on the economy, science, and society at large. Which paint color is most likely to tell you that a used car is in good shape? How can Con Edison catch the most dangerous New York City manholes before they explode? And how did YOU (well, Google) predict the spread of the H1N1 flu outbreak? The key to answering these questions, and many more, is big data, our newfound ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our newfound computing power to unearth revelations that we never could have seen before.
A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, especially the prospect of being penalized by for things we haven’t even done yet, based on big data’s ability to predict our future behavior.”
This is a presentation that McKinsey consultant, Tim McGuire, made at the recent Direct Marketing Association conference. It is very thought-provoking and inspiring one, because it is about practical value and applications of data. In direct marketing scoring models and regression analytics have been an approach any seriously result oriented marketing responsible has already tested. However, the availability of data and applications in the rich and influential online environment has exploded the value to completely new level.
Posted by CCGConsultingLLC in Current News, TechnologyI think there might be as many different predictions about the Internet of Things as there are bloggers and pundits. So I thought I would join the fray and give my take as well. The Internet of Things is that it is going to involve a new set of technologies that will enable us to get feedback from our local environment. That is going to allow for the introduction of a new set of tools and toys, some frivolous and some revolutionary.
I have read scores of articles talking about how this is going to change daily life for households. The day may come when our households resemble the Jetsons and where we have robots with more common sense than most of us running our households, but we are many years away from that.
There will be lots of new toys and gadgets that will sometimes make our daily lives easier. For instance food we buy may have little sensors put into packaging that will tell you when your produce is getting ready to go bad so that you won’t forget to eat it. There will be better robots that can vacuum the floors and maybe even do laundry and walk the dog. But I don’t see these as revolutionary and probably not affordable for the general populace for some time. For a long time the Internet of Things is going to create toys that wealthy people or tech geeks will play with, and it will take years to get these technologies to make it into everybody’s homes. Very little of what I have been reading for household use sounds revolutionary.
The biggest revolutionary change that will directly affect the average person is medical monitoring. Within a decade or two it will be routine to have sensors always tracking your vitals so that they will know there is something wrong with you before you do. There will be little sensors in your bloodstream looking for things like cancer cells, which is going to mean that we won’t have to worry about curing cancer, we’ll head it off before it gets started. This will revolutionize healthcare to be proactive and preventative and will eventually be affordable to all.
English: A technology roadmap of the Internet of Things. (Photo credit: Wikipedia)
I think the most immediate big benefactor of the Internet of Things is going to be at the industrial level. For instance, it is not hard to envision soil sensors that will tell the farmer the conditions of each part of his fields so that his smart tractor can fertilize or weed each section only as appropriate. There is already work going on to produce mini-sensors that can be sent underground into oil fields to give oil geologists the most accurate picture they have ever had of the underground topology. This will make it possible to extract a lot more oil and to do so more efficiently.
Small sensors will also make it a lot easier to manufacturer complex objects or complicated molecules. This could lead to the production of new polymers and materials that will be cheaper stronger and biodegradable. It will mean that medicines can be modified to interact with your specific DNA to avoid side effects. It means 3D printing that will feel like Star Trek replicators that will be able to combine complex molecules to make food and other objects.NASA has already undertaken a project to be able to print pizza as the first step towards being able to print food in space to enable long flights to Mars.
And a lot of what the Internet of Things might mean is a bit scary. Some high-end department stores already track customers with active cell phones to see exactly how they shop. But this is going to get far more personal and with face recognition software stores are going to know everything about how you shop. They will not just know what you buy, but what you looked atand thought about buying. And they will offer you instant on-site specials to get you to buy – ads that are aimed just at you, right where you are standing.
I remember reading a science fiction book once where the ads on the street changed for each person who walked by, and we are not that far away from that reality. There are already billboards in Japan that look at the demographics in front of them and which change the ads appropriately. Add facial recognition into that equation and they will move beyond showing ads aimed at middle-aged men and instead show an ad aimed directly at you. The Internet of Things is going to create a whole new set of attacks on privacy and as a society we will need to develop strategies and policies to protect ourselves against the onslaught of billions of sensors.
Probably one of the biggest uses of new sensors will be in energy management. And this will be done on the demand end rather than the supply end. Today we all have devices that use electricity continuously even when we aren’t using them. It may not seem like a lot of power to have lights on in an empty room or to have the water warm all of the time in an automatic coffee pot, but multiply these energy uses by millions and billions and it adds up to a lot of wasted power. You read today about the smart grid, which is an effort to be more efficient with electricity mostly on the demand side. But the real efficiencies will be gained when the devices in our life can act independently to minimize power usage.
Sensor technologies will be the heart of the Internet of Things and will be able to work on tasks that nobody wants to do. For instance, small nanobots that can metabolize or bind oil could be dispatched to an oil spill to quickly minimize environmental damage. The thousands of toxic waste dumps we have created on the planet can be restored by nanobots. Harvardhas been working on developing a robot bee and it is not hard to envision little flying robots that could be monitoring and protecting endangered species in the wild. We will eventually use these technologies to eat the excess carbon dioxide in our atmosphere and to terraform Mars with an oxygen atmosphere and water.
Many of the technologies involved will be revolutionary and they will spark new debates in areas like privacy and data security. Mistakes will be made and there will be horror stories of little sensors gone awry. Some of the security monitoring will be put to bad uses by repressive regimes. But the positive things that can come out of the Internet of Things make me very excited about the next few decades.
Of course there will be a lot of bandwidth needed. The amount of raw data we will be gathering will be swamp current bandwidth needs. We are going to need bandwidth everywhere from the City to the factory to the farm, and areas without bandwidth are going to be locked out of a lot more than just not being able to stream NetFlix. The kind of bandwidth we are going to need is going to require fiber and we need to keep pushing fiber out to where people play and work.
Brick-and-mortar retailers have long favored highly visible investments, such as advertising or store design over spending hard-earned income on back-office information technology. In fact, the retail industry devotes only about 1.7% of revenue to IT. Compare that with banking, which spends about 6%.
Big-box and boutique retailers alike see that e-commerce competitors continue to use technology as a means to win on price and selection, and know their customers increasingly use smartphones in-store to compare prices or search for deals.
IBM’s latest Big Data-based retail forecast suggests that some brick-and-mortar retailers are turning the tide against showrooming, a trend in which consumers look at items in a store before ultimately buying them online, usually at lower prices. In order to remain competitive and press their advantage further, brick-and-mortar stores must look to the cloud computing revolution as a way to upgrade their technology without busting their budgets.
Perhaps most important, clouds offer retailers a way to explore the potential of big data analytics to understand their customers better. In order to compete with e-tailers, retailers are tapping social networks to learn what customers are saying about them and about their competitors. Weather data is being used to influence product purchasing decisions, and merchandise promotions are organized around social events.
In many cases, brick-and-mortar retailers are even finding new data sources. Some companies are tracking movement of customers within stores and analyzing how many stop at displays to improve the effectiveness of merchandising. Others are considering installing license-plate cameras in parking lots to find out which customer is about to walk into the store.
All of these innovations make use of massive amounts of data. A cloud based solution, with elastic storage, computing and analytics capability, can make it economically viable for retailers as they dabble with these nascent approaches.
Cloud computing involves a new way of thinking about data. In a cloud, a single server can host many virtual servers, slashing hardware costs. The virtual servers can scale on demand depending on the need for computer capacity. That’s very useful for retailers, whose businesses are notoriously seasonal. Automatically expanding capacity on Black Friday, for example, can reduce lines at checkout counters and ensure quick service.
Further, the retail industry is aided by thousands of specialty software programs that are designed for various niches and needs. The average retail chain uses about 450 such applications — far more than most other industries. Naturally, those software programs get heavy use at certain times while they are shut down at others.
For instance, Planogram software, which lays out how boxes and cans are displayed on shelves, may only run once per month. Order entry systems run during the day and in the evening when shoppers are in stores and online. Inventory replenishment systems run full bore overnight. Frequently, each system is operated by a different part of the corporate organization. Managers order capacity based on the maximum use they anticipate for the system, knowing that it’s hard to expand later because of the need to authorize new capital budgets.
The result is that retailers use only about 10% to 15% of the computer capacity in their data centers. Some 85% is sitting idle at any time. Huge economies of scale could be gained by using the same infrastructure across multiple applications in a cloud-computing architecture.
Companies can either build private clouds in their own data centers, purchase dedicated private clouds hosted by infrastructure providers, or they can move their data and applications to a public cloud used by several different companies and run by infrastructure specialists.
Many companies choose to do both by using a hybrid cloud solution with some applications in the retailers’ own data center and others in the public cloud. In a public cloud, retailers only pay for the capacity they use, just like buying electricity from a public utility. Further, many retail applications can also be rented on a monthly basis as software-as-a-service.
As mobile, social and ecommerce continue to explode in popularity, traditional brick-and-mortar retailers must understand and harness the benefits of cloud computing to optimize the in-store experience, market to the individual and maximize every sale. If they don’t, they risk falling behind their competition.
Vish Ganapathy is the Director and Chief Technologist for IBM’s Global Retail business, and has more than 22 years of consulting experience working with retailers worldwide. Ganapathy particularly focuses on bridging software applications and technology that can enable retailers to differentiate themselves in the marketplace.
When we hear of mobile malware (especially on Android) growing 163 percent or infecting 32.8 million devices in 2012, it’s easy to understand why having a security strategy and solution for employee-owned devices is essential. However, what can sometimes get lost, especially for organizations looking to bolster their security posture, is how to prioritize security across your environment.
To be clear: establishing a perimeter defense in your network is important – very important. But if you’re a company that hasn’t already covered the basics, where should you begin? Many companies are now realizing that security is not just about holding the enemy at the gates, it’s also important to understand when the enemy is already within them. A good security posture starts by assuming you are compromised and then asking the hard questions: “Would I even know if I were compromised? What is the enemy doing? How can I stop them once they are inside?”
Security doesn’t start with BYOD – that’s just one aspect of a much larger picture. Should you really be focused on the doors to your house when the foundation is crumbling? Enterprise security shouldn’t be built like an M&M – crunchy on the outside, soft on the inside – it should be crafted more like a jawbreaker – hardened from the inside out. Of course, you want everything hardened, but you can’t tackle all aspects of your infrastructure at once. You need to prioritize based on risk and value. Attackers are after intellectual property and they have a particular appetite for credentials to help them come and go as they please. Build concentric circles of defense starting with your critical infrastructure, then extend to your application and database servers, and then encompass other sensitive systems like finance and your highest risk end-user systems (e.g., remote users, publicly accessible systems, etc.).
Also, what is a perimeter these days? When it comes to securing mobile devices and cloud computing, your corporate assets are being accessed from around the world, in Internet Cafes and homes, and by devices that don’t travel through any “known” perimeter (3G/LTE networks, etc.). Authors of advanced malware are currently targeting endpoints and servers with more regularity than mobile devices. Mobile attacks tend to be focused on small financial gains, not stealing intellectual property. So what we saw in the past with hackers changing dial-up modem settings to expensive toll lines and pocketing the cash, we now see with mobile hacking and expensive premium SMS messages; cybercrime – not cyberespionage.
Mobile devices still represent security vulnerabilities because of the unprotected credentials and company documents they store. The data on these mobile devices could always be used in more advanced attacks on desktops or servers in the future. So it should be part of your strategy to secure employee-owned devices that are not under your primary control. All I’m saying is start at the center where the data and systems are easily identifiable and there are proven technologies that exist to stop advanced threats from executing in your environment. As you extend your security layers, you will be left with a security posture that’s more sour than sweet for cyberattackers.
85 percent of us know that websites track their online shopping behavior, a new report from ecommerce optimization company Monetate says, and 75 percent of us want retailers to use our personal information to customize our shopping experiences.
That’s going back to the future, according to Monetate: going back to a time when all commerce was personal.
But there is a yin and a yang here.
While we may want personalized experiences, and we want websites to be smart — to know us, essentially, and act as an intelligent, solicitous person might — privacy is part of the picture. A good third of us don’t want our website activity tracked, and a quarter of us don’t want the websites we shop to personalize our experience at all.
Monetate has four tips for online retailers:
- Use marketing automation technology and big data to assist with personalization
- Target segments with relevant content based on what you know about them
- Don’t think of channels, think of customers first
- Be in it for the long haul, not the quick win
All the data, in visual form:
Customer is king. Always. Whether in B2B or B2C settings. With much writing this week on the importance of a Customer Centric approach where B2B organizations need to develop a much deeper understanding of the modern Customer Decision Journey.
Questions have been raised as per whether Multichannel Marketing Mix approaches have been based on the right models and research to measure results.
With the hype of a report to be issued by the Council for Research, currently investigating measurement issues related to digital video advertising, report that in turn will form the basis of an Advertising Research Foundation inquiry into the quality of the models.
“We believe it’s important to bring a combination of modeling, information and expertise to decisions “a P&G spokesman said in a statement to AdAge “We have clear evidence that marketing-mix modeling, combined with other information and expertise, has helped to improve return on investment of our marketing spending and media buying.”
Can big data really improve the customer experience with personalized ads, products and service offerings?
For certain big data can say a lot about preferences and even location. But with constantly increasing terabytes of data, in structured, semi structured and unstructured formats. To make sense of it all is to say the least challenging.
The more so for businesses, which do not have their own platform from which to gather this data, nor the technical tools or analyst expertise to navigate and make sense of data gathered from their websites, blogs and external social platforms.
What do you think?