> ## Knowledge Base Index
> Fetch the complete knowledge base index at: https://help.crisp.chat/sitemap.xml
> Use this file to discover available pages before exploring further.
> Pure-Markdown content can be obtained by appending a '.md' suffix to the content URLs listed in the sitemap (without the trailing slash).

# Dashboard Templates for Customer Support teams

*Use these four Analytics Dashboard templates to start monitoring support activity, team performance, AI impact, and Knowledge Base efficiency in Crisp.*

Crisp Analytics includes many reports, metrics, views, and filters. Templates give your team a ready-made starting point, so you can understand what is happening in support without building every Dashboard from scratch.

__This guide covers:__
* [Why use Dashboard templates?](#1-why-use-dashboard-templates) → when templates are useful
* [How to import a Dashboard](#1-how-to-import-a-dashboard) → where to upload a template file
* [Four templates you can use](#1-4-dashboard-templates-you-can-use-inside-crisp) → activity, team, AI, and Knowledge Base views
* [How to customize your Dashboards](#1-how-to-customize-your-dashboards) → filters and segments to adapt each template
* [Where to go next](#1-where-to-go-next) → companion Analytics articles

---

# ${color}[#0080dd](Why use Dashboard templates)

Templates help you avoid starting from a blank page. They group useful reports into a clear structure, then automatically use your real workspace data once imported.

A good Analytics setup usually looks at four layers: what is happening, how your team handles it, how much AI helps, and whether your Knowledge Base reduces repetitive questions.

---

# ${color}[#0080dd](How to import a Dashboard)

Open [**Crisp**](https://app.crisp.chat), then go to **Analytics → Dashboards**. Click **Create a new dashboard**, choose **Import from a file**, and upload the **.json** file for the Dashboard you want to reuse.

![Import an Analytics Dashboard template](https://storage.crisp.chat/users/helpdesk/website/-/8/7/a/e/87ae2703583ac800/crisp-analytics-dashboard-temp_17ew530.png)

Once imported, the Dashboard appears in your list and can be renamed, edited, filtered, or exported again.

---

# ${color}[#0080dd](4 Dashboard templates you can use inside Crisp)

Each template answers a different operational question. You can use them as they are, or edit them to match your team structure, support channels, customer segments, and reporting habits.

#### ${color}[#445055](Conversation Overview)

This Dashboard gives you a global view of support activity: conversation volume, peaks, channels, first response origin, and operator message activity.

![Conversation Overview Analytics Dashboard](https://storage.crisp.chat/users/helpdesk/website/-/8/7/a/e/87ae2703583ac800/crisp-analytics-conversation-o_jfotjq.png)

###### ${color}[#F08820](Included metrics)

__This template usually includes:__
* **Conversations Over Time** → volume trend across the selected period
* **Conversations Per Period** → heatmap of daily and hourly activity patterns
* **Most Used Conversation Channels** → where conversations come from
* **Conversations Per First Response Origin** → human, automation, AI, or other first response sources
* **Messages Per Operator** → message activity across your support team

|| 💬 Conversation Overview Dashboard is available in-app.

###### ${color}[#F08820](How to interpret it)

Start with conversation peaks. If volume spikes on specific days or hours, adjust staffing, routing, or automation coverage around those periods. Then compare channels to understand where customers actually contact you, and review first response origin to see whether automations are helping with the initial load.

Use **Messages Per Operator** to understand how messaging activity is distributed across the team. Combine message volume with response time, resolution time, and customer satisfaction rather than using it alone to evaluate operator performance.

Useful resources: [how Crisp Analytics work](https://help.crisp.chat/en/article/how-do-crisp-analytics-work-fwul5i/) and [improve customer service response time](https://crisp.chat/en/blog/improve-customer-service-response-time/).

#### ${color}[#445055](Team Performance Dashboard)

This Dashboard helps team leads review how agents handle conversations, where workload is concentrated, and whether response targets are being met.

![Team Performance Analytics Dashboard](https://storage.crisp.chat/users/helpdesk/website/-/8/7/a/e/87ae2703583ac800/crisp-analytics-team-performan_1j6movz.png)

###### ${color}[#F08820](Included metrics)

__This template usually includes:__
* **Human Conversations** → conversations handled by human agents
* **First Response Time** → how quickly users receive the first reply
* **Global Resolution Time** → average time to resolve conversations
* **Operator Rating** → customer satisfaction per operator
* **Operators Table** → operator-level volume, response time, resolution time, and ratings
* **Conversations Per Operator** → workload distribution across the team
* **Conversations Breaching SLA** → conversations that exceed your response target

|| 👥 Team Performance Dashboard is available in-app.

###### ${color}[#F08820](How to interpret it)

Start with workload distribution. If a few operators handle a disproportionate share of conversations, review routing, shifts, and assignment rules. Then compare response and resolution times with the team median to identify coaching opportunities or process gaps.

If SLA breaches spike at specific times, align staffing or strengthen automation during those periods. If breaches rise across the board, the team may need better shortcuts, clearer triage, or more AI coverage for repetitive requests.

Useful resources: [Routing and Assign](https://help.crisp.chat/en/article/how-does-routing-assign-work-qjl2d2/) and [keyboard shortcuts for the Crisp Inbox](https://help.crisp.chat/en/article/keyboard-shortcuts-for-your-crisp-inbox-1e7mg4k/).

#### ${color}[#445055](Key AI Support Metrics)

This Dashboard helps you track key AI and human customer support metrics and compare your performance with data from [**Crisp’s State of AI Customer Support study**](https://crisp.chat/en/reports/state-of-ai-support/).

The study provides benchmarks based on customer support data from Crisp workspaces, helping you put your own AI performance into context.

![Key AI Support Metrics Analytics Dashboard](https://storage.crisp.chat/users/helpdesk/website/-/8/7/a/e/87ae2703583ac800/crisp-analytics-key-ai-support_icwb85.png)

###### ${color}[#F08820](Included metrics)

__This template includes:__
* **Conversations** → total conversation volume
* **AI First Response Time** → first response time when the first reply comes from AI or the Auto-Responder
* **Human First Response Time** → first response time when the first reply comes from a human operator
* **Automated Conversations** → conversations answered by AI or self-service before reaching a human agent
* **Fully Automated Conversations** → conversations resolved completely by AI without human intervention

|| 🧠 Key AI Support Metrics Dashboard is available in-app.

###### ${color}[#F08820](How to interpret it)

Start by comparing **AI First Response Time** and **Human First Response Time** to understand how quickly customers receive an initial answer depending on who handles the conversation first.

Then compare **Automated Conversations** and **Fully Automated Conversations** to understand how much support volume AI handles before human intervention and how much is resolved end-to-end.

Use [**Crisp’s State of AI Customer Support study**](https://crisp.chat/en/reports/state-of-ai-support/) as a benchmark to compare these metrics with broader customer support data and identify where AI is having the strongest impact on your support operations.

Useful resources: [Getting started with Hugo AI Agent](https://help.crisp.chat/en/article/getting-started-with-hugo-ai-agent-w6gbux/).

#### ${color}[#445055](Knowledge Base Performance Dashboard)

This Dashboard shows how effectively your documentation supports self-service and reduces repetitive questions.

![Knowledge Base Performance Analytics Dashboard](https://storage.crisp.chat/users/helpdesk/website/-/8/7/a/e/87ae2703583ac800/crisp-analytics-knowledge-base_1gbffuv.png)

###### ${color}[#F08820](Included metrics)

__This template usually includes:__
* **Website Visits / Knowledge Base Visits** → traffic to your site and documentation
* **Knowledge Base Visits Over Time** → article consumption trend
* **Visits by Language** → views by Knowledge Base locale
* **Articles Table** → visits, reactions, usefulness, and article-level details
* **Top Search Queries** → most searched terms inside the Knowledge Base

|| 📚 Knowledge Base Performance Dashboard is available in-app.

###### ${color}[#F08820](How to interpret it)

Start with search queries. They reveal what customers tried to solve before contacting support. If high-volume searches have poor article coverage or low usefulness scores, prioritize those topics.

Then compare article visits with support trends. If an article receives traffic but does not reduce conversations, it may need clearer steps, better examples, stronger internal links, or a better title. Use the language breakdown to prioritize translation work when multiple locales are active.

Useful resources: [use the Knowledge Base](https://help.crisp.chat/en/article/how-to-use-the-knowledge-base-i2tsm1/) and [format Knowledge Base articles](https://help.crisp.chat/en/article/how-can-i-format-knowledge-base-articles-oiurpj/).

---

# ${color}[#0080dd](How to customize your Dashboards)

Once a template is imported, the easiest way to make it relevant is to use **segments** and filters. This lets the same Dashboard answer different operational questions without duplicating every chart.

__Segments can help you compare:__
* **Teams or inboxes** → Support, Sales, Billing, VIP support, or language-specific teams
* **Customer types** → free users, paid users, enterprise accounts, new customers, or high-value customers
* **Conversation topics** → bug reports, onboarding, refunds, pricing, or product questions
* **Channels** → chat, email, WhatsApp, Instagram, Messenger, or other connected channels
* **Regions or languages** → country, locale, or market-specific views

For example, apply an **Enterprise** segment to review high-value customers, a **Bug reports** segment to monitor engineering-related workload, or a **WhatsApp** segment to understand channel-specific performance.

Useful resource: [What is a segment and how can it help your team?](https://help.crisp.chat/en/article/what-is-a-segment-and-how-can-it-help-your-team-88hhzw/).

---

# ${color}[#0080dd](Where to go next)

These four templates give you a practical starting point for customer support reporting. Import them, review the default charts, remove anything your team does not use, and add custom charts as your reporting needs become clearer.

__Useful companion articles:__
* [How do Crisp Analytics work?](https://help.crisp.chat/en/article/how-do-crisp-analytics-work-fwul5i/) → understand reports, filters, and metric calculations
* [How to build a custom dashboard in Crisp Analytics?](https://help.crisp.chat/en/article/how-to-build-a-custom-dashboard-in-crisp-analytics-77heh0/) → create your own reporting view from scratch
* [How to share Analytics dashboards with your team](https://help.crisp.chat/en/article/how-to-share-analytics-dashboards-with-your-team-1aocit8/) → let workspace operators view and edit the same Dashboard
* [How to import / export a dashboard in Analytics?](https://help.crisp.chat/en/article/how-to-import-export-a-dashboard-in-analytics-30678w/) → reuse templates across teammates or workspaces