Want to Know More About Machine Learning and AI?

Wondering whether you should invest in AI and Machine Learning? That’s a question that the most innovative companies are considering. Why consider it? One good reason is because your competitors have already started. If that doesn’t give you some reason to get motivated, I hope you get started before you are put out of business. To make sure that doesn’t happen, there are  a few things to consider to help you start to explore an investment in machine learning.

It’s the Data, Stupid

Of course, as with any business initiative, you’ll want to create value. And this can be done using machine learning systems. But for those systems to provide value, companies will need to begin by evaluating their organization’s data maturity, but more importantly their readiness to accomplish its data-driven goals. Company’s need to start with an audit of their data warehousing, data scientific research capabilities, data governance and data hygiene. In addition, it’s important to look at the sources, uses, volume, and veracity of all your date, meaning your first-, second-, and third-party data.

Garbage in, Garbage Out

Why is making sure your data so clean? Machine learning is basically taking a computer and making it smart enough to learn from the data it’s fed. We are essentially programming machines to learn. The goal is that after a certain point of time, the computer is able to predict further data. How so? Let’s pretend you want to make your computer predict the weather. So to begin, you might feed the computer weather reports of every hour of every over the past year. What you might end up with is– because the temperature (z) depends on day of the year (x) as well as the time of the day (y), more than two-dimensional curve. In fact, weather is random, so the equation generated by the computer won’t just have 3 variables (x, y, z), it may also have higher powers. So depending on the number of factors in a prediction and the randomness of the outcome, the complexity of the curve can increasingly get more complicated.

So back to the data… And I know you know the story about data: garbage in, garbage out. So hopefully, now you see can why good, clean data is so important to prediction. As the computer is taking the data you feed it to make future predictions, those predictions dependent on the data you are feeding it. So you want the very best data possible. And it takes super computers which are capable of handling large volumes of data, as well as the ability to learn fast and to make fast decisions based on the learning it under goes.

AI and ML Are Not The Same

Often times Artificial Intelligence (AI) and Machine Learning (ML) are used interchangeably. But they are actually different. Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart.” Machine Learning is the application of AI based on the idea that we should be able to give machines access to data and let them learn for themselves. Artificial Intelligence devices (devices designed to act intelligently), are often classified into one of two groups: 1) applied and 2) general.

Applied AI is far more common. Applied AI is about systems designed to intelligently trade stocks and shares or drive an autonomous vehicle. Generalized AI is may up of systems or devices that, in theory, can handle any task. And are less common. However, this is where some of the most exciting advancements are happening today.

Deep Learning is A New Area of Machine Learning Research

It was introduced with the objective of moving Machine Learning closer to one of its original goals: that of being Artificial Intelligence. So essentially Deep Learning is a subfield of machine learning concerned with the algorithms inspired by the structure and function of the brain called artificial neural networks. Deep learning has worked it’s way into business language via Artificial Intelligence (AI), Big Data and analytics. Deep learning is an approach to AI which shows great promise when it comes to developing the autonomous, self-teaching systems which are revolutionizing many industries.

The Two Big Ideas: It May Be Possible To Teach Computers to Learn and The Internet is a Source of a Ton of Data

Arthur Samuel, in 1959 is credited as the one who came up with the big idea that it might be possible to teach computers to learn for themselves. That would be in contrast to teaching computers everything they need to know about the world and how to carry out tasks. The second big idea was that the Internet, with huge increase in the amount of digital information being generated, stored and could be used for analysis. So the scientists and engineers realized it would be far more efficient to code computers to think like human beings, and then plug them into the internet to give them access to all of the information in the world.

Neural Networks Are Algorithms

Neural networks are a set of algorithms, modeled loosely after the human brain and designed to recognize patterns. The development of neural networks has been key to teaching computers to think and understand the world in the way we do, in addition to the innate advantages they hold over people such as speed, accuracy and lack of bias. So a Neural Network is a computer system that classifies information in the same way a human brain does. It can be taught to recognize, for example, images, and classify them according to elements they contain. It works on a system of probability – which means that based on data it’s fed, it is able to make statements, decisions or predictions with a degree of certainty. The addition of a feedback loop enables “learning” – by sensing or being told whether its decisions are right or wrong and then can modify the approach it takes in the future.

What Can Machine Learning Applications Do?

Machine Learning applications can read text and work out whether the person who wrote it is making a complaint or offering congratulations. They can also listen to a piece of music, decide whether it is likely to make someone happy or sad, and find other pieces of music to match the mood. They can even compose their own music expressing the same themes, or which they know is likely to be appreciated by the admirers of the original piece.

These are all possibilities offered by systems based around ML and neural networks. The idea is that we should be able to communicate and interact with electronic devices and digital information, as naturally as we would with another human being. And another field of AI – Natural Language Processing (NLP) – has become an exciting area of innovation in recent years, and one which is heavily reliant on machine learning. (And yes, my initials just happen to be NLP, but that doesn’t really mean anything… just a happy coincidence…)

Where is Used?

Take Google for instance. Google is using it in its voice and image recognition algorithms. It is also used by Netflix and Amazon to decide what you want to watch or buy next. And it is also being by researchers at MIT to predict the future.  While Machine Learning is often described as a sub-discipline of AI, we might look at Machine Learning as the state-of-the-art of AI. Why? Perhaps because it is showing the greatest promise to provide tools that industry and society can use to drive change.

More on the practical uses of AI and ML in the future. For now, noodle on that!

@drnatalie

VP, Program Executive, Innovation and Transformation Center

 

 

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Facebook’s Artificial Intelligence Has The Ability to Search Photos by Content

The term artificial intelligence was coined 60 year ago. But now its starting to deliver. Lumos’s computer vision platform was initially used to improve the experience for visually impaired members of the Facebook community. Lumos is now powering image content search for all users. What does this means to you? You can now search for images on Facebook with key words that describe the contents of a photo, rather than being limited by tags and captions.

How does this work? It starts with the huge task of computational training. For the object recognition used in Facebook’s image search, the artificial intelligence (AI) system started with a small set of 130,000 public photos shared on Facebook. Using the annotated photos the system could learn which pixel patterns correspond to particular subjects. It then went on to use the tens of millions of photos on Facebook. So what this means is that the caption-reading technology trained a deep neural network though public photos shared on Facebook. The model essentially matches search descriptors to features pulled from photos with some degree of probability. You can now search for photos based on Facebook AI’s assessment of their content, not just based on how humans happened to describe the photos with text when they posted them.

How could this be used? Say you were searching on a dress you really liked in a video. Using the search it could be related back to something on Marketplace or even connect you directly with an ad-partner to improve customer experiences while keeping revenue growth afloat. So it seems it can help both customers, customer experience and companies selling things as well as ad partners.

What else is new? Facebook released the text-to-speech tool last April for visually impaired users so they could use the tools to understand the contents of photos. Then, the system could tell you that a photo involved a stage and lights, but it wasn’t very good at relating actions to objects. But now the Facebook team has improved that painstakingly labeling 130,000 photos pulled from the platform. Facebook trained a computer vision model to identify 12 actions happening in the photos. So for instance, instead of just hearing it was “a stage,” the blind person would hear “people playing instruments” or “people dancing on a stage” or “people walking” or “people riding horses.” This provides contextually relevancy that was before not possible.

You could imagine one day being able to upload a photo of your morning bagel and this technology could identify the nutritional value of that bagel because we were able to detect, segment, and identify what was in the picture.

So it seems the race is on for services not just for image recognition, but speech recognition, machine-driven translation, natural language understanding, and more. What’s your favorite AI vendor?

@Drnatalie, VP, Program Executive, Salesforce ITC

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Amazon Go – A Retailer Using AI, ML and Vision Technology

The idea of Amazon Go is to weave into the shopping experience the capabilities of deep learning algorithms, Artificial Intelligence (AI), Machine Learning (ML) and sensor vision. A practical application of AI and ML is Amazon Go via advanced shopping experiences. The ability to walk into a store, grab what you want and walk out, never having to wait in-line: no checkout lanes, no registers. For many customers, especially after work when they are tired and just want to get home or during the holidays could be a much better customer experience.

So how does this work? A customer opens up the Amazon Go app on their smart phone and scans their personalized bar code as they walk into a store. The phone goes into your pocket or purse and the customer begins their shopping. As the customer picks up a product, it’s added to their total. If a customer decides they don’t want an item, replacing back on the shelf removes it from their total.  Amazon Go calls it “just walk out technology” for the modern shopper. Once you are done shopping and leave the store, the total is calculated and charged to the customer’s amazon.com card.

From the customer’s point of view, while on-line shopping has increased, some customers still like the idea of going to a store and touching / seeing the merchandise. To help ensure that brick and mortar stores don’t turn into showrooms (where customers go to look at merchandise and then search on their phones for a better online deal (from that or other retailers) and buy it online while standing in their store, technologies like Amazon Go provide convenience. Perhaps the thought and the hope is that the convenience will be more important than searching for a cheaper price and buying it online.

Showrooming can be very frustrating for brick and mortar stores and put some of them out of business. It’s interesting that the online and offline shopping worlds are colliding. Fresh goods have a short shelf-life and often thought of as poor candidates for online shopping because of their perishable nature. However, it’s a high margin area that Amazon wants to tackle by using brick and mortar stores and the convenience of shop and go. Younger generals don’t have the tolerance for standing in line.

The future of shopping is just getting more and more interesting as the new technologies get implemented.

@DrNatalie Petouhoff, VP and Principal Analyst, www.Constellationr.com

Covering Customer-Facing Applications

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#OOW16 – #IOT Is Really Asking Your Business What Outcomes Are You Looking For?

Many companies approach the internet of things by starting with a device, make it connectable and then are in search of a business use case. This is a typical process that happens when there is a new area of technology area. If a company uses that as a strategy, it can be the long road to #IoT innovation. What businesses need to ask themselves are, “What business outcomes are they looking for and what innovations could be possible to shift their business model?”

We heard from the @OracleIOT group several business scenarios:

  • Break / Fix it – which drives a predictive prescriptive business process
  • Static Analytics – which drives the use of real-time, big-data analytics
  • Ownership – which drives as-a-service business models and
  • Central Service– which drives self-service as well as self-guided service.

new-business-modesl-for-iot

What they are finding is that there are various phases a business often goes through when deploying IOT. It can start with the devices or assets (trucks, phones, factories, etc…) which are then connected to a platform which are connected to a network. For a business to actually make use of IOT, the first phase, Phase 1 can be about Connecting Assets for situations like remote monitoring and asset tracking. Phase 2 is can be using Predictive Analytics which means designing predictive algorithms to transform decisions into proactive instead of reactive decisions and improving products and processes. Phase 3 can be about Service Excellence. This is where the customer or employee experience is affected. It is where IOT is being used to transform business processes by blending IOT into enterprise applications like ERP, SCM, Customer Support, CRM, HCM…

phases-of-development-of-business-maturity-use-of-iot

Some of Oracle’s IOT applications are in the areas of:

  • Asset monitoring for the utilization, availability and data from connected sensors
  • Production monitoring and prognostics of the equipment on the manufacturing factory floor
  • Fleet Management for business who have fleets of trucks, buses, delivery and maintenance vehicles
  • Connected worker for the tracking of employees, for instance in the mining, engineering construction industries.oracle-iot-application-to-business

Here are some examples of clients applying IOT to their businesses:

oracle-example-clients-using-iot

VINCI is building the next generation sensor-driven building automation to reduce the number of “truck rolls” which has a huge ROI. They are doing this with the integration or Oracle Service Cloud and SAP. Lochbridge is creating connected fleets where IOT and big data is being used for predictive maintenance in monitoring fleet / cargo to reduce the response time. GEMU is using real-time filtering and processing of valve events and proactive parts replacement with the integration of CRM, IOT and a service ticketing system. And SoftBank is using IOT to deliver mobility-as-a-service where they are monitoring vehicle location for billing and geo-fencing.

As the world of IOT expands and more and more companies start to see the value in connecting enterprise applications, with devices, and networks, we will see the transformation of workers, employees and customer experiences. When those experiences are transformed, the real value and ROI of the connected enterprise will come to life.

@DrNatalie Petouhoff, VP and Principal Analyst

Constellation Research, Covering Customer Facing Applications and IOT

 

 

 

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The Need for Customer Experience is Based on Science Not Myth

The need for customer experience to improve is not a myth. In fact, here’s why. Noted psychology researcher and writer Mihaly Csíkszentmihályi observed in 1998 that people who perform seamless, sequence-based activities on a regular basis are happier than people who don’t[i]. He coined the term “flow” to describe this behavior. With the advent of CoIT, we’ve actually imposed a new set of demands on our customer’s brains. But instead of offering a series of smoothly sequential flows, websites and mobile applications are characterized by lag, downtime, and restarts. And at the same time customer’s flow-oriented brains simply aren’t wired to deal with poor digital experience interactions. Science has shown the business need for great customer experiences is a fact, not a myth.

And it can be tempting to label customers picky and impatient. But there’s a wealth of research on what happens to customers at a neurological level when they are forced to deal with slow or interrupted processes.[i] Their impatience is an indelible part of their human circuitry. Brands must recognize that customers’ hardwiring of the brain’s and their neurological desire for flow and easy of use as part of the cost of doing business. Companies must come to terms with the economic imperative of the customer experience or drive customers to their competitors because of their poor focus on customer experiences.

Fast websites and mobile experience create happier users. Those happier users are more likely to follow “calls to action” to register, download, subscribe, request information, or purchase. Unhappy users, which could include those who experience a mere two-second slowdown in how a web page loads, make almost two percent fewer queries, three point seven-five percent click less often, and report being significantly less satisfied with their overall experience[i]. Worse, they tell their friends about their negative experience. With the word-of-mouth social networks provide, brands need to heed the seriousness of differentiating their brand’s customer experience or be left in the dust.

Response Times have been consistent for 45 years. Based on neuroscience, the facts about human perception and response times have been consistent for more than forty-five years[i]. In fact, these numbers are hard-wired in human brains. And they are consistent regardless of the type of device, application, or connection a customer is using. In fact, that’s key to where customer expectations come from thus important to capitalize on. And what’s critical is determining where a brand’ web / mobile sites compare to customer expectations as well as benchmarking against CoIT applications or competitors or even non-competitors who have a great customer experience.

Response Time Has Not changed Much. In Robert B. Miller’s 1968 paper, “Response Time in Man-Computer Conversational Transactions[ii]“, found people have always been most comfortable, most efficient and most productive with response times of less than two seconds. Since 2006, what has changed slightly is the average online shopper expects pages to load in four seconds or less. Today, forty-nine percent expect page load times of two seconds or less, and eighteen percent expect pages to load instantly[iii]. And while optimizing every aspect of a brand’s digital assets to meet an “instant” expectation is a laudable goal, organizations simply may not have initially budgeted the resources to achieve these goals. Digital experience maturity, however, provides teams the ability to identify the interaction points in the digital customer journey most sensitive to improvement so they can maximize return on performance investment and include this in the budget and resource planning activities. Here’s the results of the Walmart study on page load times and conversion rates:

Screen Shot 2016-05-26 at 10.11.29 AM

Businesses can keep arguing that customer experience doesn’t matter, it’s a touchy-feely construct or get it directly affects the bottom-line and start by designing and measuring customer experience performance management. For more on this see my report, here.

@drnatalie petouhoff, VP and Principal Analyst

Covering Customer-Facing Applications

[i] http://www.webperformancetoday.com/2014/07/16/eight-tricks-improve-perceived-web-performance/

[ii]Robert B. Miller’s 1968 paper, “Response Time in Man-Computer Conversational Transactions, https://www.computer.org/csdl/proceedings/afips/1968/5072/00/50720267.pdf

[iii]http://insights.wired.com/profiles/blogs/47-of-consumers-expect-a-web-page-to-load-in-2-seconds-or-less#axzz498kHSokj

[i] http://www.webperformancetoday.com/2010/06/15/everything-you-wanted-to-know-about-web-performance/.

[i]Dual-task interference in simple tasks: Data and theory. Pashler, Harold Psychological Bulletin, Vol. 116(2), Sep 1994, 220-244. http://dx.doi.org/10.1037/0033-2909.116.2.220

[i] The Concept of Flow: Handbook of Positive Psychology, Nakamura, J. and Csikszentmihayi, M. 2002.

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Local Motor’s Self-Driving Vehicle Taps the Power of IBM Watson

There’s been a lot of talk around self-driving cars and Local Motors, a leading vehicle technology integrator and creator of the world’s first 3D-printed cars, introduced the first self-driving vehicle to integrate the advanced cognitive computing capabilities of IBM Watson. Local Motors is a technology company that designs, builds and sells vehicles. The Local Motors platform is a combination of a global co-creation with local micro-manufacturing to bring hardware innovations quickly to market. Local Motors in National Harbor, Maryland is a public place where co-creation is the focus for advancement of vehicle technologies.

What can you see if you visit the Maryland facility? On display are 3D-printed cars and a large-scale 3D printer. There visitors can have an interactive co-creative experience that showcases what the future of 3D printing, sustainability, autonomous technology will be. Visitors can get involved with Local Motors engineers and the company’s co-creation community.

The automobile has a name and it’s called “Olli.” At its debut it was carrying the CEO of Local Motors and co-founder John B. Rogers, Jr. and vehicle designer Edgar Sarmiento. The vehicle took them from the Local Motors co-creation community into the new facility. While there are already self-driving action in Washington, DC, soon there will be vehicles on the road in Miami-Dade County and Las Vegas. The cars can carry up to 12 people. More details can be seen in this video:

Source: IBM Watson

What’s the Big Innovation? The electric vehicle is equipped with some of the world’s most advanced vehicle technology, including IBM Watson Internet of Things (IoT) for Automotive. Passengers can interact conversationally with Olli and ask about:

  • Destinations, for example, “Olli, can you take me downtown?”
  • Specific vehicle functions  like: “How does this feature work?”
  • Time related questions like, “Are we there yet?”

In addition, Olli can make recommendations on local restaurants or historical sites. Olli is essentially designed to deliver interesting, entertaining, intuitive and interactive experiences for riders. How is IBM Watson is being used to improve the passenger experience? It is enabling the natural interaction with the vehicle via the cloud-based cognitive computing capability of IBM Watson IoT to analyze and learn from high volumes of transportation data produced by more than 30 sensors embedded throughout the vehicle. As the vehicle gets used, Local Motors plans to install more sensors and adjust them continuously as passenger needs and local preferences are identified.

The platform leverages four Watson developer APIs:

  • Speech to Text
  • Natural Language Classifier
  • Entity Extraction and
  • Text to Speech.

Harriet Green, General Manager, IBM Watson Internet of Things, Commerce & Education commented that, “Cognitive computing provides incredible opportunities to create unparalleled, customized experiences for customers, taking advantage of the massive amounts of streaming data from all devices connected to the Internet of Things, including an automobile’s myriad sensors and systems. IBM is excited to work with Local Motors to infuse IBM Watson IoT cognitive computing capabilities into Olli, exploring the art of what’s possible in a world of self-driving vehicles and providing a unique, personalized experience for every passenger while helping to revolutionize the future of transportation for years to come.”

Having worked in the automotive industry in Detroit, it’s exciting to see new develops like this. It’s also exciting to see the application of cognitive computing in a real world situation. Using it for something like empowering self-driving vehicle is probably the best way to advance not only the self-driving cars but also the ability to deploy cognitive computing in a real world application. This looks to be the start of something very interesting that other brands in this space should be taking note of. Competition in the automotive is rapidly changing, from the provision of Cars-As-A-Service, with GM investing $500M in Lyft to cars that drive themselves. The Future is here.

@DrNatalie Petouhoff, VP and Principal Analyst, Constellation Research

Covering customer-facing applications that create amazing customer experiences.

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Dr. Natalie’s Research Agenda and Published Research

If you are wondering what I have been up to lately, I thought I would put all the research I have published  into one place. Here’s a list of Dr. Natalie’s completed and published research and soon to be published content! It ranges from IOT, Analytics, Big Data, Customer Experience, Leadership, Organizational Change Management, Storytelling, Collaboration, Digital Transformation, Social Selling, Social Media, the Cloud, Marketing, Sales, SaaS, IaaS, PaaS, DaaS, AI, Machine Learning, Innovation, Social Networks, Social Media Monitoring, Mobile, Customer Service and Customer Success Management….and a few things in-between…

IOT (The Internet of Things), Innovation, AI, Machine Learning, Analytics and the Cloud

• The Algorithm of You: How IoT Transforms and Differentiates Customer Experience: Using the Internet of Things to Boost Revenue and Deliver a Brand’s Personalized Promise

• Digital Disruption: The Blind Spot That Could Sink Your IoT and CX Initiatives

• The Internet of Things Improves Customer Experience in Retail Supply Chain

• The As-a-Service Economy: CX and IOT Mean You Have to Deliver Great Experiences- Upcoming

• Customer Experience IOT in the Automotive Industry-Upcoming

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Digital Transformation: Customer Engagement, CRM, Innovation, Customer Experience, Customer Service, The Cloud and Analytics

• ROI Of Customer Service & Customer Experience

• How to Measure Customer Experience: Performance Management Maturity-Upcoming

• Case Study: Elaine Turner® Brand and Oracle Commerce, Marketing and Customer Service-Upcoming

• The Need for Inspiring Leaders to Orchestrate Customer Experience Initiatives-Upcoming

• Experience Management: How to Deliver Integrated Customer Experiences

• How Rackspace Creates the Next-Generation Customer Experience

• The ROI Of Agile Customer Care: Reduce Training and Easy To Add Channels

• Digital Imperatives for Omni-Channel Retail Customer Experiences

• Nine Pillar Of Successful Self-Service for Digital Customer Engagement

• 6 Pillars of e-commerce Customer Engagement

• 9 C’s of Customer Engagement – Delivery and Communication Styles: Channels, Content and Cadence

• 9 C’s of Customer Engagement – People Centric Values: External & Internal Culture, Community, Credibility

• 9 C’s of Customer Engagement – Right Time Drivers: Context, Catalysts, Currency

• How Delta Uses Microsoft Dynamics and Avanade to Create Next-Generation Customer Experiences

• How Microsoft Dynamics CRM Improves Productivity at Trek Bicycle

• Delta Uses Microsoft to Transform Flight Operations and the Customer Experience

• New Belgium Brewing Creates Great Customer Experiences Using Microsoft Dynamics

• Beyond Journey Maps, Delivering Mass Personalization at Scale

• The State of Customer Service and Support Evolves 

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Social Media, Customer Service, CRM, Analytics, Innovation and the Cloud

• How General Motors Using Social Media To Listen To Customers and Sell Cars and Deliver Service

• The ROI of Online Communities: Online Communities Provide Value Beyond Call Deflection

• Why Top Marketers Create Branded Social Networks for Customer Engagement

• The State of Customer Service and Support Evolves 

• ROI of Social Customer Service- Upcoming

• The Customer Service Playbook for Integration of Traditional, Digital, Social and Mobile Customer Service Strategies and Technologies-Upcoming

• Mobile Customer Service-Upcoming

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Digital Marketing, Analytics, Innovation and the Cloud

• Should the Chief Marketing Officer Oversee the Whole Customer Experience?

• Data-Driven Marketing Campaign Optimization

• VentureBeat: Should the CMO Run the Whole Customer Experience?

• Executive Brief: Can Brands Keep Their Promise?

• Oracle Moves Its Focus from the CIO to the CMO

• How to Staff the Team for Effective Content Marketing

• The State of Marketing 

• Marketing Funnels Are Dead, What’s Next?

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Digital and Social Sales; Commerce, Innovation, Analytics and the Cloud

• How Sales Leaders and Sales Reps Can Create a Social Selling Organization: Convert Average Sales Teams into Top Performers Using Social Networks

• Five Approaches to Drive Customer Loyalty in a Digital World

• The Modern Sales Experience

• Continuity of Customer Experiences Drives the Future of Commerce

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Customer Success Management, Analytics, Innovation and the Cloud

• The State of Customer Success Management

• Gainsight: Customer Success Management for a Post-Sale, On-Demand, Attention Economy

• ServiceSource: Customer Success Management for a Post-Sale, On-Demand, Attention Economy

• Bluenose: Customer Success Management for a Post-Sale, On-Demand, Attention Economy

• Totango: Customer Success Management for a Post-Sale, On-Demand, Attention Economy

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If you are interested in learning about any of these reports or research, a speech or webinar on any of these or related topics, please reach out to me here!

@DrNatalie Petouhoff, VP and Principal Analyst, Constellation Research

Covering Innovative, Customer-Facing Applications that Create Great Customer Experiences

 

 

 

 

 

 

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I’m Judging the SuperNova Awards: Make Sure to Submit Your Case Study

I’m judging the 2016 Constellation SuperNova Awards! Every year the Constellation SuperNova Awards recognize individuals for their leadership in digital business. Nominate yourself or someone you know before August 8, 2016.

About the SuperNova Awards
The SuperNova Awards honor leaders that demonstrate excellence in the application and adoption of new and emerging technologies. In its sixth year, the Constellation SuperNova Awards will recognize individuals who demonstrate leadership in nine categories:
•  Internet of Things – A network of smart objects enables smart services. (sensors, smart ‘things’, device to purchase, artificial intelligence)
•  Data to Decisions – Using data to make informed business decisions. (big data, predictive analytics)
•  Digital Marketing Transformation – Personalized, data-driven digital marketing.
•  Future of Work: Social Business – The technologies enabling teams to work together efficiently. (enterprise social networks, collaboration, digital assistants)
•  Future of Work: Human Capital Management – Enabling your organization to utilize your workforce as an asset.  (talent management, benefits, HR core)
•  Matrix Commerce – Commerce responds to changing realities from the supply chain to the storefront. (digital retail, supply chain, payments, ‘ubiquitous-channel’ retail)
•  Next Generation Customer Experience – Customers in the digital age demand seamless service throughout all lifecycle stages and across all channels.  (crm, customer experience)
•  Safety and Privacy – Strategies to secure sensitive data (blockchain, digital identity, authentication)
•  Technology Optimization & Innovation – Innovative methods to balance innovation and IT budgets. (innovation in the cloud, ENSW cost savings, cloud ERP, efficient app production)
The SuperNova Awards are seeking leaders and teams who have innovatively applied disruptive technolgies to their business models as a means of adapting to the rapidly-changing digital business environment. If you have what it takes to compete in the SuperNova Awards submit your application today: https://www.constellationr.com/events/supernova/2016
If you are doing something really interesting, make sure to send in your case study! It’s your time to be recognized for your hard work!
@DrNatalie Petouhoff, VP and Principal Analyst, Constellation Research
Covering Customer Facing Applications that Drive Awesome Customer Experience
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From the Field: Capgemini Analyst Conference #capgemniAD16

Old Dogs Can Learn New Tricks: It’s never too late to transform yourself. Having been a system’s integrator many years ago, I found the transformations happening at Capgemni very inspiring. There was a period where many system’s integrators avoided the conversation about going to cloud and for good reason. Their business and revenue model was not shaped for the cloud. They were based for on-premise installations. Enter the cloud and everything changed. With the integration of IGATE and Capgemini, outstanding changes are definitely clear. Replacing McKinsey and Accenture in many digital transformation projects, they are looking to lead the digital transformation. Net new customers are over 200 and a 35% increase in the client base in North America. Though under NDA, the brands were very impressive.

What did Capgemini learn from IGATE? And I have to say I really appreciated all of the executives transparency and honesty in their process of becoming a digital transformation system’s integrator – including but not limited to Fernando Alvarez, Paul Hermelin, Srikanth Iyengar, Bill Ruh, Lanny Cohen, Tim Bridges, John Mullen, Dee Burger, Todd Rovak, Jean Pierre Petit, Frank Greverie, Doug Mills, Mathieu Colas and Andre Cichowlas. IGATE was known for the great client relationship capabilities. A client’s CIO had said, “I’ve never had a company pay more attention to my culture and my people and company that what we have experienced with IGATE.” IGATE is a new breed of company infusing it’s culture into Capgemini, with the key themes of speed, agility and imagination. And Capgemini vowed to learn from IGATE.

Capgemni’s Digital Business Model: It includes not only the “what” but the “how” of customer experience, including digital customer experience, digital organizational and people and digital operations. In terms of the “how”–  what digital seems to mean are areas like social & mobile, data, IoT, cyber security and cloud. There was a large focus on cyber security, as more and more customers are putting their data in the cloud. There is a focus on digital innovation as well as a digital ecosystem of partners and start-ups in the mix. There key digital capabilities include: innovation, digital customer experience, digital manufacturing and insights and data.

Fahrenheit212 Innovation Strategy and Design Company: They believe that innovation can be inherently reliable and have spent the last decade designing the method, building the model, and assembling the minds to make innovation a predictable driver of growth for our clients’ businesses. They believe most great innovations don’t come from consultants—they come from entrepreneurs and entrepreneurial organizations. Entrepreneurs are driven by a powerful force that counter-balances their challenger mentality. Namely, they have skin in the game. They don’t obsess over the process of innovation; they care only about the outcomes. And it’s why they make a good addition to Capgemini.

Since their inception, Fahrenheit 212 has harnessed this entrepreneurial approach through a performance-based compensation model that aligns our risk and reward with that of our clients. They offer their clients the option of putting a significant portion of our potential compensation at risk, contingent on their solutions hitting pre-determined success milestones. This means their ideas can’t just be interesting; they actually have to deliver actual business results.

Digital Manufacturing Is Hot: The digital manufacturing value proposition includes a comprehensive enterprise offer of smart product and plants, Capgemni IP and an extended ecosystem of subject matter experts and highly skilled resources. With a 180,000 Capgemini employees, they are looking not only to re-skill some folks as well as hiring new people.

Cloud Is the New Normal: Their cloud value proposition is that cloud first is the new normal. Of their North American clients, 80% want their applications in the cloud in some way- some pure cloud, others a hybrid model.

Competitive Roadmap For Capgemini: Capgemini’s competitive roadmap is one of quality of service  where they want to work with some of the most demanding clients on the most challenging projects with the most talented people in the world. Capgemini’s entry into the world of IoT, though under NDA, was very impressive and spot on. I look forward to see what comes of their partnerships and their vision.

@drnatalie petouhoff, VP and Principal Analyst, Constellation Research

Covering Customer Facing Applications, including the customer experience of IOT

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The Year of On-demand, Personalized Shopping: The Cloud and IOT Abound

What’s Happening in the World of Shopping and Customer Experiences? At the National Retail Federation Annual Convention in New York City, Microsoft made announcements with GameStop, Hardee’s, TGI Fridays, Panasonic, HP and FreedomPay, and NCR on efforts to modernize shopping experiences.

How Does IoT, The Cloud and Customer Experience Come Together? Microsoft believes this will be the year when modern shopping experiences come to life. Where retailers create instant, personalized experiences for shoppers on their smartphone, online and in stores. It will be the year that customers return to stores because technology is engaging them in new ways, making them want to buy more and come back. Microsoft shared for the first time several retail innovations using its technology, including a smart shelf and a tablet-enabled shopping cart, and showed how retailers can gather better store analytics. Microsoft also announced how Pandora and Ashley Furniture are working with technology to create more engaging experiences for employees, helping them be more collaborative and support faster product innovation.

Engaging Customers During the Shopping Experience is Essential for Today’s Retailers. GameStop announced it is working with Microsoft to create an interactive, informative and entertaining shopping experience in an immersive environment. In the near future, when customers walk into one of the GameStop pilot stores, they will be connected to the services enabled by the Microsoft Cloud, allowing them to browse product choices, share their shopping cart with salesperson’s tablet running an assisted selling application, and even browse products interactively on a big screen Ultra High Definition TV where they can view video game trailers with pristine clarity. When a customer downloads and opts into the GameStop app on their smartphone, they will be able to interact in a whole new way with GameStop marketplace through the use of Azure. Ultimately, the customer and the salesperson can push the desired products to the point of sale (POS) system for order processing and payment.

What’s Another Great Example of How Microsoft is Working With Retailers to Improve Customer Engagement and Customer Experience? One example is Hardee’s new way to make ordering a meal fast and fun. Hardee’s is currently deploying self-ordering kiosks for ordering meals, using Windows 8 devices. These in-store kiosks are being tested currently in 30 restaurants with plans to extend that test to additional restaurants soon. Each kiosk allows customers to review the menu and order food and lets managers run sales and shift reports, while dramatically reducing wait times. Check out the video and read more here.

Another Example is TGI Fridays Who Has Plans to Transform the Way People Order Food by Equipping Servers with 8-inch Tablets Armed with Payment Sleeves. With the Fridays’ Service Style technology the customer’s order is processed right at the table, the device also helps manage the waiting list and queue. The solution helps ensure orders are correct, reduces training time, and streamlines waitlists.

Modern Points of Sale Connect Retailers and Customers in New Ways.  As the shopping experience becomes more modern, so does the POS. Modern POS devices are allowing retailers to better understand their customers, provide more customized service, and help them achieve compliance with new security measures being implemented in 2015.  In partnership with Panasonic, HP and FreedomPay Microsoft is demonstrating how the modern POS can create personalized retail experiences, in real-time, through smart and secure devices. With new security regulations on the horizon, retailers need to upgrade their POS devices, not only to ensure their customer data is safe, but to also be able to provide a more personalized and seamless experience at check-out. Read more about modern POS devices here.

Innovation that helps retailers understand buying behavior and customers make informed decisions.  One of the challenges in retail is to create an in-store experience that engages customers in unique ways, entices them to come in to stores, and keep them coming back. Creating those connections creates better experiences and ultimately increases sales. With the help of a Kinect sensor, AVAretail’s SmartShelf technology allows every interaction of a shelf in a store to be monitored and recorded in real-time, providing insight into which products are most selected and picked up by customers. Another form of technology, Path Tracker, gives retailers real-time detection and analysis of a customer’s shopping path.  This provides counts of people in the store, areas visited, dwell time and shopping path, acting as a heat map of where customers are spending the most time in the store.

The NEC Biometric interface with Kinect Camera System Provides Demographic and Face Recognition Services to a Kinectically Enabled Application. Retailers can use this information for analysis and for providing the customer with a more personal selling experience. MediaCart will change the shopping cart as we know it. Adding a location-aware tablet to the cart allows a retailer to present a personal and relevant shopping experience to its customer.  This allows context sensitive ads and promotions when in front of various products along with a barcode scanning capability for price lookups and basket totals.

Retailers Are Predicting Consumer Behavior With Machine Learning. As technology advances, consumers have more tools at their disposal during the buying process. This trend seems to be growing exponentially, especially as the Internet of Things (IoT) matures. This is both an opportunity and a challenge for retailers looking to capitalize on a whole new base of consumers. Competitive pressure, combined with ubiquitous connectivity, smart devices and an intelligent cloud platform is causing a shift to a new retail reality. Food delivery company JJ Food Service uses machine learning to make product recommendations as customers are shopping for food. This provides insights, saves on costs, and ensures their customers have the food they need, when they need it.

Customer Behavior Can Be Predicted. Auckland, New Zealand-based VMob runs a mobile engagement platform on Microsoft Azure which predicts likely customer behavior based on historic and live data streams. The platform currently delivers personalized content to millions of consumers around the world, including customers of McDonald’s across several European markets. The VMob platform collects real time data from multiple sources including mobile devices, wearables, location temperature sensors, WiFi transmitters, beacons, digital signage, and POS systems to personalize engagement with the customer. The VMob platform uses Azure Machine Learning to harness the Internet of Things to predict future customer behavior – transforming live and historical data streams into actionable insights McDonald’s can employ to individualize its marketing efforts. See more information about VMob’s work here.

You Want to Reach Your Customers Where They Are. For retailers to succeed, they need to reach their customers where they are.  Because of this, we are pleased to be announcing Sitecore Commerce, powered by Microsoft Dynamics. This solution integrates the experience management capabilities of the Sitecore Experience Platform with the omni-channel commerce capabilities of Microsoft Dynamics AX for Retail. The result is a product that allows enterprises to bridge the gap between in-store and digital experiences. We are also announcing a combined effort with Toshiba to form the Toshiba Global Commerce Solutions with Microsoft Dynamics to help retailers deliver leading customer experiences through true omni-channel customer engagements. This effort includes Toshiba delivering software and implementation services on the Dynamics platform as well as plans for the global availability of a combined solution – TCxGravity powered by Microsoft Dynamics – specifically tailored to deliver omni-channel transformation on the customer’s terms, helping it provide seamless brand experiences to build lasting loyalty.

What’s The Future of Retail? Retailers are changing the game through connected stores, empowered employees, digital engagement and ambient intelligence all geared toward delighting the modern shopper. By gathering and ingesting insight from myriad data sources, retailers can create a comprehensive understanding of each customer, its store’s inventory and the capabilities of its business to seamlessly match people with the products and services they desire.

The end result of these technologies and services, and of Microsoft’s work with retailers, is an increased focus on solutions that help grow sales and profits, increase customer satisfaction and loyalty, bring products to market faster, and create a more effective business.

If you want more information, visit the Retail NewsroomThe Windows for Your Business Blog, and The Dynamics Blog.

MyPOV: I Love to shop and I love technology. So this is gonna be a great year! I can’t wait to see how cloud computing, IoT and customer experience emerge as the top competitive advantage to lead conversion rates, higher revenues and awesome customer experiences!

@DrNatalie Petouhoff, VP and Principal Analyst, Constellation Research
Covering Cloud and IoT That Drive Better Business Results and Awesome Customer Experiences in Retail Environments
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