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Happy customers are key to revenue, growth, and profitability.
However simple as it may sound, achieving enduring customer satisfaction isn’t easy. According to a report by Zendesk, over 50% of customers switch to a competitor after a single unsatisfactory customer experience.
Customer expectations are also escalating; 72% demand immediate service and the majority will pay more for a brand that solves their problems swiftly. Hence, for growth-minded businesses, the financial implications are significant; companies focused on CX see an 80% increase in revenue.
However, achieving lasting CX is challenging due to ever-shifting consumer expectations, the rapid pace of technological change, and the complexity of continuously analyzing vast amounts of customer data to refine the customer journey.
What is Generative AI?
Enter Generative AI. The technical buzzword of 2023, this compelling technology, which has been years in the making, burst into the landscape with its ability to generate human-like responses to questions, create images, generate audio, or interpret documents.
The latest advancements of Generative AI are even more potent. With the emergence of multimodal Generative AI tech, these systems can now understand and generate content that combines text, images, and audio, creating cohesive experiences that mimic human perception. They can interpret visual elements or glean information on web pages, documents, reports, and structured and unstructured data to generate more nuanced and informed answers.
How does Generative AI improve customer experience?
One of the domains where Generative AI technologies show great promise is in helping enhance customer experience.
Many of our customers are now conducting pilot projects using open source Generative AI models, leveraging cutting-edge cloud GPUs, fine-tuning and training AI models exactly on their company data, and injecting AI into their product or customer experience stack. Following are some key ways we have seen them harness Gen AI for CX:
Interactive and human-like chatbots
As mentioned before, today's customers expect immediate and round-the-clock support. Open-source large language models (LLMs), when customized with proprietary data, can adeptly handle customer inquiries in conversational language and deliver precise, real-time responses around the clock.
This reduces the necessity and expense of continuous human customer support and reallocates staff to address more complex issues necessitating personal attention. Eventually, this hybrid approach to customer support is what will prevail.
Moreover, with initiatives such as MEITY's Bhashini and IIT Madras's AI4Bharat fostering LLMs in regional languages, there's a growing potential to enhance customer experiences for India's vast non-English speaking population.
Tailored shopping experiences and recommendations
Personalization is the cornerstone of modern CX. When used effectively, generative AI models can tailor the shopping experience to individual customer preferences. One of the ways of doing that is through using Generative AI technologies like Stable Diffusion to create product images. In fact, in the near future, it will be possible to generate highly customized images specifically generated for individual customers.
It doesn’t just stop there. Self-hosted open-source Large Language Models (LLMs) like Mistral, Llama2, or Falcon can be fine-tuned on customer data safely and used to generate personalized product recommendations for an individual customer. This removes the risk of sharing sensitive customer information with proprietary AI platforms, where the company has complete control over its cloud infrastructure, customer data, and AI model.
Scaling marketing automation
Content is king in the digital marketplace, and a significant portion of it gets delivered to customers through personalized marketing. Marketing automation historically emerged as the technology to streamline and automate marketing workflows, enabling targeted marketing campaigns across various channels and personalizing interactions with customers.
Furthermore, the affordability and scalability of cloud GPU computing make it possible to generate high volumes of content without substantial financial outlays.
Real-time feedback and service adaptation
Generative AI brings an incredible ability to understand human language and can be harnessed to analyze customer feedback in real-time. This allows businesses to handle customer complaints rapidly while adapting their services to cater to customer needs. This enables companies to be more agile and responsive, thus continuously enhancing the customer experience.
The bottom line
Generative AI has the potential to redefine the frontiers of customer experience. Businesses can create highly personalized, efficient, and secure customer interactions by combining the power of open-source models, using advanced GPUs for inferencing, and training or fine-tuning the models on internal company data.
The message is clear: Adopting generative AI in CX is not just an option but imperative for future-proofing customer satisfaction and loyalty. As we step into an AI-driven future, the brands that embrace these technologies will lead the charge in delivering exceptional customer experiences.
Kesava Reddy is a Chief Revenue Officer of E2E Networks Ltd.
Image Source: Freepik
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