“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,” says David Truog, VP, 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,” he explains.
In a new research, Truog and four Forrester colleagues unpack generative AI and how it can create new content derived from a sample of existing data by discovering the deep structure in that sample and then modelling it ─ becoming what he describes as a ‘supercharged autocomplete.’
Many CX professionals are seeing good gains by using AI to generate synthetic data.
This data can mimic or extrapolate from the real world and is particularly useful for leaders who need to perform analysis on a customer data set, but who can’t use identifiable personal information.
This synthetic data also assists in training machine learning models in the absence of real-world data. For example, autonomous vehicle companies are using synthetic data to teach driverless cars how to drive.
Some forward-thinking companies are creating business avatars by generating synthetic data sets on their entire business, their customers, their operations, and their finances and using them to run simulations and conduct scenario planning.
These simulations allow business leaders to safely see the impact of CX decisions before making any financial commitments.
However, the report 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, companies must be careful to avoid what they refer to as a “garbage in, garbage everywhere” scenario.
Customer experience relies on understanding what the customer wants and building an offering that delivers on that.
Generative AI can help teams summarise customer feedback more effectively.
Forrester analysts point out that for companies with large amounts of social media interactions, generative AI could make a significant impact when it comes to distilling public feedback.
It can also generate natural language summaries of large quantities of unstructured data which can be particularly helpful to contact centres looking to create summaries of call transcripts.
In a report looking specifically at how AI is transforming contact centres 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 colleagues warn that generative AI should be used with caution as it is not yet 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 being used to help messaging agents craft more relevant replies to customer questions and help companies design the digital interactions customers will have with their organisation.
Richard Sheahan, Forrester vice-president, principal consultant (EMEA), will present: How to Lead a customer-centric organisation at CEM Africa, taking place from 15 to 16 August.