Digital giants dominate the cloud and ecommerce markets, and part of the reason for their dominance is artificial intelligence and advanced analytics. The good news is that mainstream enterprises can learn from their experiences and employ cutting-edge technologies. 

That’s the word from R. “Ray” Wang who provides a roadmap for AI success in his latest book, Everybody Wants to Rule the World. Wang calls the capability needed to move forward “AI Smart Services” that help automate precision decisions. “To fine-tune precision decisions at scale-that is, to develop decision velocity, [data-driven enterprises] must automate the process of turning signal intelligence into a decision or action. And the way to do this is by creating AI smart services-automated processes powered by AI.” 

The catch is, of course, “AI smart services are not easy to master,” Wang cautions. “They require more than just great algorithms.” He outlines six requirements for advancing in the AI era:

Computing power. To develop AI smart services, data-driven enterprises “must have access to or own cheap computing power,” Wang says. “The ultimate metric for AI rests in pricing not in terms of computing power, but in terms of potential cost per kilowatt hour. The cheapest rate of computing power may determine the cost structure for AI smart services. The most efficient code for finding signal intelligence will provide a cost advantage for each decision made.”

Time. Time waits for no one, Wang says. “The ability to compress time, or take tasks that would normally take weeks and complete them in minutes, provides [data-driven enterprises] an inherent advantage over their competitors.”  However, “AI smart services need more time to identify new patterns. That’s why early adopters who train their AI smart services to process the massive petabytes of data coming in to them gain an advantage. The earlier and the quicker the AI smart services learns, the more precision they put back into their algorithms.” 

Math talent. Algorithms are only as good as the math talent behind it, Wang says. “Success requires hiring digital artisans — those who can balance right brain and left brain expertise. Digital giants typically have armies of data scientists and a brain trust on hand to fine tune AI smart services for their data-driven enterprises.”

Vertical specific expertise. To make precision decisions, AI smart services “must understand nuances of the various verticals in which they operate — such as size of company, industries, and cultural regions.”

Natural user interfaces and user experiences. Data-driven enterprises must develop AI smart services “that engage users in a variety of human computer interfaces that mimic human interaction in terms of their sensory, visualization, voice, and gesture
capabilities. The interfaces might range from chat bots to virtual assistants, and from augmented reality to brain wave mind readers and computer vision.” 

Contextually relevant recommendations. “Once users are confident about how the system arrives at a recommendation, these AI driven smart services start automating decisions-augmenting humanity, accelerating decision making, and ultimately providing filters that deliver situational awareness (the ability to perceive one’s surroundings, events in a timeline, and the potential future state.”

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NICE has brought its artificial intelligence (AI) technologies to the heart of the contact centre, with the addition of Enlighten AI to the NICE Satmetrix Voice of the Customer.

According to the company, the AI is able to help contact centre agents identify at-risk customers and turn them into ‘loyal net promoters’  through the automated deployment of real-time, hyper-personalised surveys that are contextual and conversational.

According to NICE, consumer habits within digital environments are creating more demand for contact centres. Consumers will engage contact centre services for everything from research to purchases, as well as post-purchase enquiries and renewal.

The company also points to a recent NICE survey, which showed that 92% of contact centre decision makers have noticed increased interaction volumes. Further 84% of consumers are likely to switch brands after one poor customer experience.

Aberdeen vice president and principal analyst Omer Minkara says that organisations typically learn what causes customer churn only after they lose their clients.

“Modern contact centres don’t need to pay such a high price of frustrating or losing their clientele. Contact centres using AI capabilities achieve 2.3 times greater improvement in first contact resolution rates, 3.5 times greater annual increase in customer satisfaction rates, and an 11.5 times greater annual improvement (decrease) in service costs.”

NICE aims to Bring Enlighten AI to Satmetrix Voice of the Customer to help organisations provide impactful customer experiences that improve satisfaction and customer loyalty, and to reduce churn.

NICE workforce and customer experience group president Barry Cooper explains,  “As part of a holistic Voice of the Customer program, Enlighten AI Feedback identifies customer experience blind spots and enables organisational agility to close the loop. With that, it delivers what customers want and expect: informed conversations that are frictionless, hyper-personalised – and help resolve their problems.”

Enlighten AI with NICE Satmetrix Voice of the customer:

• Listens to and interprets 100per cent of interactions to transform subjective behaviours into objective insights without bias, using no human effort.
• Eliminates the need for human listening to understand agent performance and identify customer churn threats while providing more precise information.
• Based on the context of the interaction, deploys real-time hyper-personalised, contextual, conversational surveys that expand closed loop efforts to improve customer satisfaction and increase lifetime value.
• Uses pre-trained models that drive proactive, predictive, and prescriptive action to improve the operational efficiency of closed loop efforts at scale.
• Accelerates agile actions to resolve customer issues and prevent churn.

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ThoughtWorks, a global software consulting firm, has announced that the company is acquiring Fourkind, a privately-held Finnish consulting services company that combines data science and machine learning (ML) with strategy, design and engineering. 

As ThoughtWorks’ second acquisition in 2021, it will allow the company to expand its European footprint, and improve its customer service experience in Finland, Netherlands and the Nordics countries.

Founded in 2017 in Helsinki, Fourkind is a consulting services firm that helps forward-looking organisations create futureproof services and products. Fourkind has a strong team of 40 data scientists, machine learning experts, designers, engineers and strategists, and has managed to work with 80+ organisations in 10+ countries. And with this acquisition, ThoughtWorks will leverage its machine learning and data science capabilities for its business.

According to the news media, Fourkind will continue to operate from their existing premises in Helsinki and Amsterdam, along with its founders and leadership team.

When asked about this acquisition, Guo Xiao, the President and Chief Executive Officer of ThoughtWorks said that the company has been looking to partner with a company that can help them “accelerate growth in our key strategic focus areas of data, digital transformation, enterprise modernisation and customer experience.” And this acquisition will allow ThoughtWorks to take advantage of Fourkind’s competence in machine learning, data science, strategy, design and engineering to “help clients lower the perceived risk of adopting new approaches to artificial intelligence,” said Xiao.

He further added, “We were impressed with their track record of delivering significant return on investment for their clients’ AI and ML investments, and believe that our complementary strengths and culture make Fourkind and ThoughtWorks a winning combination,” said Xiao.

Even Fourkind has been quite excited with this recent partnership. Expressing views, Jonne Heikkinen, managing director and one of the founding partners, Fourkind stated that the company’s vision was to create futureproof services and products for companies. 

As a matter of fact, the company has been known for utilising ML in revolutionary ways for groundbreaking innovation. Being a part of ThoughtWorks will allow the company to flourish and expand faster, and “be part of an agile and successful global team of like-minded, passionate technologists” who are continuously striving to create a remarkable impact on the world,” said Heikkinen.

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With an increase in demand for accessible and efficient customer services, augmenting AI with IVR has become an imperative step to ensure improved customer satisfaction.

Whenever a call is made to the customer care center, be it while having queries regarding a particular product or while asking about different services offered by the bank, the customer can hear a monotonous incessant response such as “Your call is on waiting, please hold the line”, or “We have registered your request, we will connect you to an executive shortly.”

This recurrent voice, with monotony in its frequency, is Interactive Voice Response(IVR), which is used in every sector for tending to the needs of the customer. IVR is a telephonic catalog through which the companies register the customer’s queries by identifying, segmenting, and directly connecting the customer to an executive who can attend their queries.

Nonetheless, due to its superfluous technology often the traditional IVRs are unable to comprehend the requests made by customers or intent behind the call.

That’s why most of the customers are now displaying dissatisfaction with the services provided through IVR. The extended time taken by the IVRs to connect to a customer care executive has also become exhausting for customers.

A research report suggests that an estimated 35% of customers want to substitute a more reliable option, because of poor experience with IVRs. Thus for advanced customer satisfaction, the introduction of conversational AI to IVR can be a game-changer for sectors that are administered by attending customer services, like Telecommunication.

What is Conversational AI?

The conversational AI refers to the use of AI-based technology such as apps, speech-based assistants, or chatbots for automating communication with the customer and providing a more personalized experience to the customers.

The conversational AI provides primary insights to the customers regarding the services provided by the companies, thus enhancing the services offered to them.

With the use of conversational IVR, 66% of requests can be resolved faster as compared to that of human agents.

Enhancing the Traditional IVR
The conversational AI expands the quality of IVR, by entitling it with cutting edge technology of Machine learning and Natural Language Usage (NLU), thus offering advanced voice recognition technology. This advanced voice Recognition would respond suitably, accurately, and efficiently, by comprehending the natural free flow human conversations.

The conversational IVR also allows the AI to have intuitive conversations with human beings for having an insight regarding the customer’s service demand. For the businesses, this generates a surge in the elevated customer experience and expands the customer base. With its ability to augment human interaction, conversational IVR can be used for attending multiple language queries, thus reducing the time for response.

Enhancing Customer Services
The traditional IVR uses repetitive technology with basic performances and minimal understanding behind the intent of a customer’s demand. Conversational IVR improves the understanding of the customer’s intent while maintaining the existing context. It resolves the issues or queries of the customers, by giving them detailed information and advice regarding the brand products and services.

The Conversational IVR can also gauge the complex customer query by transferring the simplified conversation to a human agent.

Enhancing Self Learning Capabilities
One of the advantages of using conversational IVR over Traditional IVR is that it doesn’t need regular human intervention to learn and improve its capabilities. The Conversational IVR relies on self-improving after every human interaction.

For businesses this can prove lucrative for providing better customer satisfaction without altering the experience, as the conversational AI can learn from the live human interaction, thus enhancing and increasing its task handling capabilities.

Enhancing Cost- Effectiveness
The reports suggest that conversational AI can reduce the cost per call by 1/8 times as compared to traditional IVR, by decreasing the costs associated with infrastructure and maintenance, recruitment training, and salaries for customer services.

This will help businesses to invest in areas that require immediate attention and capital.

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