Big data analytics is expected to grow to more than $100 billion by 2027 as companies become more reliant on data.
Big data has become big business, with companies of all sizes relying on the data they collect to tailor their services and gain a competitive advantage. As large as the industry has become, it’s poised to become much larger.
The global big data market is forecasted to grow to 103 billion U.S. dollars by 2027, more than double its expected market size in 2018. With a share of 45 percent, the software segment would become the large big data market segment by 2027.
China’s regulators may look to ban data-heavy companies from pursing IPOs in the US.
Like the US, China is looking to reign in the power and influence of its Big Tech firms. Companies with access to large quantities of data are particularly important to the country, and have already been pawns in the trade war between Beijing and Washington. TikTok is one example, with the US trying to force a sale under threat of ban, and China taking steps to restrict the export of the kind of algorithms TikTok relies on.
China’s latest move is in the form of proposed rules that would keep data-heavy companies from going public in the US, according to The Wall Street Journal. Such a move is sure to be unpopular with many companies looking to cash in on an IPO, but China clearly wants to keep what it considers to be sensitive technologies in-country.
It remains to be seen if there will be any retaliation or fallout from Washington.
Amazon is rolling out a sweeping monitoring program, with the goal of tracking the keystrokes and mouse clicks of its customer service staff.
In the era of Big Data, few companies have access to as much customer data as Amazon. The company controls the largest e-commerce platform, a line of popular security devices and, of course, the most popular cloud computing platform in the world. As a result, the company is a prime target for unscrupulous individuals looking to access that data.
According to a document seen by Motherboard, Amazon is preparing to roll out software designed to track customer service employees’ activity in an effort to prevent abuses from occurring. The company has already had instances where imposters have impersonated customer service staff and accessed information.
The company has looked at various solutions, including those that capture all keystrokes and mouse clicks. The one the company appears to be leaning toward focuses on capturing patterns instead, building a profile of how a person interacts with their workstation, via the keyboard and mouse. If someone else tries to use it, their usage would stand out as different from the established pattern, making it easy to spot an imposter.
“We have a security gap as we don’t have a reliable mechanism for verifying that users are who they claim they are,” reads the document.
The lengths to which Amazon is going illustrates the ongoing struggle companies have, and the solutions that will likely become more commonplace as threats continue to grow.
“Once you get to the cloud all of a sudden the lid is off,” says Snowflake CEO Frank Slootman. “People can just pursue their backlogs and whatever they can imagine. We’re now in a situation where technology is ahead of what people are capable of and imagining what they could actually do with it. That’s really a big part of what you see in Snowflake’s growth profile, a completely variable paradigm.”
Frank Slootman, CEO of Snowflake, says that on-premise data centers can only accommodate a tiny fraction of what their real demand for data analytics really is:
Once You Get To The Cloud The Lid Is Off
The important thing to understand is that there’s a couple of long-term secular trends that are coinciding and driving the development of the market overall. One is, as everybody knows, the movement towards cloud. It’s really a modernization play. We’re moving from on-premise data centers and we’re taking workloads to the cloud because we get to take advantage of better economics and utility models. Then we no longer have to manage capacity, we pay by the drink and all that sort of thing.
The other aspect that’s really important for our business is that we’ve had an extraordinary amount of pent up demand. The on-premise data centers could only accommodate a very tiny fraction of what their real demand for data analytics really is. Once you get to the cloud all of a sudden the lid is off. People can just pursue their backlogs and whatever they can imagine. We’re now in a situation where technology is ahead of what people are capable of and imagining what they could actually do with it. That’s really a big part of what you see in Snowflake’s growth profile, a completely variable paradigm.
Notion Of Headquarters Is Evaporating
We don’t have a yearning to go back to where we were. I can see why people would have that because of lockdowns and things of that sort. From a business standpoint, there’s a lot of positives to the shock to the system that we received. It’s almost like a wake-up call that is just opening our eyes to the opportunity. This whole notion that the office is your workday home we just realized that it’s nonsense. In other words, offices need to be there for specific purposes, for events, for training, for meetings specifically, but not a place to hang out nine to five. That’s definitely changing. It’s going to really reduce the real estate footprint that companies have.
The other trend and you’ve seen it with companies leaving California, the likes of Oracle and HP and Tesla, and so on is that the whole notion of headquarters is pretty much evaporating in front of our eyes. We’re no longer operating with a physical center of the universe. We’re completely virtual. We’re connecting as needed. We’ve been operating for the better part of a whole year without a headquarters and it’s just fine. All of a sudden everybody’s staring at each other and saying like what is the headquarters anyway. You’ve seen companies like Pinterest and you’re writing up massive leeches in San Francisco and saying we’re going to be headquarter-less. It’s just a concept whose time has gone away… and that’s very profound.
We Are Buying Talent And Technology, No M&A
Usually, big M&A is a function of people running out of market and running out of a lot of opportunity. They’re trying to invade adjacent territories to give themselves new runway. That is obviously not the case for Snowflake. We’re in a tremendous marketplace and we are buying talent and technology. We sometimes refer to it as stem cells that we can use that we don’t have ourselves that we can build very specific technologies around that are very much built snowflake way. We can really enable our platform mission or footer. That’s really been our mode. If you looked at our history we don’t have a history of doing big acquisitions.
Snowflake CEO Frank Slootman: Once You Get To The Cloud The Lid Is Off
Informally, Industrial Revolutions are referred to as Industry “Points O’s.” The First Industrial Revolution, or Industry 1.0, took place between 1760 and 1830, the second following up shortly after between 1870-1914. Between 1950-2002, the world underwent “digitalization” as a result of the Third Industrial Revolution, or Industry 3.0; and since 2011, we have been undergoing the Fourth Industrial Revolution, more commonly known as Industry 4.0. As a result of digitalization, data intelligence has been a primary driver in prospective industry revolutions.
As a result of Industry 1.0, machines and tools were able to replace animal and human labor. This was especially monumental for its time (1760-1830). How? The use of iron and steel for machinery began to skyrocket. As a result, working class citizens were able to create new resources, such as steam and internal combustion engines – which went on to drive a sector of the economy in itself.
Under Industry 2.0 (1870-1914), workers of the mass production industry saw many days of sunshine. For the first time, assembly line efficiency and productivity was lightened and shipping was made easier due to the invention of railways and telegraphs – another product of Industry 2.0. More along, new materials such as stainless steel and plastics were introduced as societal benefits.
Things got more technological under Industry 3.0 (1950-2002). The Third Industrial Revolution introduced electronics and IT, as well integrated them into manufacturing procedures. As a result, society saw a massive rise in telecommunications, computers, and even nuclear power. There was also a noteworthy widespread in factory automation, such as the incorporation of robots and PLCs to contribute to the general workflow.
Since 2011, interconnectivity has been the key focus. Already, Industry 4.0 is set to provide higher-level automation driven by artificial intelligence, as well as optimized manufacturing using real-time data and sensors. Additionally, this Industrial Revolution is focusing on a way to integrate cyber-physical systems throughout the supply chain.
In its outcome, Industry 4.0 will have used big data and machine learning to automate plants, warehouses, machines, and more. Furthermore, Industry 4.0 will have created smart machines that will be capable of collecting and analyzing data, as well as communicating the right information at the right time.
In other words, the Fourth Industrial Revolution will lay improvements across 3 new sectors: smart communication, data quality, and smart devices.
Smart communication allows manufacturers to rapidly respond to changing demand, inventory shortfalls, or equipment faults. Data Quality helps companies quickly locate problems so they can respond to them quicker. Additionally, data quality can be refined through organization-wide networks. Smart Devices create increasingly autonomous ecosystems that act as a catalyst for the future of the industry. Examples of these include driverless vehicles and drones. Driverless vehicles can navigate factories and warehouses, and drones can be used for maintenance and inventory management.
With that being said, business owners should seek insights on the ways they’re being impacted by Industry 4.0 In other words, this is a great time to prepare an effective data structure, focus on high-fidelity data creation and communication, standardardized business and data process, and understand your business’ use case. If even one important portion of the data is missing, it can break the digital thread – causing the flow of data to stop.
Is your data ready for Industry 4.0? Find out in the infographic below.
“Every company is going to need a Data Czar, a data leader, a Chief Data Officer, over time,” says Splunk CEO Doug Merritt. “One of the big points of digitization is you now get a bunch of data that you didn’t have before so that you can actually begin to act in real-time on these different signals. That needs somebody that understands data and guides data across an organization.”
Doug Merritt, CEO of Splunk, discusses how big data has spurred the need for every enterprise company is ultimately going to need a Data Czar:
Big Data Drives Society Forward
Almost everything in the world has got some type of WiFi or network connection so there is a ton of data that is flying around the stratosphere at this moment. The difficulty is being able to capture that data and begin to make sense of it so you can serve customers more effectively, reduce costs, optimize your supply chain, and hear signals from your employee base.
All the different capabilities that if you understand big data, and cloud certainly helps dramatically there, you can actually drive society forward. It’s what we call turning data into action, bringing data to every question, every decision, and ultimately into every action, so that we can keep our organizations and our society moving forward.
Every Company Needs A Data Czar
Every company is going to need a data Czar, a data leader, a Chief Data Officer, over time. One of the big points of digitization is you now get a bunch of data that you didn’t have before so that you can actually begin to act in real-time on these different signals. That needs somebody that understands data and guides data across an organization.
That pull from corporations is what pulls companies like Splunk and others forward to help the technical population within those organizations to actually make sense of data. We also help the sales, marketing, and finance departments, and any people in organizations that are leaning more heavily on data gathering and data science in making sense there.
Splunk CEO Doug Merritt: Every Company Needs A Data Czar
At Tech Day, China’s version of GM’s EV Day, GM has announced major advancements coming to its vehicles in China.
China is GM’s largest market. As a result, the company took the opportunity to outline major initiatives that it plans to bring to fruition in the Chinese market.
Among those advancements is 5G connectivity, which the company plans to implement in 2022. GM plans to have all Cadillac and most Chevrolet and Buick models connected by then, with connected services provided via over-the-air updates.
GM also plans for 40% of its new vehicle launches in China to be electrified models within the next five years. The company has already vowed to invest more than $20 billion in electric and automated vehicles by 2025. GM plans on bringing together 5G, AI, big data and smart cities to help make its plans a reality.
“As GM’s largest market and a global center of innovation, China will play a crucial role in making our vision a reality,” said Mary Barra, chairman and CEO of GM. “With our joint venture partner SAIC, we are blending global insights and scale with local market expertise to redefine what is possible for our customers and for society.”
A group of senators will introduce legislation to help protect consumer privacy as companies focus on using data to help combat COVID-19.
Governments and companies around the world have turned to big data in an effort to map the spread of the coronavirus, and try to get ahead of it. One of the most publicized efforts is being undertaken by Apple and Google, as the two companies work on a contact tracing API. The API, and subsequent apps, will use anonymous Bluetooth keys to keep track of the phones an individual has been in close proximity with. If a person tests positive, each person that has been in contact with them over the previous 14 days will be notified they have been exposed and need to quarantine.
Needless to say, many individuals have expressed concern over the privacy implications and, as a result, half of Americans have no intention of installing any contact tracing app.
To help ease concerns, and protect the privacy of Americans, Senators Roger Wicker, John Thune, Jerry Moran and Marsha Blackburn have announced their intention to introduce a data privacy bill. The goal is to provide much-needed transparency and give consumers a measure of control over how their data will be used, as well as hold businesses accountable for how they use it.
“While the severity of the COVID-19 health crisis cannot be overstated, individual privacy, even during times of crisis, remains critically important,” said Thune. “This bill strikes the right balance between innovation – allowing technology companies to continue their work toward developing platforms that could trace the virus and help flatten the curve and stop the spread – and maintaining privacy protections for U.S. citizens.”
Here’s to hoping the legislation will help prevent abuses of consumer data.
Verizon Media (formerly Yahoo) has announced it is using its open source, big data serving engine to combat the coronavirus.
The White Hose and research groups have released the COVID-19 Open Research Dataset (CORD-19), “a resource of over 51,000 scholarly articles, including over 40,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses.” Being able to access and use that gargantuan amount of data, however, can be a challenge of its own.
To assist in the endeavor, Verizon has announced it has indexed the dataset, making it available to search via Vespa.
“After being made aware of the COVID-19 Open Research Dataset Challenge (CORD-19), where AI experts have been asked to create text and data mining tools that can help the medical community, the Vespa team wanted to contribute,” writes Kristian Aune, Tech Product Manager, Verizon Media.
“Given our experience with big data at Yahoo (now Verizon Media) and creating Vespa (open source big data serving engine), we thought the best way to help was to index the dataset, which includes over 44,000 scholarly articles, and to make it available for searching via Vespa Cloud.”
Verizon’s announcement should be a boon to researchers and scientists trying to keep up with the latest research on the virus. The company promises daily updates to the documentation and query features. In the meantime, the dataset is live and ready for use.
“Now live at https://cord19.vespa.ai, you can get started with a few of the sample queries or for more advanced queries, visit CORD-19 API Query” the announcement continues. “Feel free to tweet us @vespaengine or submit an issue, if you have any questions or suggestions.”
Microsoft has announced a big win for its Azure cloud platform: a deal to host BlackRock’s Aladdin infrastructure on Azure.
Aladdin is an “end-to-end investment management and operations platform used by institutional investors including asset managers, pension funds, insurers and corporate treasurers.” By moving the infrastructure to Azure, BlackRock hopes to bring enhanced capabilities and an improved experience to its clients.
“As both a user and a provider of Aladdin, this decision reflects BlackRock’s ongoing commitment to continuous innovation and scalable operating solutions,” said Rob Goldstein, Chief Operating Officer of BlackRock. “Aladdin infrastructure deployed on Microsoft Azure’s cloud platform will provide BlackRock with enhanced capabilities to deliver the best outcomes for our Aladdin clients.”
“By bringing Aladdin to the cloud, Microsoft will support BlackRock in further enhancing its client experience while also enabling continuous innovation in the financial services industry,” said Judson Althoff, executive vice president of Microsoft’s Worldwide Commercial Business. “Together, we will empower an ecosystem of financial services customers running their most critical workloads in the cloud.”
The two companies are committed to working together to further sustainability through the use of big data, machine learning and artificial intelligence. The deal is a big win for Microsoft, and will likely help it move further into the financial services industry.
In an effort to get ahead of the corona virus, China is turning to big data and artificial intelligence to help identify those infected.
According to the International Business Times (IBT), “several Chinese tech firms have developed apps to help people check if they have taken the same flight or train as confirmed virus patients, scraping data from lists published by state media.” The data is also giving officials the ability to track down individuals who may have been exposed, screen them and forecast how the disease will spread.
Baidu developed a system that uses infrared and AI-powered facial recognition to screen people at the railway station for a possible fever. Anyone with a temperature 99 degrees Fahrenheit or above is flagged for further checks. IBT reports that the “system can check more than 200 people a minute, far faster than the thermal scanners used at airports.”
Companies are also developing ways to both prevent the spread of the disease, as well as help those already infected. Some cities are using robots to scold people who are not wearing masks in public, while other companies are working on using drones to deliver medical supplies to the sick.
As China continues to struggle with the deadly outbreak, technology may well be the key to turning the tide.
“What Fungible is set to do is to revolutionize the economics, the reliability, and the performance, of data centers at all scales and in all geographies,” says Fungible CEO Pradeep Sindhu. “The reason that it is time to do this is because of some of the really important trends that have been happening over the last 15 to 20 years. There is, of course, the flattening of Moore’s Law. There is the hyper-connectivity that the internet has brought. Then there’s big data. The confluence of these three things is bringing us to a data-centric world.”
The Confluence of These 3 Things is Bringing Us To a Data-Centric World
What Fungible is set to do is to revolutionize the economics, the reliability, and the performance, of data centers at all scales and in all geographies. The reason that it is time to do this is because of some of the really important trends that have been happening over the last 15 to 20 years. There is, of course, the flattening of Moore’s Law. There is the hyper-connectivity that the internet has brought. Then there’s big data.
The confluence of these three things is bringing us to a data-centric world. It is time now to invent a new kind of microprocessor and this is exactly what we are doing. We’re inventing something called the DPU to improve the economics and reliability and performance of data centers. That’s what Fungible is doing.
In Five Years 90 Percent of All Servers Will Have DPUs Inside
Many, if not most, new applications are data-centric in that the amount of data that they ingest and they process is very large. As a result of this change in application, there’s a new workload that we call data-centric. In fact, the change that we see happening in data centers will happen in the redefinition of what we call a server. In five years we expect 90 plus percent of all servers to have DPU’s inside.
It will reflect in the way in which the networks are put together inside datacenter buildings. They’ll be much flatter, much faster, much lower latency, and with much more predictable latency. The DPU will enable that. Finally, the global architecture of the way data centers are built in the future will include Edge Datacenters in addition to these massively scalable data centers. The DPU is said to play a very important role in all three areas.
It’s not a zero-sum game because of the emergence of this new kind of workload, which has been building now for 30 years. There’s been some 600 X change increase in the ratio of I/O to compute. This demands the invention of a new kind of microprocessor. We don’t have any direct head-to-head competition. We will work in a manner which is completely complementary to the existing two kinds of microprocessors which is Intel x86 and GPUs built by Nvidia. The DPU will be the third kind of microprocessor inside data centers.
The Confluence of These 3 Things is Bringing Us To a Data-Centric World, Says Fungible CEO Pradeep Sindhu
“Our acquisition of Dynamic Yield has brought us a lot of excitement,” says McDonald’s CEO Steve Easterbrook. “Very simply put, in the online world when we’re shopping and we pick an item and put it into our shopping basket, any website will automatically suggest two or three things to go along with it. We’re the first business that we’re aware of that can bring that into the physical world. It’s really just taking data and machine learning and AI, all these sorts of technical capabilities.”
Steve Easterbrook, CEO of McDonald’s, discusses how the company is using technology to elevate the customer experience and accelerate growth in an interview on CNBC:
Continue To See How We Can Elevate the Customer Experience
As we’ve executed the growth plan we’ve spent the first two years, three or four years ago, turning the business around. Now we’ve had a couple of years of growth. We’re confident now that we’re beginning to identify further opportunities to further accelerate growth. That takes a little bit of research and development cost. It means you’ve got to bring some expertise into the business to help us do that. We’re still managing to effectively run the business. G&A is staying the same and we’re putting a little bit more into innovation.
We continue to see how can we help continue to elevate the experience for customers. With this pace of change in the world and with different technology and different innovations, whether it’s around food, technology, or design, we’re seeing opportunities that we think can either make the experience more fun and enjoyable or smoother for customers. If we can find that we’re going to go hard at it.
We need to continue growing. If where we are investing that money is helping drive growth across 38,000 restaurants then I think the shareholders and investors would be satisfied. We want to bring our owner-operators along with us as well. They’re investing their hard-earned dollars so that always means we got a business case. The owner-operators will want to see a return on their investment just the same as a shareholder would. We’ve got a wonderful check and balance in the system to help us make sure we spend that innovative money in the right way.
Using Data, Machine Learning, and AI to Accelerate Growth
Our acquisition of Dynamic Yield has brought us a lot of excitement. It was our first acquisition for 20 years. It was an acquisition in a way that was different from the past. It wasn’t looking at different restaurant businesses to try and expand our footprint. It’s bringing a capability, an IP and some talent, into our business that can help us accelerate the growth model. We completed the deal mid-April and within two weeks we had that technical capability in 800 drive-throughs here in the U.S. It’s a very rapid execution and implementation.
Very simply put, in the online world when we’re shopping and we pick an item and put it into our shopping basket, any website we’re on these days will automatically suggest two or three things to go along with it. People who buy that tend to like these things as well. We’re the first business that we’re aware of that can bring that into the physical world. As customers are at the menu board, maybe they’re ordering a coffee and we can suggest a dessert or they’re ordering a quarter pounder with cheese and we can suggest making that into a meal. It’s really just taking data and machine learning and AI, all these sorts of technical capabilities.
Mining All of the Data Will Improve the Business
The best benefit for customers is we’re more likely to suggest things they do want and less likely to suggest things they don’t. It’ll just be a nicer experience for the customer. But yes, for the restaurant itself, because we can put our drive-thru service lines in there, for example, the technical capability by mining all of the data will be to suggest items are easier to make at our busier times. That’ll help smooth the operation as well. The immediate result will be some ticket (increases). But frankly, if the overall experience is better customers come back more often. That’s ultimately where the success will be, driving repeat visits and getting people back more often.
Across the entire sector, traffic is tight right now and people are eating out less. They have been progressively eating out less for a number of years. Whether it’s the advent of home delivery, for example, which is something we participate in, but at the moment it’s just a little bit tight out there. It’s a fight for market share. Anyone who is getting growth, typically it’s because they’re adding new units. People are finding it hard to (increase) guest count growth. It’s something that we have stated as an ambition of ours. We think that’s a measure of the true health of the business. Last quarter, we did grow traffic and we’ve grown traffic for the last couple of years, but only modestly. We want to be stronger than that.
How McDonald’s Is Using Data, Machine Learning, and AI to Accelerate Growth
Hewlett Packard Enterprise and Cray have announced that the companies have entered into a definitive agreement under which HPE will acquire Cray for $35.00 per share in cash, in a transaction valued at approximately $1.3 billion, net of cash. “The main reason why we decided to pursue this acquisition is that the data around us is exploding,” Says HPE CEO Antonio Neri. “That data has value and the need to process that data faster continues to grow.”
Reason For Acquiring Cray – Data Around Us is Exploding
I’m super excited about the announcement today. The main reason why we decided to pursue this acquisition is that the data around us is exploding. That data has value and the need to process that data faster continues to grow. The need for high-performance computing is one element of processing that data faster. The combination of great technologies with Hewlett Packard Enterprise portfolio, which include both HPE Apollo and SGI, give us a unique set of capabilities to get us to the right business outcome from the data. What we are talking about is (improved outcomes) for machine learning, AI, as well as big data and intensive workloads. Cray brings these capabilities.
Cray has two-thirds of its business coming from the government side and one-third from the commercial side. Hewlett Packard Enterprise is the opposite with two-thirds from the commercial side and one-third from the government side. Obviously, the government has already requested for Cray to build Exascale computing. That’s on the basis of the foundation technologies that Cray has developed for some time which is what we call the interconnect fabric. For us, that level of innovation is important to scale our portfolio and continue to enter new markets like oil and gas, manufacturing, as well as academia.
Thirteen Acquisitions Under CEO – All Very Successful
I have done now thirteen acquisitions with this one. We have had an incredible discipline based on return on invested capital where we have acquired (important) intellectual property as well as bringing talent to the organization. Each of them has been very successful including Aruba Networks as well as what I call the SGI acquisition, Nimble Storage, and so forth. They have all been very successful.
When you think about the type of business it has obviously been a little bit lumpy on the Cray side but that’s because it takes time to build the systems with CAPEX upfront and then acceptance for the backend to recognize revenue. We believe the combinational of Cray added to our scale which is significantly larger will smooth the transition from the revenue profit perspective. It will also limit the CAPEX investment because both companies have similar capabilities and now we can use both in a scalable way that we couldn’t do before.
HPE CEO Antonio Neri: Reason For Acquiring Cray – Data Around Us is Exploding
Levi Strauss began trading on the New York Stock Exchange this morning under the ticker symbol ‘LEVI.’ By mid-afternoon, the stock was at $22.66, substantially higher than the price offered to institutional investors. It’s clear that investors believe that Levi’s can leverage technology and innovation to successfully compete online and in brick and mortar stores.
Levi Strauss Soars in NYSE Debut
Charles Bergh, CEO of Levi Strauss, discusses how technology and innovation are driving increased sales and market share in an interview with CNBC coinciding with their IPO:
We Are Denim and We’re the Market Leader Globally
We are denim and we’re the market leader globally. A lot of people as we were doing the (IPO) roadshow said aren’t you guys just riding the denim wave? We’re creating the denim wave. We’ve been driving the category with innovation across our men’s business and our women’s business. We’ve expanded to other categories. Last year we finished with 14 percent growth coming off of 8 percent growth the prior year. The business is really humming right now.
I believe this is sustainable for the long term. Maybe not double digits forever. But we’ve got clear runway for growth across the categories that we’re competing in. We’re building share in our core categories and expanding to new categories. Last fiscal year, when we finished the year our growth was really broad-based. If you looked at it in the categories where we competed we grew every single category. If you looked at it by geography we grew every single geography. If you look at it by channel we grew across wholesale, including US wholesale, which is a little bit of a melting iceberg right now. We grew in our own brick-and-mortar and ecommerce. It was very broad-based growth last year and we’re confident we can continue that.
We Have Built a Very Big Platform for Big Data
First of all, to be successful it does come down to strong brands. Consumers at the end of the day love an emotional attachment with their brand. We’ve recreated that that love for Levi’s. We have built a very big platform for big data. In fact just a couple of weeks ago we announced that we’ve hired a head of advanced analytics and machine learning who will sit on the executive team and report directly to me. We are mining the data that we do collect and really turning it into revenue.
Our strategies are working and one of the key strategic choices that we made seven years ago, shortly after I joined, was to become a leading world-class omnichannel retailer and it is working. The mix has shifted to omnichannel. When I joined the company it was about 20 percent of our business. Today, it’s almost a third. It is faster growing than our wholesale business and we’re continuing to invest in it. Most of our capital investment is going into retail and ecommerce and knitting that seamless consumer experience together.
Implemented New Instance of SAP and Investing in RFID
It (IPO funds) is going to go into continued investment in building out our omnichannel. So both brick-and-mortar retail as well as our ecommerce business and then knitting it together with technology. For example, we’re implementing a new instance of SAP and investing in RFID (radio frequency identification). We’ve implemented RFID across our business in the US and UK and that’s actually really turning into money. Every one of the products in our store is tagged with RFID.
I’ve actually had this experience happen to me myself in our new Times Square store. There was an item I wanted to buy and they didn’t have it in my size. A stylist came over and scanned the tag and she could see that my size was available in the back room. Just two minutes later I was in the dressing room trying it on. A year ago before our RFID that would have been a lost sale. That just wouldn’t have happened. It gives us instant clear visibility to the inventory in our store, both in front of house as well as back of house.
Levi’s Driving Market Share Through Product Innovation
Back in 2013 and 2014, the headlines were the death of denim. It was all about athletic tights and Lululemon tights. It became a throwdown moment for us as a company. We have an innovation center a couple of blocks from our office. We brought our suppliers, the mills that make denim for us, into that innovation center. We understood what women were really telling us by wearing tights. That used to be a denim occasion. They wanted soft stretchy comfortable material that made them look great and gave them confidence. That was what was driving that conversion. So we innovated around soft stretchy comfortable denim which we can now do. We developed proprietary four-way stretch so that women don’t get baggy knees, which is their biggest dissatisfier.
We relaunched our business in the middle of 2015 and we’ve grown 14 quarters in a row and in the last eight quarters at double-digit rates. It has been a huge part of our growth. We were under $800 million just on women’s bottoms about three years ago. We’re over a billion dollars today. We are number one globally with a nine percent market share, but we’re not number one in a number of markets including right here in the US. So I really do believe we can continue to grow at an accelerated rate on our women’s business. There are lots of what I like to call share donors out there for us to build share while we’re building the category.
We haven’t seen any (backlash to being an American brand). This brand stands for everything good about America. Freedom, democracy, and allowing people to express themselves. Authentic self-expression is what the Levi’s brand is all about. We’ve not seen any backlash. None. We think there are lots of opportunities still for us. I am not worried at all about denim. We are denim and we’ll continue to drive this category through great innovation and marketing that connects with consumers and sends them into our stores.
Technology and Innovation Powering Levi Strauss Growth Strategy
Starbucks has dramatically increased the use of AI-powered customer insights to drive growth, says Starbucks CEO Kevin Johnson. During the most recent holiday season, Starbucks made data-driven decisions on a variety of items from the type of holiday cups they were offering to how they promoted gift cards, all designed to increase sales. Johnson credits these new customer insights for improving gift card sales by four percent over last years holiday period.
Kevin Johnson, CEO of Starbucks, discussed in an interview on CNBC how analytics, artificial intelligence, personalization, and technology are now driving marketing, sales, and business decisions:
AI is Making Us a Better Company
We have dramatically stepped up the focus on customer insight. We are using technology to help inform us of what customers want, what they need, and what they think of Starbucks. That informed our entire holiday plan this year, and we had a fantastic holiday.
We are driving much more use of analytics, artificial intelligence, personalization, and technology to help us be more informed and more connected to our customers. That is making us a better company.
Customer Insights Driving Starbucks Growth
I’ll frame it around customer insights. Coming out of last year’s holiday we used a number of tools and research to give us customer insights on what customers really appreciated and loved about Starbucks at the holiday. That informed everything from the design of our cups to utilizing the reusable red cup promotion that we launched. We saw gift card sales grow four percent year-on-year in the quarter.
That was a function of customer insight and research that we did. This holiday, in many ways, was informed by that insight. That’s just an example of what we’re doing. We’re using all kinds of data, customer focus groups, and things to help us be more informed and more front-footed on the trends and the things that customers really want to see from Starbucks.
When you think of Facebook, you think of data, but not so much technology. Get ready for an in-depth preview of how Facebook is and is further planning to use artificial intelligence and other key technologies that they see as critical to their future.
“Facebook’s long-term roadmap is focused on building foundational technologies in three areas: connectivity, artificial intelligence and virtual reality,” wrote Mike Schroepfer, Facebook’s Chief Technology Officer. “We believe that major research and engineering breakthroughs in each of these areas will help us make more progress toward opening the world to everyone over the next decade.”
Facebook Making AI Research Useful Now
Tying all of these crucial technology projects together is AI. “We’re conducting industry-leading research to help drive advancements in AI disciplines like computer vision, language understanding and machine learning,” he says. “We then use this research to build infrastructure that anyone at Facebook can use to build new products and services. We’re also applying AI to help solve longer-term challenges as we push forward in the fields of connectivity and VR. And to accelerate the impact of AI, we’re tackling the furthest frontiers of research, such as teaching computers to learn like humans do — by observing the world.”
Facebook has learned to quickly turn their AI research into productive uses by their development and production teams. “As the field of AI advances quickly, we’re turning the latest research breakthroughs into tools, platforms and infrastructure that make it possible for anyone at Facebook to use AI in the things they build,” said Schroepfer.
The backbone of their AI product development is FBLearner Flow, which allows their coders to easily reuse algorithms across products. Also, very importantly considering the billions using the Facebook platform, it lets their developers run thousands of experiments to test scaling.
Another advancement is AutoML, which according to Facebook automatically applies the results of each test to other machine learning models to make them better. This significantly improves the time to market on AI breakthroughs.
A brand new product that they developed based on their AI research is Lumos, a self-serve platform that enables teams that haven’t been exposed to the technology a way to “harness the power of computer vision” for their products and services.
How is AI Impacting Facebook’s Users?
Facebook is quickly and sometimes quietly adding AI capabilities right into the products that Facebook users love. For instance, AI is used to help translate posts automatically from foreign language speaking friends. It also behind the one time controversial ranking of everyone’s News Feed. Remember when this used to be in chronological order?
Facebook says that over the next 3-5 years AI will be used in features all across the platform.
AI Being Used to Improve Aspects of Video
Facebook sees video communication as its future and is working on ways to use AI to improve this experience.
“We started working on style transfer, a technology that can learn the artistic style of a painting and then apply that style to every frame of a video,” said Schroepfer. “This is a technically difficult trick to pull off, normally requiring that the video content be sent to data centers for the pixels to be analyzed and processed by AI running on big-compute servers. But the time required for data transfer and processing made for a slower experience. Not ideal for letting people share fun content in the moment.”
“Just three months ago we set out to do something nobody else had done before: ship AI-based style transfer running live, in real time, on mobile devices,” he added. “This was a major engineering challenge, as we needed to design software that could run high-powered computing operations on a device with unique resource constraints in areas like power, memory and compute capability.”
All of this work has resulted in a new deep learning platform called Caffe2Go, which can capture, analyze and process pixels in real time on a mobile device, according to Facebook.
“We found that by condensing the size of the AI model used to process images and videos by 100x, we’re able to run deep neural networks with high efficiency on both iOS and Android. This is all happening in the palm of your hand, so you can apply styles to videos as you’re taking them.”
“Half the money I spend on advertising is wasted; the trouble is I don’t know which half,” said marketing pioneer John Wanamaker in the early 1900’s. That is why CRM software was invented and why it is used by every serious marketer. In today’s “Big Data” World, enterprises are making not just marketing decisions, but almost ALL decisions based on data analytics.
“Big Data holds the potential to describe target customers with an accuracy and level of detail unfathomable only a decade ago,” said Jean Spencer on the SalesForce blog, who is a Product Marketing Manager at Microsoft and was previously the content marketing manager at Kapost. “While old-school marketing efforts were limited to things like tracking returns on direct mail campaigns, or number of subscribers to newsletters, modern marketers can have data on people’s exercise habits, digital clicking behavior, time spent on various sites, purchasing history, personal preferences based on social media postings, time awake, time spent in the car, caloric intake, and almost anything else you can imagine.”
SalesForce is at the epicenter of data, marketing and sales. They offer this overview of the concept:
Using Data To Make Better Marketing Decisions
A report by the Aberdeen Group says that 44 percent of executives are dissatisfied with the analytic capabilities available to them and that they often make critical decisions based on inaccurate or inadequate data. That was in 2014 and fortunately CRM has improved dramatically since then and executives are now typically integrating CRM solutions into their marketing platforms.
“No longer do we rely on conclusions based on vague and imprecise relationships such as “we advertised last week and sales increased so it must have worked” or the common one that I’ve heard many times, “the objective was awareness and clearly many people are now aware of us”, said Gerald Chait who is Director/CEO of Marketing By Objectives. “In today’s world, this just does not cut it anymore.”
Chait added in a blog post, “Gone are the days when we would define roughly segmented target audiences and place an ad hoping someone would purchase something. Today’s marketing enables us to identify who to work with to make a sale, right down to the individual level. What’s more, we can personalize and customize our advertising and messaging to each specific person, no matter how many people there are. We can even customise and personalize website pages depending on who’s viewing them.”
It’s often referred to as predictive marketing, gathering data to learn what is working and what isn’t using precise analytical strategies and technologies in order to finely tune your marketing.
“Predictive marketing is the application of predictive technology to the entire marketing process, across the entire buyer’s journey, and across every channel of communication,” says Eli Snyder, Associate Technology Director of Strategy at Intelligent Demand. “It means not only having predictive insight into the future through predictive analytics, but also using that insight to make better decisions about who and how to engage, and then build better content, campaigns and programs.”
“In order to execute your marketing strategy in the most effective way, you’ll need your business management platform (or CRM) and marketing automation tools to work together seamlessly; using one to generate leads, and the other to maintain them, so you can get a complete picture of your business,” said Mark Sokol who is the VP of Product Marketing and Branding at ConnectWise.
The Intersection of Marketing & CRM is Leads
CRM and marketing are now tightly integrated in order to make marketing more efficient and and successful. “In the past, the marketing campaign stops here in the CRM software system and the rest is carried out externally,” said Denise Holland, VP & Senior Analyst of Genesys Advisory in the CRMsearch blog. “In today’s world, the right customer relationship management system can create the message, compile your target list, distribute your messaging pursuant to an automated schedule, capture the replies and inquiries from these marketing placements, route them to the right sales person or department, track the sale opportunity progress, record the successful sale event and calculate the campaign ROI.”
“This CRM system can also advise the best time to call or email your customers, what type of messaging will illicit the best response, if your customer is really serious or just shopping around, how you can improve your products and services, and what new products and services your R&D department should focus on next,” he says.
“CRM has one common component to help you make marketing decisions, Leads, says Joe CRM on the PowerObjects blog. “Lead data allows you to gauge how healthy your marketing is, what works and what doesn’t, and lets you understand lead quality. In today’s post, we’ll provide some lead data sources from CRM you can use to help make marketing decisions.”
Joe at PowerObjects says you need to know where your leads are coming from. “Some examples of lead sources include outbound cold calls, email, chat, website form submission, and events,” he said. “Keeping the lead source simple lets you use a different field, source campaign, to describe the lead source in more detail as needed.”
He says that knowing where leads come from drives marketing decisions such as:
Number of employees needed for the inside sales team
Budget disbursement for paid advertising
Landing page success
P&L for events attended
Create a Data-Driven Culture
“To cultivate a data-driven culture within your organization, it’s important to remember that without data, you’re simply another person with an opinion,” commented MeetMe CTO Jonah Harris on the NGDATA blog. “All too often, with valuable data and insights in hand, people remain invested in their own hunches and intuition.”
“Transitioning to a genuine data-driven culture is a challenge for many organizations, but one of the ideal first steps is to start leveraging the data your business has to guide evidence-based decision making,” added Vaclav Shatillo of Business Intelligence at Clutch. “When data reinforces or, better yet, contradicts the gut feeling, the conversation around the importance of a data-driven approach is bound to begin.”
At what frequency the data is needed to make actionable decision, and
How to package the data so it can be easily digested, analyzed and reacted to.
Find other great advice from a variety of experts quoted about how to create a data-driven culture here.
Darren Catalano, the CEO of HelioCampus offers some great tips on building a data-driven culture that can be applied to any business:
Data is Marketing Gold
“Data isn’t an overwhelming set of facts and figures,” said Megan Totka is the Marketing Director for ChamberofCommerce.com. “It’s marketing gold. It shows you what your customers want and how to get your customers to buy from you.”
Joe CRM says that the “data you receive from leads that turn into opportunities and then end up as customers is a goldmine.” He says, “This data alone can give your company direction and help you find your niche. That’s why when you use your closed as won accounts it should be for a macro view of your marketing processes. This is the data executives want to see from marketing because it helps prove ROI or that the money spent was worthwhile.”
Data that can power your successful marketing strategy is sometimes found in places that you don’t expect. “New marketing technology, measurement platforms and other advances have greatly expanded the sources that marketers can sift through for nuggets of information,” said Eva Rohrmann, the director of solutions and customer lifecycle marketing for PR Newswire. ”
Rohrmann says that the “most useful data that will turn strategic, positioning and tactical efforts into gold oftentimes is hiding right under your nose: with other teams within your organization.” She believes that ideas and data are “streaming” from many directions, “from sales to product to customer support.”
“Every team within your organization has a treasure trove of actionable marketing intelligence waiting to be discovered,” she says.
The marketing landscape is changing and that should make every CMO’s job easier because they are using justifiable logic instead of just gut intuition. In order for a company to reach their maximum sales potential they must utilize data-driven CRM strategies.
“Marketing is currently undergoing a metamorphosis from a once qualitatively measured art towards a quantitatively driven science,” said Eamonn O’Raghallaigh, the Managing Director of Digital Strategy. on the company’s blog. “This paradigm shift will indeed lead to significant impacts on the competitive landscape; with the bias towards companies who adopt and embrace a data-centric culture within their organization.”
It’s not news that spam plagues social media, but Networked Insights (via Marketing Land) recently put out some research looking into how it affects brands, and the conclusion is that data is pretty “dirty”.
According to the report, 9% of all Twitter users who tweet in English are non-consumers. That’s not just spammers, but includes bots, celebrities, brand handles, and inactive accounts. Spam is a bigger problem on blogs and forums, where 28% of all posts are written by non-consumers, it finds. Still, over 90% of social media posts in conversations around some brands are classified as spam.
Brands today are becoming more sophisticated about analyzing social media to discover consumer insights. But, if social data is filled with spam, brands’ analyses will not be accurate or actionable,” the report says. “The industry recognizes data is inherently dirty. According to a recent New York Times article, 50% to 80% of a data scientist’s time now involves cleaning data. Efforts are being made to clean up social spam, but it’s an uphill battle. Twitter is actively finding and removing social bots, But, according to the Wall Street Journal, the black market is able to create fake accounts quicker than Twitter can remove them.”
The report defines social spam as including tweets, reviews, or blog comments, which contain coupons, product listings, contests/giveaways, adult content, or general spam, which may contain “gibberish or nonsense”.
Older forms of social media like forums and blogs are still the heaviest sources of social spam, based on the report’s findings.
Different categories have different percentages of spam posts, with the most appearing for the shopping (13%), finance (11%), and technology (10%) categories compared to real estate (7%), automotive (6%), pets (6%), sports (1%), science (1%), and religion (1%).
“There are branded posts and conversations about brand names happening across social media all the time,” the report says. “Although overall spam rates are less than 10% across social media platforms, conversations for some brands are dominated by spam.”
Elizabeth Arden and Rite Aid are among the brands being dominated by spam, each with 95% of posts about them falling under the label. Other troubled brands include Visa (81%), MasterCard (76%), Ulta (75%), American Eagle Outfitters (73%), Best Buy (72%), Fisher-Price (70%), Lancome (68%), and Victorinox (68%).
The main takeaway from the report is that when you detect and remove all the spam from brand conversations, the conversations look very different. For example, when they removed the spam from the food and drink category, they found “more nuanced conversations” about healthy food, food cravings, etc. This would enable brands to better interpret what consumers are really talking about.
Once you’re able to eliminate (or at least cut drastically) the spam noise out of the data, you can focus on legitimate data, which you can then use to personalize your marketing, which is key to increasing brand loyalty.
Infogroup has a new study out, which reports that 47% of marketers are seeing a return on their big data investments.
The study is based on a survey of nearly 600 marketers, and found that while over half of them express optimism about personalized marketing during this year, they’re not so confident in the accuracy and completeness of their consumer data.
15% of them said their biggest challenge in 2015 is collecting data, while 21% say analyzing data is their biggest challenge. Over half primarily rely on high-level forms of personalization for campaigns.
According to the report, 53% of marketers “crave more information on their customers,” while just 10% think they collect too much data. Over a third say they collect the right amount.
“The findings come as investment in data-driven marketing reaches a tipping point,” says Infogroup. “More than three out of five companies (62 percent) have started investing in data marketing solutions. Investment in data-as-a-service or software-as-a-service (DaaS or SaasS) is up from 54 percent in 2013. And almost half of brands (47 percent) are already seeing a positive return on data-related investments, with another 15 percent expecting to see a payoff for the first time in 2015 – meaning the majority of marketers will be seeing ROI this year.”
As the firm notes, its study suggests marketers understand that the data they have doesn’t provide the complete picture about customers.
“Although data-driven marketing is now the norm, marketers still thirst for more data,” said Infogroup president Gretchen Littlefield. “Even as they invest in DaaS and Saas and execute more sophisticated multi-channel campaigns, brands are seeking to continually deepen their understanding of customers by acquiring more meaningful data from multiple sources.”
The study found that just 21% of marketers are “very confident” in the accuracy and completeness of their customer profiles. 16% said data application will be their biggest data challenge this year.
Customer purchase history and third-party lists are the data sources marketers are relying on the most at 48% and 44% respectively. Web browsing history and social media posts are much lower at 16% and 12%.
Most (55%) marketers primarily rely on names to personalize campaigns, it found. 53% rely on demographic info. Less than a third use consumer interests, transaction and event triggers, or consumer interactions with brands.
Infogroup asked survey participants what stands in the way of implementing personalized campaigns. 40% blamed difficultly integrating across channels, while 35% said lack of quality customer data for segmentation, and 32% said fragmented systems.
While he was writing specifically about Facebook, James Whatley, the social media director at Ogilvy & Mather Advertising, London, recently wrote, “Forget about big data. 2015 is about smart data.”
“The thing that continuously blows minds is just how niche you can get with that detail,” he said. “In the autumn of 2014, one enterprising data monkey even managed to get his targeting so perfect that he set about specifically serving ads to his roommate as part of an elaborate prank. That’s mind blowing. In 2015, it would be great if the creative industries could get familiar with the smart data available to them.”
While less than half of marketers may be seeing a return on their big data investments, perhaps Watley is on to something with his smart data remarks. Read our conversation with him here.
Netflix is just getting started with this whole original movies thing.
Sure, the once-DVD delivery company and future king of streaming has produced successful TV series like House of Cards and Orange Is The New Black. It’s also produced award-winning documentaries. But I’m sure Netflix would be the first to admit – fictional movies are an entirely different beast.
Earlier this week, Netflix announced its first-ever original feature film – a sequel to Ang Lee’s 2000 film Crouching Tiger, Hidden Dragon. It’ll be called Crouching Tiger, Hidden Dragon: The Green Legend and will land on Netflix and (some) IMAX screens in August of next year. On the heels of that announcement, Netflix made a somewhat more surprising and no doubt polarizing decision. For its second foray into filmmaking, with all eyes fixated on its every move, Netflix struck a huge, multi-year deal with…
Netflix had to have known that this would elicit this type of feedback – at least from a decent swath. The past, well, decade or so of Adam Sandler productions have been less than inspiring. Despite what you think of Jack & Jill, however, do note that Adam Sandler movies continue to perform at the box office – at least on the whole. Adam Sandler is a nearly $4 billion box office commodity.
But that’s only a small, and I’ll say much less significant factor in Netflix’s decision to sign up for four (count ’em, four) original Happy Madison productions.
The reason Netflix inked this deal, for an Adam Sandler movie a year for four years, is because it knows you’re going to watch them. It knows you’re going to watch them because Netflix has been compiling data on your viewing habits since day one. It’s how it knew you’d lose your shit over House of Cards. It’s how it knew you would tell all of your friends that they just had to watch Orange Is The New Black.
And it’s how it knows you’ll watch Adam Sandler.
“They’re so repeatable,” Netflix Chief Content Officer Ted Sarandos says of Adam Sandler movies. “What we’ve seen is the more international we have become, the data has reinforced the incredible global strength of Adam.”
Sarandos says that Adam Sandler is one of the most-viewed actors on Netflix. Globally.
What do you bet Crouching Tiger, Hidden Dragon is super popular on Netflix?
“We know what people watch on Netflix and we’re able with a high degree of confidence to understand how big a likely audience is for a given show based on people’s viewing habits,” Netflix communications director Jonathan Friedland told Wired nearly two years ago. “We want to continue to have something for everybody. But as time goes on, we get better at selecting what that something for everybody is that gets high engagement.”
Netflix knows you. And it wouldn’t make a deal like this without some a ton of evidence suggesting that people will watch. In droves.
“When these fine people came to me with an offer to make four movies for them, I immediately said yes for one reason and one reason only . Netflix rhymes with Wet Chicks,” said Adam Sandler in the press release. ”Let the streaming begin!!!!”
Netflix rhymes with Wet Chicks! Go ahead and say whatever dumb shit you want, Adam Sandler. It doesn’t matter. This is bigger than you. It’s data.
