Personalization is profitable (when it works).
Connecting with customers on a deeper level is an undisputed game-changer in sales and brand development. Understanding the audience—their needs, preferences, and behaviors—leads to better problem-solving and conversions. For example, according to McKinsey, businesses that leverage personalization can achieve a 10-15% boost in sales.
And when they were first rolled out at scale, chatbots were supposed to deliver a new chapter in the story of personalization. Consider that in 2011, Gartner predicted that by 2020 customers “will manage 85% of their relationships with the enterprise without interacting with a human.”
However, a decade later, chatbots had hit the infamous Trough of Disillusionment in Gartner’s Hype Cycle—meaning their pitfalls had become more apparent than their promises.
To be sure, chatbots have helped reduce labor costs, helping companies cut down the headcounts of their once-huge customer service departments.
But truth be told, early iterations of chatbots left much to be desired. Why? Because they never truly lived up to the hype.
What’s more: companies seeking to cut down their short-term costs with cheap chatbots have ended up turning away long-term consumers.
Here’s where a Forrester Consulting survey’s findings are instructive, if not depressing: While most consumers welcome the 24/7 convenience of chatbots—and, in fact, want the option of chatbots, most give their experience a D grade. That same worldwide poll found that 40 percent of respondents rated their chatbot interactions poorly, largely due to the fact chatbots’ responses weren’t relevant to their inquiries.
The consequence of these bad chatbot interactions?
“Thirty percent of consumers,” per Forbes, “are likely to take their purchase to a different brand, abandon their purchase altogether, or tell their friends and family about their poor experience with the brand.”
That’s the bad news; here’s the good: Generative AI has turbocharged the capacities of chatbots to a point where they’ve rightly merited a new name entirely: virtual assistants.
Exponential advances in natural language processing (NLP) allow these virtual assistants to understand and adapt to nuanced conversations, making interactions feel infinitely more human-like. This quantum leap in capability has reshaped customer communication, providing a level of service that early chatbot technology could not achieve.
Personalization at Scale
Generative AI has begun enabling companies to deliver personalized experiences at scale, a development once thought virtually impossible.
Sephora first began deploying chatbots in 2016, but in recent years they’ve continuously upgraded their consumer-facing technologies, including aggressively adopting generative AI. The global beauty company now uses generative AI through its Virtual Artist to personalize the shopping experience by recommending makeup products based on customers’ unique skin tones, preferences, and past interactions. This AI-driven tool enables virtual try-ons and real-time, tailored product suggestions, enhancing customer engagement and satisfaction at scale.
The financial benefits of personalization are well-documented.
A Deloitte study highlights that brands offering personalized experiences see higher conversion rates, greater engagement and improved customer satisfaction—all of which spell greater consumer retention and lifetime value.
Breaking barriers
Another transformative aspect of AI-powered virtual assistants is their ability to break down barriers, whether linguistic or cultural. For instance, Telefónica, a global telecommunications company, uses a generative AI-powered virtual assistant called Aura to provide multilingual support for customers across various regions. Aura leverages natural language processing (NLP) to understand and respond to customer inquiries in multiple languages, helping Telefónica deliver personalized communication and improve customer experiences across diverse cultural contexts.
Creating new products and services
The most underrated benefit of generative AI lies not in customer service but rather in innovation. The data amassed and analyzed by generative AI provides companies with new opportunities to refine their current products and services as well as create new ones.
For instance, L’Oréal uses an AI-driven tool (appropriately called TrendSpotter) to analyze customer feedback and purchasing habits through its online platforms. By understanding preferences like skin type, concerns, and product choices, L’Oréal is able to not only refine existing products but also develop new skincare lines and makeup products tailored to specific customer needs. This approach allows them to stay ahead of trends and offer more personalized, solutions that resonate in near-real-time with their consumers’ changing demands.
The train has left the station
As generative AI continues to evolve, the companies that embrace this technology will position themselves at the forefront of innovation and customer engagement. Businesses that fail to adopt these advancements risk falling behind, losing relevance in an increasingly competitive market where customer expectations are rising. The future belongs to those who harness the power of AI to foster deeper, more meaningful connections with their customers, driving growth, loyalty, and long-term success.
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ABOUT THE AUTHOR
Titus Jumper , CEO, Jovee AI
With a visionary approach and a passion for innovation, Titus has built Sales Hub from the ground up, driving it to become a leader in the marketing industry. His expertise spans strategic brand development, digital marketing, and customer engagement.
Known for his entrepreneurial spirit and commitment to excellence, Titus inspires the team to deliver exceptional results for his clients. Under his leadership, the agency continues to thrive and achieve new heights in creative and strategic marketing solutions.