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Winning Customers with AI, Machine Learning and IoT

Cognizant

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Whether consumers know it or not, three next-generation technologies are playing a major role in shaping their experience with brands — and the future of consumer goods marketing: artificial intelligence (AI), machine learning (ML) and Internet of Things (IoT).

To keep pace and effectively compete in an increasingly connected marketplace, brands are investing in these three technologies to continually fine-tune their customer strategies, using hyper-personalized information across touchpoints.

Convergence of Disruptive Technologies 

Have you ever wondered how Netflix makes movie and TV show recommendations, how Facebook prompts friends to be tagged in photos, and how Alexa, Siri and Google Now assist in our day-to-day activities? These are real-life examples of machine learning — a subset of AI. ML uses a customer’s historic data and behavioral patterns to create high-quality predictions of their future behavior.

IDC predicts that applications with predictive analytics will grow 65% faster than those that don’t have this functionality, and that by 2018, most consumers will interact with services based on cognitive computing.

Related: Stepping into IoT – 14 Case Studies

Similarly, IoT is disrupting many industrial business processes. IoT refers to everyday “things” equipped with sensors that generate enormous amounts of data based on use and environmental conditions. Enterprises across industries are deploying next-generation business models around the convergence of two or more of these disruptive technologies to segment and analyze the volumes of data they generate to determine what is meaningful.

Figure 1

In light of this, tech giants such as Apple, Amazon, Google, IBM and Facebook are on an acquisition mission to beef up their ML and AI capabilities. For instance, Google has upgraded its image search and recognition capabilities to identify individuals or objects in photos on the Web. Meanwhile, Apple is investing heavily in AI in areas such as self-driving autonomous vehicles, mapping, image recognition and processing, and voice control.

Rethinking the Customer Experience with AI, ML and IoT

ML is already delivering consistent, gratifying customer experiences across digital channels in three key areas, namely sales, marketing and customer service.

1. Improving Sales Productivity

Sale personnel rely on their mobile devices to stay connected to their company and their customers. Given the enormous amount of data generated by various systems across channels, sales leaders are challenged to qualify leads and identify the right opportunities. By applying ML algorithms, forward-thinking businesses are improving their sales forecasts (predicting credit risk, customer churn, etc.), automating account management and lead-identification activities, and uncovering new upsell and cross-sell opportunities.

2. Better Targeting Marketing Campaigns

As more customer information becomes available through big data, ML will become an essential element of customer-focused marketing campaigns. Among the top challenges marketers face include lead generation, ROI measurement and generating personalized offers/messages in real time by utilizing customers’ personal data, demographics, historical purchase patterns and social sentiments, for example.

3. Enhancing Customer Service

Customer service organizations are increasingly incorporating human-assisted virtual agents such as chatbots to route customers to the right agent and improve the overall quality of service. AI technologies such as natural language processing and speech recognition assist live call center agents by looking up relevant information and suggesting appropriate responses. (To learn more, read: “How Machine Learning Can Optimize Customer Support.”)  Another AI technology, conversational voice interfaces such as Amazon’s Alexa and Apple’s Siri, provides the ability to conduct a natural conversation with customers (and customer support personnel) and suggest the next best action.

[Download]: Stepping into IoT – 14 Case Studies

Looking Ahead

Today’s enterprise systems generate enormous volumes of data that can be fed into AI, ML and IoT technologies to analyze meaningful trends and generate actionable insights. C-level decision makers must understand the important role of this treasure trove of enterprise and customer data in building and maintaining stronger customer relationships, providing hyper-personalized offers and increasing client engagements.

What’s the best way to evaluate where these technologies can be best applied? We recommend:

  • Identifying repetitive business processes that require a lot of manual intervention, often leading to mistakes in order fulfillment, inventory management, shipping, purchasing and billing. When automated, these tasks are predictable and manageable — freeing human resources to focus on more critical tasks.
  • Assessing IT back-office systems and batch processing functions, which are good candidates for intelligent automation.
  • Automating customer service functions for inquiries or tech support with virtual assistants to encourage self-help.
  • Enhancing business processes with ML algorithms to predict employee/customer churn, track equipment conditions and resolve trouble tickets faster by intelligently routing work to the right agent.

As ML, AI and IoT solutions mature, their impact will be felt in more profound ways across the enterprise. The time is now for companies to weave these disruptive technologies into their strategic agendas to enrich the customer experience, streamline processes, drive profitable business growth and transform the way they operate and serve customers.

This article originally appeared on cognizant.com

[Download]: Stepping into IoT – 14 Case Studies

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New research predicts six key trends in the consumer IoT market

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Smart home IoT company Viomi Technology and the International Data Corporation have jointly issued a white paper that identifies key consumer trends for the Internet of Things and the smart home.

With the smart home, connected services and the Internet of Things overall gaining greater acceptance it is important for businesses to understand where the technology is heading next. Focusing on the home market, smart home Internet of Things company Viomi Technology, in collaboration with the market intelligence company International Data Corporation (IDC), has issued a white paper that signals the key consumer trends that are set to shape the home IoT market over the next few years.

The new paper is called “Consumer IoT Outlook 2025“, and as the title suggests it forecasts the primary trends in the consumer IoT market from now through to 2025. These trends are:

  • Computing capabilities of consumer IoT devices will increase rapidly. For this, artificial intelligence is vital to the future development of consumer IoT. The main developments will be with sensing technology, data acquisition capability and decision-making intelligence.
  • Different network protocols will work together as a hybrid network. The aim here is to provide consumers with stable and fast connection anywhere and anytime. This will be enhanced by 5G, and increased consumer expectations for connection anywhere and anytime.
  • Edge computing and local storage will be widely used on smart devices. This move will improve computing efficiency and personal privacy.
  • Consumer IoT devices will have more open integration in terms of technology. Interoperability should be achieved by breaking the boundaries between products, platforms, and applications.
  • Human-device interaction will be more user-friendly and feel more natural. This will be seen with applications like voice-, image-, face-, and touch-based interaction.
  • Smart devices will soon move into the stage of proliferation. The main growth area, the report suggests, will probably be in China.

The research will be presented by Viomi at the Appliances & Electronics World Expo in Shanghai, China on March 13, 2019.

At the same time, a separate report from market research firm Grand View Research predicts that the global smart home automation market will hit $130 billion by 2025, compared to $46.15 billion in 2016.

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The cloud strategy that Microsoft is leading and that Google and Amazon are betting on is growing, report says

Business Insider

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Microsoft CEO, Satya Nadella. - Photo by LeWeb
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  • According to Flexera’s RightScale 2019 State of the Cloud Report, the amount of large companies with a hybrid cloud strategy, or combining public clouds and data centers to store workloads, has risen from 51% to 58%.
  • Microsoft is the leader in hybrid cloud, as it introduced its hybrid cloud Azure Stack in 2017.
  • Google Cloud and Amazon Web Services have also announced hybrid cloud offerings in the past year.

For a long time, Microsoft has been touting hybrid cloud, or a mix of on-premises and public cloud services.

And in the past year, both Amazon Web Services and Google Cloud have followed suit, making major announcements around hybrid cloud. Companies often choose to keep some of their work on data centers due to regulations, especially in industries like health or finance, and analysts say this will not change anytime soon.

Indeed, 58% of companies with more than 1,000 employees are now pursuing a hybrid cloud strategy, up from 51% last year, Flexera’s RightScale 2019 State of the Cloud Report says.

What’s more, 84% of those companies have a multi-cloud strategy, which means that they store workloads on multiple public clouds, hybrid clouds or data centers. This rose from 81% last year.

Microsoft launched its hybrid cloud Azure Stack in 2017, and currently, Microsoft is the only company out of the top three cloud providers that has a generally available hybrid cloud.

Last November, Amazon announced a hybrid cloud offering calledAWS Outposts, and it will be available later this year. And in February, Google Cloud announced that it will make its hybrid cloud offering Cloud Services Platform available as a beta for customers, a move that company officials say is a part of its strategy to attract more enterprise customers.

In addition, IBM is betting on its upcoming acquisition of Red Hat to help it become a top hybrid cloud player.

Now, 45% of enterprises see hybrid cloud or a balanced approach being using public clouds and data centers as their top priority in their cloud strategy, the survey found. In comparison, 31% of enterprises see public cloud as their biggest focus.

The Flexera RightScale survey polled 786 respondents, 58% of which were large, 1,000+ employee corporations and 42% of which were small businesses.

This article was originally published on Business Insider. Copyright 2019.

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Who will control the data from autonomous vehicles?

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Self-driving cars, like many inventions of the data-driven age, collect huge volumes of data, relating to the performance of the car and geospatial information. Who will, and who should, own this data? A new study assesses the importance.

Researchers from Dartmouth College have questioned the ownership of data in relation to autonomous vehicle technology. As self-driving cars advance, there will be a vast quantity of data amassed from navigational technologies. This leads to important questions that need to be asked about data privacy, ownership, cybersecurity and public safety. This is in the context of the mapping data being collected and analysed by the companies that manufacture the navigation technology.

One use that companies will make of the collected geospatial data is to develop and design new maps. These are produced through sophisticated and proprietary combinations of sensing and mapping technologies. These technologies feature continuous, multimodal and extensive data collection and processing.

Such maps will be able to identify the spaces within which people live and travel. While this can help to promote technological innovation, it raises privacy questions. The researchers are calling on the developers of the ‘black boxes’ that will be integral to autonomous cars to be more open as to what happens with the data and for the navigation devices themselves to have greater transparency.

According to lead researcher Professor Luis F. Alvarez León:

“Self-driving cars have the potential to transform our transportation network and society at large. This carries enormous consequences given that the data and technology are likely to fundamentally reshape the way our cities and communities operate.”

The new research paper proposes that governments should enact legislation that allows future autonomous cars users to unlock the ‘black box’ and understand what data is being used for and why. As León states: “oversight of the self-driving car industry cannot be left to the manufacturers themselves.” The paper also calls for developers to use open-source software, which will enable an understanding of what is happening with the data.

There is also a call for greater understanding of security risks and the extent that data can be taken from car navigation systems.

The discussion has been developed in a paper published in the journal Cartographic Perspectives. The research paper is titled “Counter-Mapping the Spaces of Autonomous Driving.”

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1 download. 14 Case Studies.

Download this report to learn how 14 companies across industries are demonstrating the reality of IoT-at-scale and generating actionable intelligence.

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