AI Talk: Deliver an ROI from conversational AI

On 3 December 2024, AI Talk host Kevin Craine was joined by Ayman Husain, Customer Engineering Leader, Google; Jamie Grabert, President/Co-Founder, The Consultancy Group; and Peggy Salz, Content Strategist and founder, Mobile groove.

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As billions pour into gen AI initiatives, a stark reality emerges – enthusiasm outpaces understanding. A recent KPMG survey reveals a staggering 78% of C-suite leaders are confident in gen AI’s ROI. However, confidence alone is hardly an investment thesis. Compounding this issue is the complexity of attribution.

 

In today’s interconnected business environments, isolating the impact of AI from other factors – market fluctuations, concurrent tech upgrades, or even changes in workforce dynamics – is akin to untangling a Gordian knot. There is an opportunity cost of not investing in conversational AI, which varies across different sectors and companies. The rationale behind implementation can be both cost and generating new revenue streams. Your ROI will depend on a couple of factors such as the quality of the framework you establish, the quality of data, and the willingness of staff to use the technology. Keeping your people and your customers involved in AI will enhance the effectiveness and efficiency of the tool.

 

GenAI can do a lot of things and improving the customer experience is one of them. To assess the success of implementations, both qualitative and quantitative metrics need to be taken into consideration. And it must also be remembered that the customer experience will always affect the bottom line. It’s also important to make sure that all the metrics relate back to business goals. 

The challenges of GenAI deployment

Conversational AI will dominate in call centres 2025. When there is an emergency, an AI agent will immediately know all the personal details and the terms of the service provided and won’t ask an agitated consumer about these. The AI agent will also be capable of taking out the sentiment from what the consumer says.

 

Surveys conducted across the globe show that customers are rather accepting with AI agents. AI agents can also provide proactive assistance and relevant suggestions. Privacy and security are issues that aren’t specific to GenAI. However, there are ethical concerns specific to the field that must be addressed. To leverage GenAI, go to your data first and find where cost reduction can take place, then check how an AI agent can difuse the negative feelings of a disgruntled customer. You can also go back to your current KPIs and see how GenAI could improve them. Historical data plays a key role. All your customer interactions should be tracked and tagged as it will help you identify the best time for outreach and the best opportunities to personalise. Trailblazers in this new space are looking at metrics such as churn, retention and how dormant users are reengaged to assess the success of the new technology.

 

Reluctance to share data within an organisation – particularly between sales and marketing – should be addressed too, as it’s a barrier to calculating RoI. The general trend is that marketers now look more to intangible benefits of GenAI such as trust building and brand equity. This is becoming increasingly important thanks to the shift that is taking place in performance marketing. 

 

The panel’s advice

• To leverage GenAI, start with the right use case and define where you expect to find value.
• AI can help sales deal with the percentage of customers that they previously had no capacity for.
• Data in your legacy system will point you to the missed opportunities and suggest how these can be better leveraged.
• The historical data you use for gaining insights where customer service can be improved must be accurate and clean.
• Adaptive learning will lead to deeper personalisation.
• Enable your people to learn with and about GenAI.