ChatGPT has over 300 million weekly users sending more than 1 billion messages per day and Internet search traffic is predicted to drop 25% by 2026.
Why? Conversation has rapidly become the interface of choice for the modern user.
While above is an example of the move from traditional search to Conversational AI, a new shift is rapidly approaching for customer-facing analytics. This is the change from static, pre-canned dashboarding and reporting to dynamic, intelligent conversational analytics.
User-facing analytics must transform to meet the emerging habits and behaviours of users.
Here are 3 ways Conversational AI is transforming customer-facing analytics.
Users no longer want to fiddle with filters. They have become accustomed to getting answers, fast. The old approach of manually setting filters, date ranges, and aggregations is clunky and leads to dead ends on follow-up questions.
Conversational analytics allows users to ask for answers in natural language. It figures out what data is needed and is immediately ready for the next question so users can easily pivot and drill down through their data.
Conversational analytics facilitates a 10x speed boost in time to answer, giving users the answers they came for without delay.
Static customer-facing analytics are inherently inflexible. That’s why embedded analytics emerged.
Embedded analytics dashboards may allow users to get answers without needing to submit a support request. However, even these require users to pre-build the dashboard or reports in-app before their questions can be answered, thereby limiting flexibility..
Conversational analytics changes this by connecting directly to your database. The AI model can extract any data permutation on demand to answer vast numbers of users’ questions.
Conversational analytics offers a level of flexibility that static dashboards and even self-serve embedded analytics tools simply can’t match, thanks to recent advances in large language models (LLMs) and AI agents.
Conversational analytics turns every user query into a valuable data point. For the first time, seeing exactly what users ask, businesses can gain direct insights into their users’ priorities, pain points, and thought processes.
This natural language feedback isn’t just numbers; it reveals users’ true intentions. In other words, analyzing these questions allows you to fine-tune your product, address gaps, and develop a more user-centric experience.
See how Conversational AI can revolutionize your customer facing analytics by getting started here.