The Promising Future of AI Translation in CXM | Blog

Driven by new technological innovations, Artificial Intelligence (AI) translation holds the promise to reshape the customer experience by transforming conversation channels, increasing agent efficiency, and reducing the need for language specialist talent. Read on to learn about the potential for the CXM industry as well as the obstacles that need to be overcome before AI platforms can eventually replace human agents.

While machine translation (MT) has been used for more than five decades, recent developments in AI and neural machine translation models have sparked new interest in AI translation to improve customer experience.

Today’s AI engines are being trained to translate 1000-plus human languages in real time and develop the ability to understand large volumes of text data. These innovations are revolutionizing the CXM industry by increasing agent efficiency and accuracy.

While the advances have just started and developing the ability to translate instantaneous voice conversations will take some time, AI translation’s potential is generating a lot of excitement. Let’s explore its promise further.

What is AI translation?

AI translation is a machine translation process using complex algorithms to understand the source data in its original language and translate it into a wide range of other languages.

Advanced AI/ML technology has improved machine translation accuracy, enabling it to better mimic the human brain’s ability to process spoken and written words and comprehend phrases, voice tones, complex sentence structures, and human sentiments.

Impact of AI translation technology on the traditional customer experience management (CXM) industry

With its people-heavy operating model, the traditional CXM industry has always struggled to attract and retain talent, which is especially difficult when language skills also are required.

Many service providers have invested heavily in building multilingual hubs in a broad spectrum of locations and recruiting agents from around the world or in training to improve language proficiency.

However, meeting the vast language and dialect diversification needs across the globe is nearly impossible and puts huge financial pressure on service providers to provide language capabilities in every spoken language a client may require.

This is why AI translation is a real game changer in CXM. It is already transforming conversation channels, increasing agent efficiency, reducing the demand for human language talent, and saving huge operational expenses – and additional opportunities still exist for further development.

Pros and cons of AI translations

Customer satisfaction and agent efficiency are major deciding criteria for companies in selecting a CXM service provider. Research has shown that customers feel more appreciated when they interact with an agent in their native language, positively influencing their buying decisions and increasing customer brand loyalty.

Using AI translation to respond to customers’ queries can offer numerous advantages, including the ability to offer services in many diversified languages and dialects through omnichannel conversation platforms such as chat, email, voice, and social media in the local language.

Other benefits include:

• Increased agent efficiency and speed for agents who may be slower working in a second or third language
• Reduced need for a multilingual talent pool
• Faster time to proficiency of agents
• Decreased need for sites in local countries

Currently, AI translations primarily are used for text data translation. With expanding data libraries and AI engine training, text data translation accuracy is improving rapidly. But to have broader application success, AI translation must:

• Expand beyond simple, repetitive queries
• Gain insight into human emotions and sentiments
• Reduce contextualization errors to improve accuracy
• Acquire a full understanding of local nuances, tone, formality, vernacular, slang, and colloquialism
• Eliminate human supervision

Current AI translation technology can be inefficient and require human assistance to differentiate between normal conversation and exchanges involving humor or sarcasm. The inability to detect humor or sarcasm is less important in a customer service environment, as customers primarily want to resolve their issue. But it can create problems in content moderation where improper translations and misunderstanding the context of dialogues can lead to reputational losses for brands.

Use of AI translation engines in the CXM industry

To overcome these obstacles and benefit from advanced AI translation technology, many service providers leverage human linguists and digital translator tools to optimize resources.

Digital translator tools bring speed and efficiency, while human experts add accuracy and a personal touch. Combined, these solutions boost agent efficiency and performance by using AI for simple and standardized customer inquiries while transferring inquiries in hard-to-serve, low-volume languages to experts, simultaneously solving the problem of speed and accuracy.

Many service providers have partnered with technology providers to develop AI translation tools to serve their clients globally. For example, Concentrix Lingualab and Webhelp Polyglot combine best-in-class translation engines and machine learning tools with highly skilled language experts in centralized hubs to serve as multilingual service delivery centers. Another BPO provider, Majorel, with their Lingua, too combines machine translation, AI, and crowd-based human quality control.

What does the future hold?

Many technology providers are investing in building advanced translation tools to reduce machine translation engines’ dependence on human linguists.

Translation tools’ limitations will get resolved as AI engines build their content library with diverse languages, predictive replies, industry vocabulary, common phrases, knowledge articles, and vernacular, as well as its understanding of human emotions. The automated self-learnability of AI technology makes it possible to eventually replace humans completely.

Many technology giants also are now focusing on advanced speech translation engines. Meta Universal Speech Translator and Google AI language model are building translation engines that can translate more than 1000 languages.

Technology will also need to solve multiple issues to replace robotic voice delivery with the perfect human voice with flawless command over speech delivery speed, dialect, speaking styles, tone, and slang. And before AI agents fully replace humans, they will also need to understand human sentiments to appropriately reply to customers.

As voice translation tools evolve, they can revolutionize the BPO industry by completely replacing human agents with artificial intelligence platforms. But industry leaders estimate fully operational affordable real-time speech translation tools are still five to 10 years away. These advanced tools offer great potential to change CXM service delivery and transform the customer experience.

If you have questions or would like to discuss developments in this space, reach out to [email protected].

Learn about our Customer Experience Excellence Membership for deep customer experience research and strategy assistance.

And don’t miss our upcoming webinars, LinkedIn sessions, and events for more insight into what AI will bring and customer experience possibilities.

Customer Data Platform – The Torchbearer of the Personalization at Scale Movement | Blog

Customer Data Platforms (CDPs) enable brand marketing teams to build hyper-personalized campaigns and retain high-value loyal customers. Seizing opportunities in this growing market can set brands apart. Learn how to achieve personalization at scale in the second blog in our series.  

In our previous blog, The Rising Role of Customer Data Platforms in Data-driven Personalization, we explored the factors driving CDP’s fast growth of 25 percent in 2022. Let’s now look at how to choose a CDP to gain profitable business outcomes.

The dire need for personalization at scale

True personalization is when Spotify surprises listeners with discovery playlists, when Netflix delivers differentiated experiences to each family member, and when Amazon recommends the exact gift a shopper urgently needs. Personalization at scale happens when companies can perform activities like these for millions of customers, in real-time, and at every relevant time in the customer journey.

Making every customer feel valued and loyal to the brand is the power of personalization. This only can be accomplished by knowing what customers want without being told and delivering it on the right channel and at the precise time.

With the surge in customer touchpoints leading to a massive flood of data from disparate sources and increasingly stringent privacy regulations, delivering tailor-made content for tangible and sustainable business outcomes is direly needed. Marketers today must realize that consumers have an overabundance of options, and demonstrating that they know their consumers better than others is the only way to gain a competitive advantage.

The Customer Data Platform – packaged software that ingests data from multiple sources, draws consumer insights through unique 360-degree profiling, and activates channels – plays a pivotal role in achieving true personalization at scale.

Personalization technology – the role of the customer data platform

Building marketing teams to keep up with the growing customer base is the biggest hurdle enterprises face to personalization at scale. The latest technology can enable marketers to take the long leap from merely collecting demographic data to using Artificial Intelligence (AI) and Machine Learning (ML) to harness huge amounts of data from disconnected sources.

That’s where the Customer Data Platform comes in.

A CDP’s core function is to create unique customer profiles by collecting data from multiple sources, such as Customer Relationship Management (CRM) systems, websites, and email campaigns. To achieve personalization at scale, enterprises need best-in-breed platforms that not only collect data but also orchestrate personalized experiences at scale by using smart segmentation, behavioral scores, AI, and ML models that constantly optimize experiences based on real-time interactions.

Choosing the right CDP

Since one size does not fit all, enterprises need to dedicate time and resources to select the right CDP provider that offers expertise aligned with their personalization goals and the use case they prioritize.

Our research finds more than 160 providers offer expertise in these delivery areas and include both enterprise-grade CDPs (such as Salesforce and Adobe) and pure-play CDPs (such as mParticle and Treasure Data).

According to the CDP Institute, four main service categories exist based on capabilities in data, analytics, campaigns, and delivery, as illustrated below:

Exhibit 1:  Customer data platforms categories based on capabilities

Enterprises need to consider many factors when shortlisting CDP vendors, including marketing technology capabilities, vendor maturity, business use case alignment with the vendor’s core strengths, and pricing flexibility.

Evaluating technology features is extremely critical. The CDP Institute defines “shared features” as essential elements for a platform to qualify as a CDP and “distinguished features” as enhancements to the basic platform:

Exhibit 2: Features of customer data platforms 

People and process recommendations

Selecting the right CDP only solves one piece of the entire personalization puzzle. Enterprises also need to further optimize their internal operating models and align their teams with their overall business objectives to ensure success.

Below are the key elements needed to optimize people and processes to achieve personalization at scale:

• Setting goals – Marketers need to make sure the entire team is aligned with customer end goals before implementing any personalization technology.
• Removing silos – True personalization only can be achieved if customers have consistent experiences across touchpoints. As enterprises scale and these touchpoints increase, the number of teams that own them rises. This can lead to varied unconnected customer experiences across channels, provoking scenarios where the marketing team promotes a certain offer and the customer care executive denies it to the customer. Brands need open communication across teams to ensure alignment in tone and messaging.
• Hiring the right talent – In the talent war, enterprises find it extremely difficult to hire and retain the right type of data engineering and data science talent to achieve personalization at scale. Organizations need a talent strategy for their personalization efforts.

Although achieving sustainable personalization at scale can seem daunting, brands that gain the first-mover advantage will benefit by retaining loyal customers and increasing their lifetime value, reducing time to market, and improving workflow efficiency.

Consumers today expect sophisticated experiences that can predict their unspoken demands, and marketers must acknowledge this mindset paradigm shift to remain relevant. Brands that can personalize the customer experience at scale will differentiate themselves in the cut-throat marketing landscape.

To discuss Customer Data Platforms, contact Vaani Sharma at [email protected].

Learn more in our blog, How a Robust CXM Outsourcing Strategy Can Help Enterprises Navigate the Economic Downturn.

The Sports Marketing Playbook is Being Rewritten! Are you Ready? | Blog

The FIFA World Cup 2022 was a global arena for marketers and brands to display revolutionary technologies that create immersive fan experiences based on Web 3.0. But to be game changers in the sports industry, organizations will need to digitally transform their fan engagement, media, partnerships, sponsorships, and content, effectively rewriting the sports marketing playbook. Read on to learn recommendations and winning examples to ensure you don’t drop the ball.   

With over a million fans having visited Qatar for the World Cup, the tournament is expected to have been one of the largest sporting events for brands in the digital world. A plethora of brands and tech companies competed to score points by creating unique fan experiences at stadiums and off-location.

What differentiated this World Cup from others is how brands harnessed the hype with a range of digital assets, virtual worlds, Augmented Reality/ Virtual Reality (AR/VR) tools, and other Web 3.0-based solutions. In this blog, we explore this further and share some innovative use cases.

Digital technology is unlocking unprecedented opportunities in the global sports industry, valued at approximately $2.3 trillion. But to fully capitalize on this growth, sports organizations will have to go through a digital overhaul in four major areas.

Fan engagement

Organizations are leveraging technology to move from reactive to proactive fan engagement in the following ways:

Elevating the fan experience: Seamless fan engagement, both off-venue and on-venue, has become critical in providing a great fan experience, especially post-pandemic. Today’s fans expect more personalized and customized experiences across multiple channels. Cloud-based solutions and technologies such as AR/VR are being deployed to deliver these experiences to fans.

Developing robust loyalty programs: Sports fans have an unwavering loyalty towards their favorite teams and players. These fans are a notch above traditional customers as the sport is linked to their sense of identity.

Sports organizations are investing in loyalty programs to reward fans for their commitment and passion for the sport. These programs are also using digital assets such as Non-fungible Tokens (NFT) to incentivize their most loyal fans. Additionally, they are leveraging these platforms to create year-round engagement with fans to establish loyalty that extends beyond the game season.

Media management

The rise of digital media, coupled with the pandemic, has had a transformational impact on sports broadcasting and media.

Increased adoption of digital streaming platforms: Overall linear TV viewership has been declining due to factors such as the rise of streaming platforms, changes in the media landscape, and consumer behavior. This is no different in sports. Major leagues are signing digital broadcasting deals with streaming platforms, leading to increased ad spend on these platforms.

Leveraging influencer marketing: Sports has given rise to some of the world’s biggest celebrities, to say the least, and social media channels have turned them into influencers who are more accessible to their fans than ever before (Football star Cristiano Ronaldo recently became the first person in the world to surpass 500 million followers on Instagram, and these are not just followers, they are fans driven by passion!). Brands are leveraging platforms such as TikTok and Instagram to cultivate a personalized connection with fans through simpler technological innovations and highly engaging content.

Building digital infrastructure: A strong digital infrastructure in the form of websites, mobile apps, and Customer Data Platforms (CDP) is not only crucial to reach the target audience, but it is also a rich source of first-party data for sports organizations.

Partnership/sponsor management

Partnerships and sponsor management in the sports industry is also evolving past its traditional confines:

Moving from sponsorships to partnerships: Organizations are putting skin in the game to improve fan experience and build awareness for their brand through more purposeful and riveting partnerships, instead of just sponsoring a sporting event or branding jerseys and venues.

Evolving merchandising play: Sports merchandising includes sports-related equipment, clothing, and collectibles, among other things. E-commerce and social commerce are changing how fans purchase merchandise and with the advent of digital assets like NFT, the nature of the collectibles also is changing.

Content management

When games change in a fraction of a second, delivering content that resonates with fans at the right time and place is imperative. Here’s how it is being done:

Data-driven content: Technologies such as (but not limited to) optical tracking and wearables have given organizations access to newer and richer data points. While this data can help with decision making and team strategies, marketers are widely leveraging it to create content that can give fans unique insights and a more nuanced understanding of the game.

Dynamic and real-time content: Just like fast-moving sporting events, fans expect dynamic and real-time content. Organizations are relying on cloud-based solutions and AI-enabled tools to deliver the in-moment excitement and thrill associated with any sport.

A winner’s playbook to enable marketing in sports

To enable the new era of sports marketing, sports organizations need to build systems driven by intelligent automation, omnichannel experiences, and data, see the exhibit below.

Sports has always been and continues to be a force that brings people across demographics together. Digital advertisers and sponsors who manage to extend the passion, excitement, and loyalty fans have for their teams to their brands will see incredible results over time.

The stage is set, and the ball is now in the marketer’s court: will they become MVPs? Or have-beens? Only time will tell.

To discuss evolving marketing trends, contact Nishant Jeyanth and Mustafa Pitolwala.

Learn more in our webinar, How are Leading Organizations Delivering Exceptional Customer Experience?