Can generative AI improve customer experience?
Forrester researchers say yes — but advise caution and patience
Though generative artificial intelligence (AI) has permeated many parts of our lives, most customer experience (CX) professionals are wary of allowing such a fairly nascent technology near any customer-facing tasks. However, new insights from research company Forrester reveals the potential of generative AI to improve CX without exposing a business to undue risk.
David Truog, VP, principal analyst at Forrester, explains: “Generative AI is opening major opportunities for CX professionals, but many don’t understand what it is and how it’s relevant to CX. Few CX professionals, 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.”
New research conducted by Truog and his colleagues unpacks 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.”
Forrester’s research reveals that many CX professionals are seeing good gains by using AI to generate synthetic data. This data can mimic the real world or extrapolate from it, 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.
Generative AI could have a significant effect when it comes to distilling public feedback
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, companies must be careful to avoid what they refer to as a “garbage in, garbage everywhere” scenario.
CX 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 have a significant effect 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 using “large language models along with natural language query and natural language generation techniques to allow customer service teams to obtain 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 ways the technology can drive savings and boost CX include generative AI being used to help messaging agents craft more relevant replies to customer questions and to help companies design the digital interactions customers will have with their organisation.
In separate CX research, Forrester highlights how companies should align CX with employee experiences (EX) to drive business success. However, as the report “Build the Right Bridge Between EX and CX Management”, outlines, CX and EX teams often fail to collaborate, despite many opportunities to align on data, metrics and goals.
One potential reason for this failure is that human resources departments have historically been siloed and can be protective of their mandate to deal with employee-related matters. This territorial approach can lead to these departments being reluctant to share EX insights.
The turf war can be worsened by overlaps in functions such as training for customer-facing employees, which can in turn create a competitive relationship that is not conducive to collaboration.
Forrester’s report goes on to explore three approaches that companies can take to create a more collaborative environment to help bridge the gap between CX and EX. These include bringing CX and EX together under a single experience leader; giving them co-ownership of experiences and having them collaborate via centres of excellence.
The big take-out:
The big take-out: While AI is capable of distilling vast quantities of data, companies must be careful to avoid a “garbage in, garbage everywhere” scenario.
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