Could you uncover £300k savings in your virtual assistant?

If your virtual assistant resolves less than 80% of your conversations, you’re sitting on a goldmine of opportunity and could enhance the performance of your conversational artificial intelligence

The use of Conversational AI & Virtual Agents is expanding at a massive rate. The global market is expected to reach USD 168.2B by 2034 – up from USD 13.7B in 2024*.

This growth is driven by businesses looking to enhance customer engagement and operational efficiency. Organisations leverage conversational AI technologies to

offer round-the-clock customer service,

reduce operational costs,

and improve customer experience.

Conversational AI continues to impress users and businesses have increasingly high expectations, especially in light of large language model (LLM) features that it is now possible to incorporate into virtual assistants.

Once a virtual assistant (e.g. chatbot) is in place, savvy businesses iterate based on performance, customer feedback and further technological developments. Yet currently there is no standard set of performance measurements for bots or virtual assistants; metrics traditionally used in business intelligence reports will provide insight into stats, but these dashboards simply present the data – they don’t really understand the data.

Measuring the performance of conversational artificial intelligence for business success

Key Performance Indicators (KPIs) used to understand how virtual assistants are doing often include metrics on

Containment

Customer Satisfaction (CSAT)

Time to resolution

Fallbacks

Handovers

And of course, to really get a detailed understanding, it’s possible to read transcripts or run searches for keywords or phrases to uncover valuable insights. But how do you analyse every single conversation and find deeper patterns across all your conversations? Or fully determine if the intent recognised is right without verifying with the user?

“[Quality assurance is] arguably one of the biggest challenges from a practitioner standpoint working with these models. What you need to know when you’re building with these models is: are they doing the thing that you need them to do and getting it right every single time?”

Kane Simms, VUX World

Knowing how to prioritise enhancements can be a challenge, as can clarity on features that matter when it comes to return on investment (ROI).

If your virtual agent or chatbot has 100k conversations per month,

and the cost per agent call is £5,

a 5% increase in containment could

save £300k a year

Organisations that can fully leverage the qualitative as well as quantitative data behind conversational AI can

enhance customer satisfaction,

improve operational efficiency

and save money.

The big question is how? And the answers can be uncovered with Chatpulse.

Chatpulse gets to the heart of your conversational data, providing actionable insights, deep understanding and clear cost savings.

New! Spring Conversational AI Health Check

Evaluate the performance of your conversational AI; quickly understand how your virtual assistant is doing, and more importantly identify gaps and priorities with the CAI Health Check.

This fixed price package delivers a comprehensive performance report (based on insights from Chatpulse, and analysis by our expert CAI consultants), and includes a list of top 5 actionable insights – prioritised in order of the money they will save you, or value they can add to your business.