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6-steps-for-Conversational-Bot-success-A-primer 

Make the most of your conversational bot investment with our easy-to-follow guide featuring best practices that can be applied to your digital transformation journey.

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(Featured) 6-steps-for-Conversational-Bot-success-A-primer

Six steps for conversational bot success: A helpful primer for chatbot implementation

See why cloud technology, data protection, AI, interactive voice search and navigation and omnichannel experience are the top digital CX trends in 2023.

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digital trends 2023

The top digital customer experience trends in 2023

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TELUS International, in partnership with Statista, surveyed 250 enterprise leaders to explore where they plan to invest in digital customer experience (CX) technology in 2023. Uncover the results.

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Survey results: Digital customer experience priorities for leaders in 2023

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Outsourcing Locations E-book Feature

Discover some of the top outsourcing destinations for consideration and the factors to keep in mind as you make your decision.

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Selecting the best outsourcing destination for your business

You've heard of product-market fit, but what about profit-market fit? Learn the difference and how scaling tech brands can achieve it.

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profit market fit

Why achieving profit-market fit is essential for scaling brands

Generative AI is a type of AI that can be used to generate new content such as text, images, audio, video, code or synthetic data. Discover exactly how generative AI works and what you can do with it.

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Generative AI 101

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Learn about how we helped a consumer robotics company improve their digital customer experience with agent-facing automation.

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Deploying automation to assist agents at a consumer robotics company

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The future of content moderation: Strategies and tools for 2023 and beyond

Organizations have a responsibility to create and maintain digital experiences that are truthful, welcoming and safe. Learn how brands can keep pace with the growing levels of user-generated content (UGC) to build trust with their customers and protect their reputation.

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In this IDC Info Snapshot, learn about the three key pillars for any successful AI implementation and the advantages of partnering with a trusted advisor to create and deliver your AI vision.

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Quality, quantity, and responsibility: Three key data pillars for successful AI implementations

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Digital transformation has reshaped the payments industry. With consumer expectations on the rise, there's never been a better time to invest in a high-tech, high-touch customer experience (CX). See how our mix of human touch and cutting-edge digital tools can help streamline operations, improve fraud detection measures and offer exceptional experiences that promote long-term customer loyalty.

See how TELUS International can help card services brands meet rising consumer expectations through high-tech, high-touch customer experiences.

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Holistic digital customer experience solutions for card services

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Digital Experience (DX)

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TI Resource WhitePaper 2023

Delve into new insights about customer experience outsourcing from a survey of 712 enterprise executives with strategic decision-making authority.

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Executive survey results: CX outsourcing in 2023

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Discover best practices for the sourcing, labeling and analyzing of training data from TELUS International, a leading provider of AI data solutions.

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The essential guide to AI training data

Player support outsourcing isn't just for Triple-A studios. Learn about the benefits of outsourcing for growing games companies.

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What growing games companies can gain from player support outsourcing

Germany's diverse and talented workforce make the European nation an ideal CX outsourcing destination. Read up on all the benefits.

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Don't overlook Germany as a CX outsourcing destination

If words like "amortization" get your customers feeling anything but amore, you're not alone.

Many would-be customers grapple with the complexities of financial decision-making. It's easy for them to become paralyzed by choice: should they save? Invest? Pay down debt?

These anxieties are compounded by an increasing sense of financial vulnerability amid rising inflation and costs of living. According to the American Psychological Association's 2022 Stress in America™ survey, 65% of respondents say money is the most significant stressor in their life — a steady rise from the previous survey results from 2021.

For banks and fintechs, consumers' rising financial stress and decision fatigue present an opportunity to ease tensions through digital customer experience (CX). By looking after your customers' best interests and helping them make better decisions, industry brands can demonstrate that they understand the challenges of the day. As Forrester's report The Top Emerging Technologies In Banking In 2022, points out, this is where predictive analytics can play a critical role.

Predictive analytics is an artificial intelligence-backed technology that captures data from diverse sources and uses computer models to create insights for a range of practical applications.

In the financial services industry, the technology is used to score client's creditworthiness, identify fraud and much more. In fact, while industry brands have leveraged the power of predictive analytics for some time, the use cases are evolving — so much so that the aforementioned Forrester report lists predictive analytics as a "hot" technology. The research firm explains that the label reflects "both interest and planned spend in the coming 12 months," and adds that it will "shape the future of the banking industry and customer experience."

Companies in the financial services industry are rapidly adopting predictive analytics as a way to gain a competitive edge, and to deliver higher-end customer experiences. As per the Forrester report, 89% of global data and analytics technology decision-makers in the financial services industry placed real-time/predictive analytics in the high-priority category. They said they either already implemented the technology, have begun the implementation process or are planning to introduce it imminently.

The sheer amount of sophisticated data collected by banks and fintechs has led to further development of a wide suite of internal and client-facing tools that target specific customer needs.

Despite the many personal finance tools and resources available, an understanding of finance fundamentals is still a gap for many customers. The 2022 Investopedia Financial Literacy Survey found that only around half of Americans have a strong grasp of financial literacy basics like budgeting, saving and spending. Even fewer felt confident in their knowledge of investing and digital currency.

A lack of confidence and trust can lead to poor decision-making, and sometimes deter customers from making decisions at all. This underlines the importance of looking to your data for signs of customer indecision or low confidence. When natural language processing and other AI applications are considered, speech and text analytics can be of great value for industry brands. Mining unstructured data from voice- and text-based interactions (email, chat, social media, SMS, etc.) with customer support teams can yield untold customer experience insights.

In the ideal situation, insights unearthed by customer analytics and AI can help banks to develop comfort levels among their customers. This is not only true on the level of the individual customer, but also at a higher level that enables banks to pick up on trends and create solutions that help customers make sound financial decisions.

The benefits of predictive analytics in banking

From a customer experience perspective, predictive analytics are the gateway to data-driven personalization. Many financial institutions have the data at their disposal, but can miss the mark when creating personalized experiences that resonate with their customers, notes a J.D. Power 2022 U.S. Retail Banking Satisfaction Study.

"It's no longer predominately about being fast, efficient or convenient," says Jennifer White, senior consultant of banking intelligence at J.D. Power, in a press release alongside the survey data. "The preeminent performance metric with the biggest influence on customer satisfaction is 'supporting customers during challenging times,' and that means customers are expecting a personalized mix of financial advice, hands-on help with problem resolution and guidance on how to grow their money."

According to the J.D. Power survey, 46% of respondents feel the most critical part of personalization is getting help avoiding fees for things like overdrafts, while 37% say they want to receive account alerts. Predictive and real-time analytics can help make both those wishes come true because of how adept the technologies are at identifying anomalies and predicting outcomes. Being able to alert customers of potential overdrafts, detect odd and potentially fraudulent spending and propose debt management solutions are examples of analytics in action.

These solutions are low-hanging fruit for banks and other financial services providers. More sophisticated and bigger-picture ideas include AI-powered modeling in customer product design and uptake, and determining creditworthiness more equitably by looking beyond past borrowing history and instead including a broader set of data points to determine eligibility. They can also more accurately predict (and lower the cost of) credit risk.

Internally, your contact centers can benefit from analytics technologies that predict client issues and supply support agents with the exact information they need to solve issues quickly — a powerful tool that helps improve critical KPIs like average handle time and first call resolution.

Predictive and data analytics are even useful in managing your staff. They can identify gaps in customer experience training and knowledge bases, helping you to better target skills training opportunities.

In today's market, financial services providers are feeling an elevated sense of urgency to up their data game as customers look for banks and fintechs that deliver a more refined, personalized customer experience. Developing and effectively implementing predictive analytics takes time and resources — both of which can be saved by working with a trusted partner with experience in both the banking industry and disruptive technology.

Banking decision-makers are prioritizing investment in predictive analytics. Learn why the technology is generating interest.

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Appreciating the value of predictive analytics in banking

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Learn how a leading technology client leveraged TELUS International’s AI Data Solutions to build a multilingual dataset that helps researchers scale natural language understanding technology.

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Building a multilingual dataset with high-quality data collection and annotation

Discover TELUS International’s end-to-end AI data capabilities, delivering human powered data backed by advanced AI training tools.

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"In the pursuit of creating truly remarkable customer experiences, we must embrace the power of generative AI," explains Alexander Grayson, founder and CEO of AI-led start-up, Quixl. "It allows us to think differently and break free from the constraints of conventional wisdom, propelling us into a realm of unimaginable possibilities."

Grayson makes a convincing case for the role of artificial intelligence (AI) in the future of digital customer experience (CX).

There's just one problem. Neither Alexander Grayson, nor Quixl, exist.

The Silicon Valley-based tech firm and its enigmatic founder are a construction of OpenAI's ChatGPT-4, one of many wildly popular generative AI applications on the market today, like Google's Bard and Amazon's Bedrock. With some prompt engineering, the technology swiftly took up the role of a successful founder of a start-up with an ambiguous name. Alexander Grayson even has a favorite food (sushi) and a reason for loving it so much ("it combines simplicity with artistry").

Fake though he may be, Grayson's belief in the power of generative AI (or "GenAI") is shared by many real people at very real organizations. Take AWS' Vice President of Generative AI, Vasi Philomin, who, in a recent interview with TechCrunch, said, "We think every application out there can be reimagined with generative AI."

Researchers are aligned too. In fact, Grand View Research projects that generative AI's market size will reach over $109 billion by 2030 thanks to an expected compound annual growth rate (CAGR) of 35.6%.

The market growth and pace of innovation is making artificial intelligence and bot technology impossible to ignore for digital customer experience decision-makers.

Tip: If you're looking to learn more about the underlying technology, give our Generative AI 101 article a read.

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