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Why CX professionals should use generative AI to create synthetic data
By our News Team | 2023
This can be useful for marketers who need to analyse customer data sets, but can’t use identifiable personal information.
While generative artificial intelligence solutions such as ChatGPT aren’t yet ready for direct conversations with customers, customer experience (CX) professionals are starting to see good gains from using AI to generate synthetic data – which mimics or extrapolates data from the real world – to de-risk real-world decisions.
This is particularly useful for marketers who need to perform analysis on a customer data set, but who can’t use identifiable personal information, says Forrester, the international research and advisory consultancy.
Photo by Tara Winstead from Pexels
It adds that some companies are even generating synthetic data sets on their entire business, customers, operations, and finances – and using these to run simulations and conduct scenario planning so they can safely see the impact of customer experience decisions before making financial commitments.
“Generative AI is opening up major opportunities for CX professionals, but many don’t understand what it is and how it’s relevant to CX,” notes David Truog, Vice President and Principal Analyst at Forrester.
“Few CX pros, for example, know how generative AI can answer questions without performing any kind of search, why it sometimes confidently asserts falsehoods, or what makes it occasionally exhibit humanlike creativity.
“And few recognise the many ways it will help with understanding, serving, and designing experiences for customers.”
Synthetic data de-risks real world decisions
However, Forrester warns that companies hoping to use synthetic data must ensure that their original data is accurate. While AI is capable of distilling vast quantities of data, organisations must be careful to avoid a ‘garbage in, garbage everywhere’ scenario.
In a report looking specifically at how AI is transforming contact centres titled: Generative AI: What it Means for Customer Service, Forrester experts say they expect vendors will soon be leveraging “Large Language Models (LLM) along with natural language query (NLQ) and natural language generation (NLG) techniques to allow customer service teams to access deeper conversational insights with far less upfront effort”.
Truog and his research colleagues warn that generative AI should be used with caution as it is not ready to be customer-facing just yet. However, the potential to leverage the technology when it comes to chatbot support in contact centres is clearly evident.
Examples of where the technology can be used to drive savings and boost CX include generative AI helping messaging agents craft more relevant replies to customer questions, and assisting companies to design the digital interactions customers will have with their organisation.
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