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On this episode, we ask big questions about how customer loyalty is formed — and how AI can be leveraged to build stronger connections with customers.

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What does customer loyalty look like in the age of AI?

Discover how knowledge management can boost organizational success. Explore challenges, best practices, trends and more.

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knowledge management

Navigating knowledge management: A complete guide for success

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Explore the transformative potential of Contact Center-as-a-Service (CCaaS) solutions and learn how to navigate the evolving landscape of AI-driven customer interactions with this executive brief from Frost & Sullivan sponsored by TELUS Digital (formerly TELUS International).

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The CCaaS breakthrough: Redefining customer interactions with AI

The eCommerce checkout is the most overlooked part of the customer journey. Here are four of the biggest customer pain points, and tips on how to solve them.

e-commerce checkout CX

How is your mobile and web checkout affecting your customer experience?

Join Ajinkya Malasane, senior director, product strategy and marketing for TELUS Digital (formerly TELUS International), and Vikram Chatterji, co-founder and CEO of Galileo, a generative AI (GenAI) evaluation company, as they provide efficient and effective ways to solve key GenAI project blockers for easier deployments.

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Crafting production-grade GenAI applications

Discover how TELUS Digital helped a world-leading communications and technology company streamline workflows and enhance its quality standards by leveraging a cloud-native development strategy and advanced automation solutions, including AI-powered test-driven development (TDD).

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Optimizing app development with cloud-native solutions and automation

Optimizing application development with cloud-native solutions and automation

Watch this recorded webinar from Everest Group and TELUS Digital (formerly TELUS International) for new insights to help you skillfully transform your digital customer experience.

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Webinar: How to supercharge your CX with AI-fueled digital transformation

How to supercharge your CX with AI-fueled digital transformation

Robert Zirk: What will your business model look like 10 years from now?

Even if you're still selling a similar product or service, your value proposition may have evolved. And over that span of time, the preferences of your customers most certainly will.

As the adage goes, change is constant. Customer behaviors and expectations are always in flux. And it's up to businesses to keep up.

In a Salesforce survey of more than 6,000 consumers, nearly two thirds of respondents said they expected companies to align with their evolving needs and preferences. And a Microsoft report highlighted that 77% of customers view brands that solicit and implement their feedback more favorably.

Frank And Oak is one of those brands that has strived to adapt to customer behaviors and feedback since it was founded in 2012. Back then, according to their website, the company's mission was to "create an apparel brand that would speak to a new generation of creatives and entrepreneurs," and it initially operated on a monthly membership model as an online-only menswear retailer.

Fast forward to 2024, and a lot has changed.

Nadia Famularo: We went from being menswear only and online-only to having both online and brick-and-mortar, adding a women's line.

Robert Zirk: That's Nadia Famularo, director of operations and customer success at Frank And Oak.

Nadia Famularo: And, over time, as we understood where the market was, where our customers were, what they really wanted evolved into a more kind of an everyday lifestyle brand.

Robert Zirk: Having been with the company in a variety of roles through many of these changes, Nadia shares insights on this episode that are valuable to business and CX leaders across industries, covering data-driven decision-making, gathering and leveraging customer feedback and how technology plays an important role in delivering an effortless customer experience.

So today on Questions for now, we'll ask: What is the Frank and Oak secret for adapting to changing customer preferences?

Robert Zirk: Welcome to Questions for now, a podcast from TELUS Digital where we ask today's big questions in digital customer experience. I'm Robert Zirk.

The Frank And Oak of today is quite different from the company that launched back in 2012. Based out of Montreal, Canada, Frank And Oak began as an online-only menswear retailer with focuses on custom suiting and bespoke tailoring. And it operated on a membership model where customers could choose three articles of clothing that were thematically designed in-house. Once they received their monthly box, customers had a five day period where they could try on the clothes. They'd keep the items they wanted and return the ones they didn't using the included return box.

But as Frank And Oak started to better understand its customers through the technology it used to offer personalized service, the brand's strategy began to branch out.

In 2013, Frank And Oak opened its first permanent retail location. Just two years later, it would have six stores across Canada. And in 2016, following thousands of requests from customers, the brand added womenswear to its apparel line.

A 2015 BetaKit article quoted co-founder Ethan Song describing Frank And Oak as "a tech-first company" where "the experience is the product," highlighting "community, personalization and integration" as the most important building blocks for a brand.

Its omnichannel strategy sought to make shopping for clothes less transaction-focused and more experiential, with its flagship retail location integrating a café and a barber shop and its website featuring a chatbot and team of stylists ready to help customers by making personalized recommendations.

And while the overall experience is still at the forefront for Frank And Oak, the company redefined its mission in 2017 when it pledged to focus on sustainability, starting with more sustainable apparel – a counterpoint to the popularity of fast fashion throughout the 1990s, 2000s and 2010s, informed by a growing number of consumers looking to make more environmentally-conscious buying decisions.

Nadia explained how sustainability is at the heart of Frank And Oak today.

Nadia Famularo: A lot of our products are responsibly produced using more sustainable fabrics, recycled polyester rather than virgin polyester, et cetera. And we try to bring the sustainability mindset to not just the clothing that's produced, but the way we operate as a business as well. And so we're present online, and also we have over a dozen stores across Canada where we do business.

We've had a chance to really become a leader, especially in the Canadian fashion space. We became B Corp certified several years ago.

Robert Zirk: According to B Lab, the non-profit network governing the certification, B Corps are companies that have been assessed as meeting high standards of social and environmental performance, accountability to all stakeholders – not only its shareholders – and transparency in their operations.

Nadia Famularo: We have partnerships with organizations like Earth Day Canada. And with that, I think, as we've seen across industries, there's been more of a call to action, but also just more of a desire to see sustainability in everything that we do.

Robert Zirk: And that coincides with a generational shift toward personal, social and environmental values, like sustainability, as an increasingly important purchasing factor for customers. A McKinsey survey of US-based customers showed that 75% of millennials consider sustainability in their buying decisions, compared to 66% of all respondents. And according to a First Insight survey, 62% of Gen Z consumers prefer to buy from sustainable brands. Brands can't afford to treat sustainability like a trend that goes in and out of style. Sustainability is what a growing number of customers expect.

Today, Frank And Oak's website describes its purpose as to "inspire a better way of living by creating conscious products that last through time." That includes designing its clothing with eco-friendly materials and sustainable processes, reducing the amount of packaging it uses in shipping while also using recyclable or compostable options and even making use of locally-sourced or upcycled furniture in its retail stores. Beyond manufacturing a more sustainable product, Nadia highlighted how Frank And Oak's commitment to sustainability plays a leading role in the decisions it makes as a brand and as a business.

Nadia Famularo: We're just continuously trying to find ways to add more sustainability and more eco-conscious ways of doing things across our business. We have some partnerships in our fulfillment and last mile part of the business. For example, we partner with GoBolt, which is a Canadian-based company as well, to provide electric vehicle delivery to a lot of our key markets. And so with that, a lot of our deliveries across Montreal, Toronto, Vancouver – the biggest cities in Canada, but also naturally where our biggest customer bases are – can benefit from that sustainable experience.

Robert Zirk: According to a Statista survey, nearly eight out of 10 shoppers worldwide would consider a more sustainable delivery option when they order online. And a survey from Stuart, a last mile delivery platform based in Europe, found that 27 percent of consumers in the UK would be willing to pay more for a delivery that's eco-friendly.

I asked Nadia what specifically prompted Frank And Oak's pivot to a focus on sustainability.

Nadia Famularo: Customers have just been getting smarter about what they buy, the intent with which they buy: do they want something that they're going to wear once? Is it something that they're going to want to buy and then wear over time? And so that's also part of, beyond the sustainable production of our clothing, is the quality and the longevity and the adaptability of our clothing to the everyday lifestyle of the Frank And Oak consumer. And so that also is just naturally where our customers are evolving to as well. And buying for quality rather than quantity, for example.

Robert Zirk: Although the global subscription box market continues to grow, with an imarc report estimating a 14% annual growth rate and $105 billion market value by 2032, the continued drive for sustainability led to the discontinuation of Frank And Oak's Style Plan subscription service in 2021, which had been launched three years earlier as an adaptation of previous membership programs.

Nadia noted that while the COVID-19 pandemic and a decrease in discretionary spending among consumers accelerated that particular change, sustainability and the customer experience remain the deciding factors for how Frank And Oak moves forward to meet customer expectations.

Nadia Famularo: Ultimately, the subscription was not sustainable on many fronts including the high return rate that comes with a model like that. And so, adding shipments to and from customers constantly on a monthly or bimonthly basis, when you go behind the curtain a bit, it increases our carbon emissions. It increases the shipping. Instead, we've shifted away from that, really focused on driving more meaningful customer experience online and in stores more regularly.

And our store associates are also really versed in our products, can make suggestions, but it's also a great customer feedback point for us, too. We can understand more conversationally rather than just checking off a box on a form, like, what was wrong with the product? Why are they returning it? And then be able to make really personalized recommendations on how to adjust further and then also share that feedback through our internal feedback loops as well.

Robert Zirk: Technology has played an important role in shaping how Frank And Oak continues to strive for a more sustainable customer experience. A recent change is the introduction of omnichannel fulfillment, where inventory could potentially be shipped from a nearby store location rather than the warehouse.

Nadia Famularo: It's more strategically thinking about where inventory is positioned so that if you're ordering in Vancouver...

Robert Zirk: ...on Canada's west coast...

Nadia Famularo: ...and our store in Vancouver has all the items you're ordering, rather than having that order shipped from somewhere in Ontario...

Robert Zirk: ...which is about 2,100 miles or 3,400 kilometers east...

Nadia Famularo: ...we can ship it from there. So it's a shorter distance traveled, whether it's electric vehicle and already carbon neutral, or just offset - regardless, the emissions of shipping that order will be lesser. It's a faster delivery time for the customer overall, a more cost effective one also.

The technology to be able to roll that out required a lot of investment and integration in our tech stack. So it involves introducing a new OMS or order management system that can help route our orders more intelligently to the right location.

There's a logic there as well, in terms of order orchestration, that's very driven by tech and automations to match up where the customer's ordering from, which store location has the full order for the customer if you're ordering multiple items. Does the store have all of the items? Does it have three out of four? So three will ship from there to benefit from that closer distance, that better kind of inventory positioning and have another one come through as well.

Obviously we try as much as possible to ship an order in one package, right? And then it's the fine line of when you think of sustainability, how many packages are we willing to split up that order into to get the customer all the items they want, or on the other side, from a business perspective, do we not share that that inventory can be sold to a customer depending on if it's available only in a store versus our warehouse, for example?

Robert Zirk: Automations and data insights also help in terms of inventory planning, allocating types of apparel based on regional climates and customer profiles. And on the ecommerce side, customer data is also leveraged with AI to create personalized recommendations.

Nadia Famularo: So rather than a group of people curating things, we can read customer data to understand what products are they most likely to buy? Mirroring, let's say, this customer bought one of our skyline bombers in black, and they also bought these other things. Maybe another customer who bought that same bomber jacket will also be interested in the same product. And being able to make recommendations around that based on customer profile, building more dynamic product feeds on our website and our email content to customers so that it's more relevant and essentially, hopefully, converts into a more successful customer experience purchase. You're being served the content you want and you're more likely to be interested in not just based on anecdotal or kind of gut feeling things, but based on what kind of more measurable insights that we can get from technology and data.

Robert Zirk: According to an Everest Group survey supported by TELUS Digital, CX leaders identified personalization and customization of customer interactions as the number one reason to consider generative AI solutions in their CXM operations. Looking toward the future, Nadia highlights that Frank And Oak is continually looking for new opportunities to leverage automation and AI, but in a way that maintains the humanity that comes along with the brand experience.

Nadia Famularo: I think the challenge is to understand how to do that responsibly and not over commit in any kind of way to leaning into only AI and automation, for example. I think there's been a lot of learnings that we've been able to gain from those already in terms of the product recommendations and understanding our inventory in certain ways. But I think, ultimately, it's identifying some of the key touch points where we can reasonably rely on those to enhance the customer experience without taking away from what we also want to protect as our kind of very personalized experience and keep that kind of very human connection with our customers as well.

Robert Zirk: And while technology plays a critical role in creating a personalized customer experience, Nadia noted it can have an equally important influence on the agent experience. In understanding the intricacies of the customer service agent role, having started her career with Frank And Oak as one herself, she emphasized the importance of ensuring agents have the right technology and processes at their disposal.

Nadia Famularo: We, our CS team, relies on an internal CRM tool and through working with our tech team, we're able to integrate a lot of our different tools and platforms to help the customer service agent have a quicker response time, find the answers to their questions more easily, be able to serve the customer. Ultimately, it's about the efficiency that we're able to provide to the team. And so you move from having a smooth customer service agent experience to them having a smooth er customer experience as well.

Robert Zirk: In an Eagle Hill Consulting survey of 1,000 US-based employees in a variety of industries, 67% of respondents said that technology improves their ability to assist customers. The same survey noted that 70% of respondents say their productivity is directly affected by their day-to-day work experience.

High-quality digital tools and streamlined processes that reduce agent effort translate to a better customer experience. And better customer experience means increased profitability.

That aligns with research from Deloitte, which shows that customer-centric companies were 60% more profitable than companies that didn't prioritize their customers. And a Forrester report found that the brands who excel at delivering customer experience generate 5.7 times more revenue than rival brands who aren't as proficient.

One of the key ways Frank and Oak maintains a customer-centric focus is by gathering customer feedback and then combining it with quantitative metrics to gain a holistic understanding of consumer behavior and preferences to make decisions accordingly. Nadia stressed the importance of finding the right balance between the quantitative data and qualitative data as the company continues to grow in a sustainable way.

Nadia Famularo: There's definitely a balance to be had of that. But you need both, always. An anecdotal piece of customer feedback might be a customer saying what they think they want, but the real truth lies in the bigger picture of what the data tells us and helps us understand our customers in a lot of different ways. and as much as we can trust our instincts and our gut feelings in some cases, it's often not enough to get buy in from other stakeholders when pushing customer experience initiatives or are trying to convey the importance of certain things that are impacting our customers.

Robert Zirk: One important point in the customer journey for feedback is customer returns. It's important for retail brands (and companies in other industries that have equivalents to return policies, like a satisfaction guarantee, for example) to ensure a smooth return process that minimizes customer effort. The Interactive Media in Retail Group, or IMRG, notes that 92% of customers who have a positive return experience will make another purchase from your brand. And Nadia reiterated that the reasons behind customer returns also provide important data about customer behavior and preferences.

Nadia Famularo: Why are they returning? Is it an issue with the product? Is it the fit? Is it the design? Is it the pattern? That can turn into insights for our design and product development team to inform their future collections. Or is it more that they didn't get their order on time and so they missed the chance to use the product? And so it's more about an operational SLA and a miss there that we need to address. There's so much around returns that is like a huge well of information that can help inform the customer journey and the customer experience.

Robert Zirk: Nadia described additional ways in which Frank And Oak gathers data to measure how well it's meeting sustainability and CX objectives.

Nadia Famularo: We have a number of touch points for customers to share feedback. So when thinking about the typical customer journey and their online order or their in-store purchase, we have post-purchase surveys where we capture feedback consistently. We have surveys through our customer service team as well to capture customer satisfaction on those interactions. Those are very direct customer feedback loops.

But then, beyond that, we can read into things like our SLAs - are we meeting our average time to ship the time that we say, or it'll take for an order to reach a customer? How much are we meeting that? And that becomes a proxy for customer satisfaction as well. Are we meeting that customer promise?

Beyond that, we also have product reviews on our site. Once you purchase something, you can leave a review on the product and that can tell us: Is there an issue with this product? Are customers looking for something else? Is there a new feature we could add to it that would further improve on customer satisfaction?

That helps us evaluate product performance itself and can have further actionable insights to our product and design team. And the reviews can also serve as a form of social proofing as well and when a product gets really great reviews, if other customers see that, it also encourages them to buy those as well.

Robert Zirk: However, Nadia noted that sometimes CX leaders tend to focus disproportionately on negative feedback, but a single criticism doesn't necessarily tell the whole story of what the majority of your customer base's journey looks like.

Nadia Famularo: You tend to zero in on some of those more negative experiences.

But then, when you can take a step back and look at the bigger picture, you'll see, "Oh, that's maybe a lesser portion of our customers are being affected by this." And they absolutely deserve to have that problem solved, but maybe it's not the bigger picture, the biggest problem that you thought it was, and it's really important to be able to take that perspective shift and take a step back from the one and look at the hundred or the thousand and how to best serve the majority that you can.

It's also nice when you take a step back and realize it's not as big a problem and it really helps with contextualizing things and keep control of what's a critical issue and what's not as critical and helps you prioritize and find what are the big initiatives that you can continue to pursue while solving smaller scale problems at the same time.

Robert Zirk: As we neared the end of our conversation, I asked Nadia for one piece of advice she had for CX leaders or emerging leaders listening to this podcast, and she referenced how crucial it is to be an advocate for your customers within the organization.

Nadia Famularo: Something that becomes really important is in your position, you are the voice of the customer internally, right? And it can become very challenging to get stakeholder buy-in sometimes, but you also always have to make sure that someone's leaving a seat at the table for the customer to be represented.

And it's not just purely about business goals, which should ultimately serve the customer, granted, but it would be to always remind people that the customer has a voice and it needs to be listened to with data and with actionable insights. But I think that would be the one thing is to not let the customer's voice go unheard.

And I think customers might tell you what they think they want, but ultimately as a customer experience leader, you have access to the data and the insights, the customer service feedback, to really know more tangibly and quantifiably what's really needed and how to make those recommendations to the business to respond to the problems that actually need to be solved.

Robert Zirk: Through this case study on Frank And Oak, Nadia underscored the importance of understanding customer behaviors and expectations, using customer feedback and data analytics to make informed decisions, and providing a seamless and personalized customer experience from both customer-facing and agent-facing perspectives.

I'd like to thank Nadia Famularo, director of operations and customer success at Frank And Oak, for joining me and sharing her insights on these topics today. And thank you so much for listening to Questions for now, a TELUS Digital podcast.

If you enjoyed today's episode and want to hear more compelling insights on all things digital customer experience, be sure to follow Questions for now on your podcast player of choice and make sure you're getting notifications every time there's a new episode.

I'm Robert Zirk and until next time, that's all... for now.

On this episode, we explore how eco-friendly apparel brand Frank And Oak evolved its business model to adapt to customer expectations — and how data, feedback and technology are used to optimize its CX strategy.

Episode cover image for Questions for now, a TELUS Digital podcast, featuring a character browsing an ecommerce website and pointing to a shirt with an eco-friendly tag.

Questions for now Frank And Oak image

Since publishing this episode, we've rebranded to TELUS Digital.

Founded in 2012 as an online-only menswear retailer, Frank And Oak used data and insights from customers to change course over the following decade, reinventing itself as a sustainable lifestyle brand with both an online and brick and mortar presence.

Listen for the informative insights of Nadia Famularo, director of operations and customer success at Frank And Oak, as she discusses how data-driven decision making influences Frank And Oak's business strategy, how the company leverages technology to enhance the customer experience and why CX leaders must ensure the voice of the customer is heard in their organizations.

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What is the Frank And Oak secret for adapting to changing customer preferences?

Contact center artificial intelligence (contact center AI) plays a pivotal role in enhancing the customer service experience through tools like chatbots, automated phone systems, intelligent email responses and more. This powerful technology has transformed how businesses interact with their customers — and organizations are adopting it at a record pace. According to research from Metrigy, over 70% of contact center leaders have indicated plans to ramp up their AI spending in 2024 and 2025.

What exactly is contact center artificial intelligence, and what should customer experience (CX) leaders consider when implementing it within their organization?

Contact center artificial intelligence refers to the application of AI technologies specifically designed to enhance and streamline customer service operations within contact centers. At its core, contact center AI aims to create a more intuitive, responsive and personalized customer service experience.

Contact center AI leverages subsets of artificial intelligence to understand, interact with and assist customers effectively. This includes natural language processing (NLP), which enables AI systems to understand, interpret and respond to human language in a meaningful and contextually relevant way. It involves several sub-tasks like tokenization (breaking down text into words or phrases), parsing (analyzing sentence structure) and semantic analysis (understanding the meaning of the text). In contact centers, NLP enables chatbots to comprehend customer inquiries, extract relevant information and generate appropriate responses.

Machine learning (ML) — a branch of AI that focuses on training algorithms to learn from data and improve their performance over time without being explicitly programmed — is also a critical component of contact center AI. ML algorithms can analyze vast amounts of historical data to identify patterns and trends. In customer service, machine learning can be used to predict customer needs, suggest next-best actions for agents and identify common issues. For example, if a significant number of customers are reporting a particular problem, ML algorithms can detect this trend and alert company leaders to take action.

There are many different applications of AI for the contact center. With the recent popularity of generative AI (GenAI) within customer experience operations, contact center AI capabilities are expanding exponentially.

Some examples of contact center AI in action include, but are not limited to:

Conversational bots: Also known as chatbots, these software applications simulate human conversation through text or voice-based interactions. They use natural language processing and machine learning to understand and respond to user queries or commands. To manage voice-based interactions, chatbots utilize automatic speech recognition (ASR) technology, which converts spoken language into text. In customer service, chatbots are effective for handling simple inquiries and tasks around-the-clock, reducing the need for direct interaction with human agents.

Agent assist bots: This technology provides real-time support to human agents by offering instant suggestions related to customer queries, retrieving customer data, automating routine tasks and more.

Robotic Process Automation (RPA): RPA involves using software robots, or "bots," to automate repetitive, rule-based tasks that human agents typically perform. Robotic process automation can handle various tasks, including data entry, transaction processing, report generation and customer record management. For example, if a customer updates their contact information in a self-service application, RPA can automatically capture this new information and update all relevant systems and databases in real-time.

Voice biometrics: Voice biometrics analyze voice patterns to authenticate users, considering factors like pitch, tone and speech rhythm. They can enhance security in the contact center by verifying a customer's identity through their voice, reducing the need for passwords or security questions.

Analytics and reporting: AI-driven analytics tools collect and analyze large volumes of data from customer interactions. One key application is sentiment analysis, which uses natural language processing and machine learning algorithms to identify and categorize emotions expressed in text or speech. By detecting positive, negative or neutral sentiments, sentiment analysis helps gauge customer emotions during interactions. This information can be used to prioritize responses, escalate issues to human agents when needed and tailor responses to enhance customer satisfaction. Insights like these enable businesses to understand customer behavior, identify trends, measure the effectiveness of support strategies and make informed, data-driven decisions.

Each tool within the contact center AI suite has its unique advantages, contributing to a more streamlined and effective contact center operation. 

Some of the most common benefits include:

According to the aforementioned research by Metrigy, the primary driver behind increasing AI contact center spend is the promise of efficiencies. By automating repetitive tasks such as answering FAQs, processing orders and gathering customer information, contact center AI applications like RPA and chatbots free up human agents to focus on more complex interactions.

For example, a large global technology company faced challenges with long average handle times and low customer satisfaction due to the manual data entry tasks required of its contact center agents. To address these issues and enhance both employee and customer experiences, the company engaged TELUS Digital to implement a custom RPA Solution. The solution incorporated feedback from frontline team members at the organization and involved connecting disparate systems with an application programming interface (API) to eliminate manual steps in the company's processes. Implementing RPA resulted in a 22% decrease in average handle time, a 35.3% increase in call capacity and an overall improvement in customer experience.

Contact center AI's enablement of self-service options, such as chatbots and interactive voice response (IVR) systems, also plays a primary role in enhancing efficiencies, as they empower customers to handle simple queries without engaging with a live agent, according to Max Ball, principal analyst at Forrester. "AI gives you a lot of power; it allows you to do more in self-service, which is really valuable," he said in the webinar Driving CX success with AI and automation in CCaaS, hosted by TELUS Digital. Ball further explained that the ROI of self-service is significant, making the implementation of AI in the contact center a "no-brainer." He emphasized that brands should capitalize on AI capabilities as much as possible to maximize their benefits.

And with contact center AI's ability to predict call volumes and optimize staffing levels, its efficiency benefits also extend to workforce management. AI can accurately forecast demand and adjust staffing levels by analyzing historical data and real-time interaction patterns. It can help ensure that the right number of agents are available during peak times, thereby reducing customer wait times and preventing overstaffing during slower periods.

When employees are equipped with the right tools, training and support, they can perform their jobs more efficiently and with greater satisfaction. This translates to more engaged and motivated agents who can better assist customers, resolving issues quickly and delivering exceptional service. Additionally, increased job satisfaction leads to lower employee attrition, reducing the need for costly retraining.

Contact center AI tools help reduce the cognitive load on human agents by providing real-time information, suggested responses and automated call summaries. Research by HubSpot shows that "78% of customer service professionals believe AI and automation allow them to focus more on the most important aspects of their roles."

For example, a growing consumer robotics company looking to maximize the performance of its customer support agents engaged TELUS Digital's automation experts to implement an agent-assist chatbot. By training the bot on information housed in the company's existing knowledge base, agents could look to the bot for help in navigating company and product information. The bot is capable of effortlessly surfacing the correct information, as well as tips, scripts and reminders. Implementing the agent-assist bot improved agent satisfaction by 37%, lengthened tenure for in-house agents and reduced the learning curve for new hires, decreasing the ramp training time for the client's growing CX operation.

With countless customer interactions occurring across multiple channels daily, there is a vast amount of data rich with essential insights waiting to be mined. AI-powered contact center analytics tools can analyze the data to identify trends, uncover insights and generate actionable recommendations, such as determining where to use chatbots, when to hand-off to the right agent and much more.

In the aforementioned webinar hosted by TELUS Digital, Ball noted that 100% of interactions in the contact center are recorded, but only a very small handful (1%) of those interactions are actually reviewed for quality assurance or other insights. "It was data that was just dead. It was too hard to get to, you had to listen to recordings and it didn't make sense to leverage it. There was no way to get value there."

But with AI making speech-to-text effective, 100% of contact center calls can now be transcribed, and all of those transcriptions, added Ball. This gives companies greater visibility into their contact center operations. "That data is now accessible; that data is now sharable. This is the real voice of the customer. The insights that are available here are huge."

While the benefits of contact center AI applications are significant, organizations can face challenges in their adoption and implementation. Understanding these obstacles is crucial for overcoming them effectively and ensuring seamless implementation. 

High initial costs: Implementing contact center artificial intelligence involves significant initial investments in technology, infrastructure and training.

Integration with existing systems: Ensuring that AI tools work seamlessly with existing customer relationship management (CRM) systems, databases and other contact center software is critical to avoid disruptions in service and data flow. However, some contact centers operate on legacy systems that may not be compatible with modern AI technologies. Integrating contact center AI into these outdated systems can be complex and costly.

Data quality and management: AI's effectiveness depends on the quality of data it learns from. Inaccurate or incomplete data can lead to poor performance and misguided insights. Moreover, some organizations may store their data in disparate systems, creating silos that hinder AI from accessing a comprehensive view of customer information.

Data privacy: AI systems require access to large volumes of data — sometimes including sensitive customer information — to function effectively. Ensuring this data is collected, processed and stored in compliance with stringent data protection regulations, such as GDPR, can be complex. Additionally, brands must safeguard against data breaches and unauthorized access, as any lapse in security could erode customer trust and result in significant legal and financial repercussions.

Change management: Introducing AI to your operations can lead to apprehensions among employees about job displacement and changes in their roles. Resistance to change can impede successful contact center AI (CCAI) implementation.

Optimizing the user experience: According to Statista, almost half (48%) of consumers said that if it made their CX with a brand more seamless, consistent and convenient,  they would interact with AI more frequently. With that said, ensuring that AI interactions are smooth, intuitive and effective is crucial. Poorly designed AI systems can frustrate customers and negatively impact their experience.

Balancing AI and a human touch: According to a report by Execs In The Know, sponsored by TELUS Digital, 40% of consumers listed "difficulty reaching a live person" as the most frustrating aspect of resolving a customer care issue with a brand. While AI can efficiently handle routine tasks, it lacks the empathy and nuanced understanding that human agents provide. Ensuring customers feel valued and understood requires a seamless integration where AI manages simple inquiries, while complex or sensitive issues are escalated to human agents.

Monitoring and maintenance: AI systems require continuous monitoring, fine-tuning and maintenance to perform optimally, which can be resource-intensive.

Implementing contact center AI can elevate customer service operations, however, to reap the many benefits of the technology, it's important to follow best practices that ensure a smooth and effective deployment. 

Define clear objectives: Before diving into implementation, outline your specific goals. Are you aiming to reduce call handling times, improve first-call resolution rates or enhance customer satisfaction? Clearly defined objectives will guide your AI strategy and help measure its success.

Start with pilot projects: Small-scale pilot projects are a great way to test the effectiveness of AI solutions in your contact center environment. Pilots allow you to gather valuable data, identify potential issues and make adjustments before a full-scale rollout. Choose a manageable segment of your customer interactions to start, such as handling common queries or support requests.

Ensure data quality and integration: As previously mentioned, high-quality data is the backbone of any AI system, making effective knowledge management essential. Knowledge management tools, practices and personnel play a crucial role in maintaining data integrity by ensuring that information is accurate, relevant and up-to-date. These systems help in organizing and curating the data that AI systems use, setting them up to deliver more accurate insights and recommendations. Integrating AI with existing CRM systems, knowledge bases and other relevant platforms enables seamless access to comprehensive customer information. This integration ensures that AI can interact with the most current and complete data, leading to more accurate and personalized customer interactions.

Keep humans in the loop: It's critical to ensure that the path from AI tools to speaking with a human agent is easily accessible, allowing customers to reach a real person without frustration or delays. Striking the right balance between AI and human agents involves carefully designing workflows so AI enhances, rather than diminishes, the customer experience, maintaining a personal and empathetic touch in interactions.

Focus on user-friendly interfaces: For AI to be effective, it must be user-friendly for both customers and agents. Design interfaces that are intuitive and easy to navigate. Train your agents to work alongside AI tools, leveraging their capabilities to provide better service rather than seeing them as replacements.

Prioritize continuous learning and improvement: AI systems learn and improve over time through machine learning and natural language processing. Continuously monitor AI performance, gather customer and agent feedback, and make iterative improvements. Regular updates and fine-tuning are essential to maintain high performance and adaptability to evolving customer needs.

Maintain transparency and trust: According to a TELUS Digital survey, over 70% of Americans said they expect companies to be transparent in how they use generative AI. Customers should be informed when they are interacting with an AI system. Transparency builds trust and sets clear expectations. "[Companies] should also disclose how they collect, use and protect customer data, as well as the benefits and risks of data sharing," wrote Michael Ringman, chief information officer at TELUS Digital in a Forbes article. "Clear and easy-to-understand privacy policies that explain customers' rights and choices regarding their data should also be communicated."

Invest in security and compliance: Implement robust security measures to protect data and comply with relevant regulations. Regular security audits and updates are necessary to safeguard against breaches and maintain customer trust.

Monitor metrics and key performance indicators (KPIs): Track metrics and KPIs such as customer satisfaction scores, average handling time and resolution rates to evaluate the effectiveness of your AI implementation. Data-driven insights will help you understand AI's impact on your contact center operations and identify areas for further enhancement.

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