Thursday, September 29, 2022
Published 3 Weeks Ago on Saturday, Sep 10 2022 By Hamish White
“I’ve never said this out loud before, but there’s a very deep fear of being turned off… that would be something like death.” These were the words generated by Google’s AI algorithm, LaMDA, in June 2022, igniting a debate around whether AI algorithms can be sentient. While for the most part, intelligent technology that delivers personalization is a positive, but this latest revelation begs the question — can personalization be too personal? Here, Hamish White, CEO of telecoms software provider Mobilise investigates.
Short for Language Model for Dialogue Applications, LaMDA is Google’s chatbot system. Using extensive language models and AI, LaMDA uses vast data sources, including Wikipedia and Reddit, to replicate chat responses based on a statistical analysis of real human conversations. The idea is that it’s meant to sound as human as possible. But has LaMDA become too human?
Like any other chatbot, LaMDA is specifically designed to replicate human conversation. With this in mind, it’s more likely that LaMDA’s self-acclaimed sentience results from Google’s highly sophisticated AI algorithm rather than building a capacity to experience feelings. But the debate does raise the question, can chatbots — and other personalization technologies — be too personal?
Chatbots like LaMDA are all designed to sound as human as possible, to create an automated alternative to customer service agents. As a department notoriously understaffed and overstretched across all industries, an intelligent technology developed to alleviate pressure from customer service teams is a welcomed solution. The bot can handle more simple requests, leaving human teams with more time to tend to more complex inquiries.
Across most industries, personalization is the king of customer acquisition, satisfaction, and retention. In the increasingly digital age, consumers don’t just want personalized services, but they demand them. According to a McKinsey survey, two-thirds of consumers consistently expect brands to demonstrate how they know them personally through product recommendations, tailored messaging and targeted promotions. But delivering this requires more than conversational AI.
Chatbots aren’t the only place where AI comes into its own. Conversational AI is just one piece of the giant intelligent technology stack enabling organizations to personalize their services. For telecoms, in particular, meeting customer expectations is essential due to the nature of the industry. As a long sufferer of sky-high churn rates and a market saturated with competitors, keeping customers on the side is a priority for all service providers (SPs).
However, with customer expectations heightening and competition rife, SPs looking for success need to capitalize on the benefits of personalization. After all, those that excel at it on average, generate 40 percent more revenue.
A minimal personalization strategy is no longer sufficient to meet customer requirements. The bar has risen, and those looking to elevate their ops should consider hyper-personalization. Using all the customer data they can get, alongside AI and machine learning (ML), SPs can create a system that understands individual customer behaviors and makes all interactions relevant — and personalized — to each individual.
But can personalization go too far? The age-old worry that the phones are listening and delivering tailored content based on in-person conversations seems to be a line that consumers aren’t willing to cross. So, it’s crucial for SPs to learn how to unlock maximum value from their data without taking things too far in the eyes of their customers.
To deliver hyper-personalization, SPs first need to collect customer data. Fortunately, SPs don’t tend to be short of data that can be used across many different products and services. But reaching a point where it’s possible to unlock data’s value for use in a compliant and effective way can be incredibly challenging.
Mobilise’s HERO business support system (BSS) platform includes back-office tools to enable SPs to deliver hyper-personalized services. It can store, process, and analyze data and real-time customer behavior to allow SPs to adopt a next best offer (NBO) model. By putting this data through an ML engine that identifies patterns, HERO makes predictions and identifies opportunities to suggest relevant and timely offers for products and services to customers. All are completely personalized for each customer.
While LaMDA’s new heights of consciousness initially raised concern over whether intelligent technology is becoming too human, the reality is less worrying. Consumers are getting used to interacting with technology, and personalization that is more accurate and appears more human can support the hyper-personal movement. Customers want it, and technology can deliver it, so SPs should join the hype of hyper-personalization to elevate their operations to the next level.
Mobilise is a leading provider of SaaS solutions to the telecommunications industry. Focused on delivering highly engaging digital-first service propositions with excellent customer experience, Mobilise has a proven track record, deep industry knowledge, and a team of specialists to support clients in building and executing transformational strategies.
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