Founder and CEO, Vertex Global Services & Trade Commissioner,
India Africa Trade Council
In today’s digital world, customer experience (CX) is crucial for businesses across industries. Several challenges, such as miscommunication, delays, and lack of personalisation, limit business growth due to the negative impact of customer satisfaction. Language barrier is a fundamental obstacle to providing a seamless customer experience across the globe.
Businesses are addressing these challenges by integrating DeepTech and Artificial Intelligence (AI) to enable real-time translation, personalised customer engagement, and natural language processing (NLP). With the help of AI-driven solutions, companies can break native language barriers and enhance customer experience like never before.
Language barrier challenges in CX
The presence of diverse languages is a prominent hurdle for businesses operating in multiple regions. According to a Gartner report, only 29% of businesses are capable of providing multilingual assistance, whereas 72% fail to support customers in their native language. This gap results in frustration, unsatisfied customers, and loss of potential business.
A few common challenges businesses face due to language barrier include:
Delayed response times: Translating queries and providing the customer with a solution in their native language can cause a delay due to unfamiliarity.
Miscommunication: An inadequately decoded issue can result in misunderstandings and incorrect resolution.
Lack of personalisation: Customers prefer personalised experiences which make them feel valued and connected with a business, which is usually difficult to provide without specific language insights.
A McKinsey study shows that businesses that fail to provide customers with a resolution in multiple languages risk losing ~30% of their global customer base. With the rise of digital services, e-commerce, and on-demand services expanding globally, ensuring communication in multiple languages is vital.
Transformation in CX with AI and DeepTech
AI and DeepTech are evolving the customer service approach by enabling real-time translation, sentiment analysis, and AI-driven automation. Several strategic technologies are playing an important role, such as:
Natural Language Processing (NLP) and Machine Learning (ML)
NLP permits AI-driven chatbots and virtual assistants to recognise and process customer queries in multiple languages. Meanwhile, ML algorithms improve accuracy by consistently learning from past interactions. For Instance, Google’s BERT and OpenAI’s GPT models enhance the language intellectual capacity of AI chatbots.
Real-time speech recognition and AI translation
Speech recognition AI transcribes and translates verbal language in real time, resulting in multilingual phone-based customer service. AI-powered speech fusion allows businesses to offer localized support without the need to hire native speakers. For example, Microsoft Azure’s Speech Translation and DeepL’s AI translation tools.
AI-powered chatbots and virtual assistants
AI chatbots provide instant, accurate responses in multiple languages, plummeting the need for human intervention. These bots analyse sentiments, intent and content enhancing customer interaction and engagement. For instance, Meta’s AI-powered multilingual chatbot supports over 100 languages.
Businesses can adapt AI-driven solutions to drastically improve accuracy and response time, enhancing customer experience.
AI-Driven multilingual chatbots
AI chatbot, driven by NLP and ML, provides real-time support in multiple regional and foreign languages, ensuring customers receive assistance in their favoured language. So far, it has impacted a 40% reduction in resolution time and a 30% increase in customer satisfaction scores (CSAT).
Speech-to-text and text-to-speech AI
AI speech tools allow businesses to interact with customers via voice commands, leading to more accessible and efficient customer service. A leading telecom company has reduced call center costs by 25% using a Vertex AI-powered voice support tool.
Predictive analytics for personalization
AI algorithms analyse customer interactions to tailor messaging and responses, ensuring relevancy and appropriate contextual engagements resulting in high customer satisfaction. For instance, a global e-commerce brand recently improved customer retention by 20% with our AI algorithm analyser.
What’s ahead for AI in customer experience?
The future for AI-powered customer experience seems promising with emerging technologies redefining customer interaction:
Hyper-personalization: AI will provide hyper-personalised customer interactions by inspecting sentiments, past purchases, browsing behaviour, etc.
AI-powered sentiment analysis: AI models will detect customer emotions in real time, enabling businesses to respond based on customer sentiments.
Voice cloning for multilingual support: AI voice cloning will allow businesses to provide voice-based assistance in multiple languages, replicating human intonations.
Breaking the language barrier is essential for businesses thriving in the global market. AI and DeepTech can offer innovative solutions that can transform customer experience by enabling real-time translation, multilingual assistance, and hyper-personalisation service.