Article • 4 min read
Promptable analytics: How CX teams can have a two-way conversation with data
Instead of slow, static dashboards, CX leaders are investing in tools that allow their teams to truly interrogate data. Discover more about promptable analytics and how CX metrics are changing in the AI era.
Vanessa Kahn
Product Marketing Manager for Analytics at Zendesk
최종 업데이트: December 10, 2025
Imagine your own personal data scientist, sitting by your side and able to take a nebulous hypothesis and check if it plays out in the data.
That’s the promise of promptable analytics.
Its potential is huge. It can turn a hunch into something that’s provable, and helps CX teams get to data-backed decisions faster.
What are promptable analytics?
In short, it’s a new way of accessing and interpreting CX data using natural-language prompts – that is, by asking questions in everyday language and instantly receiving AI-driven, context-rich insights.
Just as you might ask ChatGPT for something in your own words, imagine being able to similarly interact with your CX data—through a process grounded in statistical rigor.
In the past, analyzing CX performance meant solely relying on dashboards and reports, or waiting on data teams for more complex questions.
Instead, promptable analytics democratizes data access, enabling anyone in an organization – not just your analysts – to query operations and uncover answers in seconds.
Learn more about our recent acquisition of HyperArc, a generative AI-powered promotable analytics tool.
What do CX leaders think about promptable analytics?
In our latest CX Trends 2026 report, 87% of CX leaders said that AI is already significantly improving data and analytics. Among high-maturity organizations, that figure jumps to 97%.
Promptable analytics is proving to be a core part of this shift to AI-powered data.
Today, 44% of organizations have implemented a prompt-analytics hub, but that number is expected to nearly double to 86% within a year.
High-maturity organizations are leading this charge. By 2026, virtually all (97%) will have promptable analytics tools at their disposal, while only about half (55%) of low-maturity organizations will.
How are CX metrics changing?
It’s not just how teams are analyzing data. The data itself is transforming.
According to our recent trends study, organizations tracking new AI-specific KPIs will climb from 47% today to 86% within the next two years.
Companies like SeatGeek, for instance, have already expanded their scorecards to include AI-specific measures such as automation containment, bot satisfaction, and cost-per-contact.
These new metrics capture dimensions of CX that traditional KPIs like CSAT and FCR (First Contact Resolution) alone cannot.
And with promptable analytics, they’ll be more accessible than any data we’ve had in the past.
How could teams use promptable analytics?
The thing about promptable analytics is it makes CX data fit to you – the way you think and speak – rather than force you to analyze data in fixed ways.
But to give an idea of how promptable analytics might work in practice, here’s how some CX roles can take advantage:
1. Heads of CX
Goal: align KPIs with business goals through layered metrics
You want to know: how different metrics tie together to influence overall customer satisfaction
You ask: “Show me the correlation between first contact resolution (FCR), average handle time (AHT), and CSAT scores over the past quarter.”
You see: trends showing that higher FCR strongly predicts better CSAT, whereas AHT varies less
2. CX managers
Goal: quickly identify emerging customer issues across channels
You want to know: why there’s been a sudden spike in support ticket volume
You ask: “What customer issues increased the most across email, chat, and social media last week?”
You see: a recent product update has caused confusion with returns policy
3. Support supervisors
Goal: measure AI automation success with context
You want to know: how well AI chatbots are managing inquiries without human help
You ask: “What percentage of AI agent interactions last month were resolved without escalation, and how did customers rate their satisfaction?”
You see: while most issues are fully resolved by bots, satisfaction dips when billing questions arise, signaling a need for improved escalation workflows
4. Frontline teams
Goal: enable agents with instant insights
You want to know: about product compatibility to answer a tricky question from a customer
You ask: “What were the top solutions given for compatibility issues in the last 100 support tickets?”
You see: an accurate, consistent answer based on a vast amount of knowledge base information
How do you get started with promptable analytics?
Here’s a short checklist to keep in mind as you move into promptable analytics:
- Move beyond traditional metrics like speed and volume. Focus on resolution-based KPIs that measure the effectiveness of support – was the issue truly fixed the first time?
- Invest in AI-powered analytics platforms that support natural language querying and integrate multi-channel data.
- Empower your teams with promptable tools that democratize data access and encourage data-informed decision-making at all levels.
- Track and expand AI-specific KPIs including automation containment rates, bot satisfaction, and cost-per-contact to get a fuller picture of CX success.
Transitioning to a whole new way of doing analytics is a journey. And it’s as much about changing mindsets as it is implementing new tech.
