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  Think Big – Now Think Even Bigger
  Join Us at Internet of Things at Cloud Expo, November 11-13,
at the Javits Center!


The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago.

All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades.

With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend Internet of Things at Cloud Expo in New York City. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be!

Delegates to Internet of Things at Cloud Expo will be able to attend eight separate, information-packed tracks:

  • Enterprise Cloud
  • Digital Transformation
  • The API Enterprise | Mobility & Security
  • DevOps | Containers & Microservices
  • Cognitive Computing | AI, ML, DL
  • Big Data | Analytics
  • IoT | IIoT | Smart Cities
  • Hot Topics | FinTech | WebRTC

There are 120 breakout sessions in all, with Keynotes, General Sessions, and Power Panels adding to three days of incredibly rich presentations and content.


We'll see you in New York!



Day 3 Keynote at @ThingsExpo | Chris Matthieu, CTO of Octoblu
In his keynote at @ThingsExpo, Chris Matthieu, Director of IoT Engineering at Citrix and co-founder and CTO of Octoblu, focused on building an IoT platform and company. He provided a behind-the-scenes look at Octoblu's platform, business, and pivots along the way (including the Citrix acquisition of Octoblu).
  Themes & Topics to Be Discussed

Consumer IoT
• Wearables
• Smart Appliances
• Smart Cars
• Smartphones 2.0
• Automation
• Smart Travel
• Personal Fitness
• Health Care
• Personalized Marketing
• Customized Shopping
• Personal Finance
• The Digital Divide
• Mobile Cash & Markets
• Games & The IoT
• The Future of Education
• Virtual Reality

Enterprise IoT
• The Business Case for
x IoT
• Smart Grids
• Smart Cities
• Smart Transportation
• The Smart Home
• M2M
• Authentication/Security
• Wiring the IoT
• The Internet of
x Everything
• Digital Transformation
x of Enterprise IT
• Agriculture
• Transportation
• Manufacturing
• Local & State
x Government
• Federal Government

IoT Developers | WebRTC Summit
• Eclipse Foundation
• Cloud Foundry
• Linux Containers
• Node-Red
• Open Source Hardware
• Ajax and the IoT
• Leveraging SOA
• Multi-Cloud IoT
• Evolving Standards
• WebSockets
• Security & Privacy
x Protocols
• GPS & Proximity
x Services
• Bluetooth/RFID/etc
• XMPP
• Nest Labs



The Top Keynotes, the Best Sessions, a Rock Star Faculty and the Most Qualified Delegates of ANY Internet of Things Event!


The future of computing lies in these things. As computing takes a much more active role in our lives it will at the same time become much more invisible. Internet of Things Expo will address the challenges in getting from where we are today to this future.
 
The high-energy event is a must-attend for senior technologists from CEOs on down – including CIOs, CTOs, directors of infrastructure, VPs of technology, IT directors and managers, network and storage managers, network engineers, enterprise architects, and communications and networking specialists.




@ThingsExpo Power Panel | The World's Many IoTs: Which Are the Most Important?
The Internet of Things is clearly many things: data collection and analytics, wearables, Smart Grids and Smart Cities, the Industrial Internet, and more. Cool platforms like Arduino, Raspberry Pi, Intel's Galileo and Edison, and a diverse world of sensors are making the IoT a great toy box for developers in all these areas. In this Power Panel at @ThingsExpo, panelists discussed what things are the most important, which will have the most profound effect on the world, and what should we expect to see over the next couple of years.
Benefits of Attending the Three-Day Technical Program
  LEARNexactly why Internet of Things is relevant today from an economic, business and technology standpoint.
  HEAR first-hand from industry experts the common issues and requirements for creating a platform for the Internet of Things.
  SEE what new tools and approaches the Internet of Things requires.
  DISCOVER how to drive a distributed approach to the Internet of Things, where applications move to the data.
  FIND OUThow the vast volumes of new data produced by the Internet of Things provides a valuable new source of business insight through advanced analytical techniques.
  MASTER how the ongoing development of smart cities, cars, and houses will enhance connectivity infrastructure.
Lunch Power Panel | Microservices & IoT- Moderated by Jason Bloomberg
In this Power Panel at @DevOpsSummit, moderated by Jason Bloomberg, president of Intellyx, panelists Roberto Medrano, Executive Vice President at Akana; Lori MacVittie, Evangelist for F5 Networks; and Troy Topnik, ActiveState's Technical Product Manager; and Otis Gospodnetic, founder of Sematext; peeled away the buzz and discuss the important architectural principles behind implementing IoT solutions for the enterprise. As remote IoT devices and sensors become increasingly intelligent, they become part of our distributed cloud environment, and we must architect and code accordingly. At the very least, you'll have no problem filling in your buzzword bingo cards.


Case Study: Skinit Transforms Big Data into Actionable Information
Gains unprecedented visibility into customer behavior

Skinit Inc. is an eCommerce provider of personalized skins and cases for a wide range of consumer products. With over 180 licensed brands, in-house artwork and the ability to completely customize designs, the company reaches a diverse market. Skinit knew it faced an increasingly competitive market where customers were expecting a more personalized experience. Like many eCommerce companies, we had a large amount of data on what was purchased, what pages were visited, where visitors were coming from and so on. However, while we had more and more data every day, we still lacked the ability to connect all these data points and turn them in to knowledge.

The eCommerce Challenge:
Like any eCommerce site, Skinit relied heavily on web analytics data, using both free and high-priced platforms. Unfortunately both provided some challenges, and the marketing team created a "wish list" of capabilities for a new system.

The "wish list" consisted of the following:

1. We needed an analytics system that was light on implementation and high on integrity. The unique capabilities of Skinit's site made implementation management difficult and threatened data integrity. Like many companies, our development team was swamped with other projects so getting implementation on site in a timely manner was a big challenge.

We were looking at various tag managers to solve this issue. While tag managers would have surely relieved some of the implementation burden, we still had concerns about data integrity as we had experienced problems with tagging in the past, particularly with getting the data comparable for year-over-year benchmarking.

2. The data needed to be person-based rather than page-based. All our efforts were spent optimizing and improving the customer journey, and we needed data that supported this. Connecting web-behavior data to sales, CRM and other supplemental data sets was the next logical step.

While data analytics platforms allowed us to get some data in this format, it was limited and difficult to connect when visits did not lead to purchase - and non-purchasers were the target audience for optimization.

3. Data needed to be collected to enhance merchandising and personalization. With such a large catalog, understanding relationships between products was key to helping the customer personalize their device quickly. We wanted to be able to make recommendations to help the customer along. Since the product can have a wide array of attributes such as color, brand, gender affinity, sports market affinity, geography, etc. that aren't necessarily present in page-level meta-data, we needed to be able to pull data from multiple sources to better understand just what made different products appealing to different users.

We looked at third-party recommendation engines, but felt there were some limitations in the models as they were either built to analyze frequency of purchase combinations or frequencies of products viewed. This presented a challenge for us since most customers bought one product at a time, and products viewed together were proven to be self-fulfilling because customers either viewed what we merchandised to them or they left. The challenge was that we didn't feel we knew how to merchandise the right thing to them.

For example, what recommendation should we make to a customer accessing the site from the San Francisco Bay area but viewing Pittsburgh Steeler products? If we based the recommendation on category, the customer would be shown other NFL products for other teams - unlikely to be appealing since it is rare for a fan to have a strong affinity to two teams in a single sport. Do we market another sport such as baseball? And if so, do we assume they are a San Francisco Giants fan or a Pittsburgh Pirates fan? To really elevate the business, we needed a system that could effectively make decisions like these.

4. We needed to be able to quickly identify, track and examine each micro-conversion path for optimization. Ideally, we wanted to be able to quickly identify the most frequent paths to success and the most frequent paths resulting in drop off. For example, if we had a five-step cart process, we wanted to see how many users went from Step 1 to Step 2 to Step 3 to Step 4 to Step 5, and how many deviated from that path and how. Traditional cart funnels clued us in to deviations from this path, but not where or why.

We could conduct this analysis using our paid analytics platform, but we could not integrate it into our business intelligence system, which made the analysis time consuming and limited in scope.

5. Finally, we needed a better way to visualize problems or optimization opportunities throughout the company in order to get teams to act on findings. We looked at session replay technologies, but were concerned about the limitations in filtering or searching these sessions for specific characteristics important to us. This meant we would have to sample records, which was not the time saver we had hoped for.

We added up the cost of all the various services, partners and platforms we could use to meet most of these challenges. Ultimately, Cloudmeter, a leading software solution provider for transforming real-time network Big Data into actionable information for IT and business users, satisfied all of these requirements and cost 30 percent less than the alternate solutions.

The Cloudmeter Results
The no-code implementation meant that the new platform could be up and running quickly without interfering with site performance. Cloudmeter's reactor system also made it easy to add new variables and to push data to different sources. This was extremely important, as we wanted a system that would grow with us as our questions became more sophisticated. The data feeds were easily integrated into our existing business intelligence system, allowing us to tie onsite behavior to other known data points.

We created a data feed where the primary unit was the customer. Whether they converted or not, we were able to capture each navigation path using custom logic, from how they came to the site, found the product and what cart actions they took. Each of these paths could be aggregated and searched. For example, we could quickly identify the common navigation paths for a customer who clicked on a recommended product and added it to cart, or users that added an invalid coupon code. Since this data was layered into our BI system, we would examine onsite behavior differences by things like gender or market segment.

We were able to capture product metadata from the page and combine that with things like searched keywords to understand relationships between products for merchandising. We found common behavior paths in different customer segments and information, and how to quickly identify those segments - from geographic region, search interest or loyalty.

Finally, the combination of Cloudmeter Stream with web session replay added a layer of efficiency to our analysis. Not only could we email sessions throughout the team - allowing customer service, technology or marketing to see issues first hand, but we could also gain a level of insight into a problem in a much shorter time period. In the past, when an anomaly in the data was observed, it would trigger a time consuming deep dive. Through "data forensics," we tried to piece together theories for the change. Now, when we observe something unusual in the data, we immediately search sessions in Cloudmeter Stream containing the behavior anomaly and usually gain immediate insight into the cause. This simple yet powerful step frees up our analytics team to spend more time on strategy and optimization rather than on constant investigation.

As a result, Skinit is in the process of re-designing the eCommerce platform based on the insights we have learned from Cloudmeter. We expect to see some big gains from the new site, but more importantly, I think we are all excited to find the next place to continue optimization.

About Kate Bartkiewicz
Kate Bartkiewicz is Web Analytics and Manager of Business Intelligence at Skinit, Inc., a provider of consumer personalization products for electronic devices.

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Testimonials
This week I had the pleasure of delivering the opening keynote at Cloud Expo New York. It was amazing to be back in the great city of New York with thousands of cloud enthusiasts eager to learn about the next step on their journey to embracing a cloud-first worldl."
@SteveMar_Msft
 
How does Cloud Expo do it every year? Another INCREDIBLE show - our heads are spinning - so fun and informative."
@SOASoftwareInc
 
Thank you @ThingsExpo for such a great event. All of the people we met over the past three days makes us confident IoT has a bright future."
@Cnnct2me
 
One of the best conferences we have attended in a while. Great job, Cloud Expo team! Keep it going."

@Flexential


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