Set up Crisp Analytics for Customer Support: 4 dashboards templates
Crisp Analytics includes many reports, metrics, views and filters. For many teams, the hardest part is simply knowing where to start.
This guide gives you 4 ready-to-use dashboards that you can import into your Crisp workspace.
They provide a clear foundation to understand:
- your support activity,
- your team performance,
- your AI impact,
- and the efficiency of your Knowledge Base.
Each dashboard can be customized later depending on your workflows, channels, or business structure.
Why use dashboard templates?
Crisp Analytics offers a wide range of charts and metrics, but choosing how to organize them into a meaningful dashboard can still feel complex. Templates give you a structured foundation so you don’t have to start from a blank page.
They work in any Crisp workspace and automatically adapt to your real data. This means you instantly get a clear, reliable view of your activity, without needing to configure dozens of settings first.
Templates also improve team communication. When everyone shares the same dashboards, support agents, managers, and product teams read metrics the same way. It becomes much easier to align on priorities, spot issues, or report performance.
Finally, they are designed for readability. Charts are grouped logically, the layout is intentional, and each dashboard focuses on a single topic. This makes Analytics far easier to scan and understand, especially for teams exploring Crisp Analytics for the first time.
How to import a dashboard (.json)
You can import any of the dashboards below using the .json configuration file.
Steps:
- Go to Analytics → Create new dashboard
- Click Import dashboard
- Upload the
.jsonfile - Rename the dashboard if needed

How to import / export a dashboard in Analytics?
4 Dashboard templates you can use inside Crisp
These four dashboards were designed to work together and give you a complete, readable view of your customer support activity.
Each one focuses on a different layer of your operations so you can move from a global understanding to more precise diagnostics without getting lost.
The idea is simple:
- Conversation Overview helps you understand what is happening (volume, peaks, channels).
- Team Performance shows how your agents handle it.
- AI Performance highlights how much your automations help and where they need improvement.
- Knowledge Base Performance reveals how much self-service reduces workload.
Together, they form a clear method to navigate Crisp Analytics: start broad, drill down by team or automation, and finish by evaluating how well your documentation absorbs common questions.
1. Conversation Overview
This dashboard gives you a clear, immediate understanding of how your support workload behaves.
It removes guesswork around when your inbox is busiest, which channels create the most pressure, and how automation contributes to the first reply. It’s the fastest way for any CX team to see patterns, anticipate demand, and make informed staffing or workflow decisions.

Included metrics
- Conversations Over Time
Daily conversation volume. Helps you spot peaks, recurring patterns, seasonality or unexpected spikes caused by incidents or releases.
- Conversations Per Period (Heatmap)
Hour-by-hour distribution across each weekday. Reveals true peak hours, quiet periods, and staffing gaps.
- Most Used Conversation Channels
Breakdown of workload across Chat, Email, WhatsApp, Contact Form, Telegram, etc. Shows which entry points require more resources or automation.
- Conversations Per First Response Origin
Treemap showing whether the first reply came from a Bot, Auto-responder, or Human. Useful to understand how much load automation absorbs before agents step in.
How to interpret and act on this dashboard?
Use the heatmap to identify your real peak hours: the moments where agent presence matters most. If specific time ranges are consistently overloaded, adjust shifts, create follow-the-sun coverage, or activate targeted automations during those periods.
Compare channels to understand where pressure accumulates. If chat or email dominates, consider strengthening your templates, routing rules, or AI setup for those channels specifically. This ensures effort is focused where it creates the biggest efficiency gain.
Finally, look at how often bots or autoresponders deliver the first reply. If automation barely contributes, your Data Hub or chatbot scenario likely needs expansion. Conversely, if automation absorbs a large part of the initial load, analyze quiet periods to schedule maintenance, training, or workflow reviews without impacting your response time.
Understanding and Mastering the Crisp AI Chatbot
Why Self-Service is the Future of Support (Without Losing the Human Touch)
Customer Service Automations Every Support Team Should Deploy
2. Team Performance Dashboard
This dashboard helps you understand how your team handles the workload: who manages the largest volume, who responds the fastest, and where conversations take longer to resolve.
It gives managers a transparent view of capacity, consistency, and areas where coaching or redistribution would create immediate gains.

Included metrics
- Human Conversations (KPI)
Total conversations handled by agents.
- First Response Time
Average delay before the first human reply. Indicates reactivity.
- Global Resolution Time
Average time to fully resolve a conversation.
- Operator Rating
Average customer rating for each operator.
- Operators Table
Shows per-agent workload: conversations handled, response time, resolution time, rating.
- Conversations Per Operator (Treemap)
Visual distribution of workload across the team.
- Conversations Breaching SLA (>1h)
Line graph showing how many conversations exceeded the agreed response target.
How to interpret and act on this dashboard?
Start with volume distribution: if a few operators absorb a disproportionate share of conversations, rebalance routing rules or reinforce shifts during their active periods. This prevents burnout and stabilizes team performance.
Compare individual response and resolution times with the team’s median. Operators who are significantly slower may need better tools (snippets, shortcuts), clearer processes, or coaching on triage and prioritization. The opposite is true as well: high performers offer insights worth spreading across the team.
Use SLA breaches to detect operational bottlenecks. If breaches spike on specific days or hours, align staff availability accordingly. If they rise across the board, it’s often a sign that automation should be strengthened or the overall team workload is too high relative to capacity.
How does Routing / Assign work?
How do I create a department routing Chatbot?
Keyboard shortcuts for your Crisp Inbox
10 proven ways to improve customer service response time (with AI-powered examples)
First Response Time: The #1 metric that shapes long waiting times
3. AI Performance Dashboard
This dashboard focuses on how Crisp automation and AI impact your support workload.
It helps you see how many conversations automation handles from the start, how many are fully deflected, and how quickly AI compared to humans resolves issues. It’s essential for monitoring quality, reliability, and return on investment.

Included metrics
- Conversations
Total monthly conversations.
- Automation First-Hand
Conversations receiving their first reply from an AI chatbot or automation.
- Deflected Conversations
Conversations resolved entirely by automation without agent intervention.
- Avg. Resolution Time — Human
Average human resolution time.
- Avg. Resolution Time — AI
Average automation resolution time.
- Overall Rating / Automation Rating
Customer satisfaction for both human and automated replies.
- Fallback Messages / Month
Treemap showing when the AI failed to answer (e.g., "I don't understand" messages from visitors).
- Total AI Messages
Line chart showing monthly AI-generated messages.
How to interpret and act on this dashboard?
Compare human vs AI resolution times to understand efficiency gains. If AI resolves far faster, increase automation coverage by expanding the Data Hub or adding new intents to your Chatbot scenarios. If AI resolution time increases, investigate fallback messages, they often reveal missing content or misunderstandings.
Monitor deflection rate closely: it’s the strongest indicator of AI ROI. A low deflection percentage means too many conversations still escalate unnecessarily. Strengthen documentation, add training examples, or refine reply tone to boost automation reliability.
Use fallback analysis as your improvement roadmap. If a single topic represents most failures (e.g. “faq_issue” segment), update corresponding help articles, add missing snippets, or refine bot flows. This alone often decreases workload by 10–30%.
Understanding and Mastering the Crisp AI Chatbot
How to measure AI Chatbot ROI with Crisp?
Ticket deflection: How AI Chatbots reduce support backlogs
First response vs Resolution: why 24/7 AI support changes after-hours resolutions KPIs
4. Knowledge Base Performance Dashboard
This dashboard shows how effectively your documentation reduces support volume.
It helps you track article visibility, usefulness, and search behavior, revealing both what works and what information is missing. It’s the easiest way to improve self-service and reduce repetitive tickets.

Included metrics
- Website Visits / Knowledge Base Visits
Traffic to your site and documentation.
- Knowledge Base Visits Over Time
Line chart showing daily article consumption trends.
- Visits by Language
Distribution of views by locale.
- Articles Table
Per-article metrics: visits, reactions, usefulness rating, quick access to edit or analyze.
- Top Search Queries
Treemap showing the most searched terms inside your knowledge base.
How to interpret and act on this dashboard?
Start with search queries: they reveal what customers try to solve before contacting support. If high-volume searches don’t match article titles or lead to low-usefulness ratings, you’ve found gaps the team should address immediately.
Compare article visits with support trends. If certain articles attract traffic but don’t reduce conversations, revisit structure, clarity, or add more actionable examples. Articles with high “thumbs down” reactions often need rewriting or clearer steps.
Use language breakdowns to prioritize translation work. If most users access only one locale, start there. If multiple languages spike, align your publishing workflow accordingly so all versions remain consistent.
How can I format Knowledge Base articles?
From FAQs to AI: How Chatbots Deliver AI Self-Service Support at Scale
After-hours customer service: Support customers while you sleep
How to customize your dashboards?
Once your dashboards are imported, the most powerful way to adapt them to your workflow is by using Segments.
Segments allow you to filter analytics based on real conversation attributes so every dashboard becomes instantly more relevant to your team.
Segments let you break down your data by:
- Teams or inboxes (ex: Support vs. Sales vs. Billing)
- Customer types (ex: free vs. paid users, enterprise accounts, new users)
- Conversation tags (ex: bug reports, onboarding, refunds…)
- Channels (ex: email-only users, WhatsApp leads…)
- Regions or languages
Instead of duplicating dashboards manually, you can simply apply a segment to view the same structure through a different lens.
For example:
- Apply an "Enterprise" segment to see how your AI, team or KB performs specifically for high-value customers.
- Apply a "Bug reports" segment to understand workload patterns for engineering-related issues.
- Apply a "WhatsApp" or "Email" segment to compare channel performance without changing your dashboard layout.
- Apply a "New users – 30 days" segment to monitor onboarding quality.
Segments turn each dashboard into multiple specialized dashboards without extra setup.
If a segment does not yet exist, you can create one based on rules such as message origin, domain, user properties, event triggers, tags, or inbox routing. Once the segment is created, it immediately becomes usable as a filter in all analytics dashboards.
What is a segment and how can it help your team?
These four templates give you an easy starting point to understand your support activity with Crisp Analytics. You can import them, use them as they are, or extend them to create your own reporting system.
Check out these helpful resources:
How to build a custom dashboard in Crisp Analytics?
Updated on: 03/12/2025
Thank you!