Pylon Analytics: A practical guide for B2B support leaders

Most B2B support teams are drowning in tickets but starving for insights. Your support staff want to improve their response times and make sure AI agents are set up to be effective, but they can’t easily access this data because it’s scattered across tools, messaging platforms, and dashboards. 

Unified customer support analytics help you move beyond reactive ticket-handling to start making real, measurable improvements. In this article, we’ll explore which analytics to track and how to build custom reporting in Pylon’s Analytics dashboard that gives you real-time insight into important figures like response times, CSATs, and SLA compliance.

How to set up Pylon’s support analytics: 8 steps

Here’s a simple step-by-step guide to setting up and using Pylon’s Analytics dashboard:

1. Navigate to the Analytics page. From your Pylon dashboard, click on “Analytics” to see an overview of the data that’s been set up for you out of the box.
2. Explore the default dashboards. By default, Pylon gives you a range of dashboards covering issue volume, customer satisfaction scores (CSATs), net promoter scores (NPSs), community and workforce analytics, SLA adherence, and AI agent analytics.
3. Apply filters. For each dashboard, add filters at the top to narrow down the data by time, accounts, and other properties. This helps you quickly go from overall insights to specific, actionable data.
4. Drill into charts. As you hover over the bars on each chart, more details appear. When you want to drill down even more, click to see the underlying data. For example, on a bar chart showing issue volume per day, click on the bar for a particular day to see a list of every issue created that day, which customer it was for, and who it was assigned to.
5. Create a custom dashboard. From the Analytics page, simply click the “+” button to create your own custom dashboard. Give it any name you want, control who can see it, and click “Add Chart” to add all the charts you need. Reorder and resize them just by dragging and dropping to create the exact report that fits your use case.
6. Build custom charts. You can create custom graphs by selecting the graph type and choosing which metrics to display on each axis. Add filters, group data, and use multiple series on a single graph. You can even use formulas for complex data visualization.
7. Use AI to build charts. Pylon’s AI can also help you build charts more easily. Simply describe what you want (e.g., “Number of issues per account over the last year”), and the AI Assistant will build the chart for you.
8. Share and iterate. When you’ve finished creating your dashboard, click “Share” in the top-right corner, and choose who you want to share this data with. Then, keep exploring your data and improving the dashboard, adding and removing charts until it shows the precise metrics you want to track.

From prebuilt dashboards to AI-powered custom charts, Pylon gives your team the visibility to actually improve. Schedule your personalized walkthrough.

What teams learn when they start tracking support analytics

Support analytics give teams the business intelligence they need to make smarter decisions and achieve better results. 

For example, Sardine centralized conversations from multiple customer channels into a single platform that allows them to generate detailed reports and improve their results; the team has since achieved a 90% decrease in first response time.

Builder.io used analytics tools to track its migration from Zendesk to Pylon, making sure all 9,000+ tickets and six integrations were migrated successfully, with zero customer complaints. It measured the impact of Pylon’s automated workflows, finding that the team saved 6–7 minutes per transaction. 

And Coalesce used exploratory data analysis to learn that AI-generated summaries decreased manual note-taking by 85% and reduced the time spent preparing for customer check-ins by 40%.

The support metrics that actually move the business

When you build reports, the categories and data sources you choose will depend on the specific business outcomes you want to achieve. These are the main categories that B2B support teams usually focus on.

Volume and velocity 

Use volume metrics to view customer demand, and combine them with velocity metrics to see how quickly your team is responding to that demand. 

Key metrics include:

• Ticket volumes by channel
• Ticket backlog
• First response time (FRT)
• Time to resolution (TTR)
• Escalation rate

Together, these metrics help you spot operational bottlenecks and plan your hiring needs.

Satisfaction signals

Track customer satisfaction metrics to measure your overall performance and highlight retention risks before they appear in renewal conversations.

Satisfaction metrics include:

• Customer satisfaction scores
• Net promoter scores
• Customer effort scores

SLA compliance 

Service-level agreements (SLAs) represent your commitments to customers, so you need to track how well you’re meeting your targets and make urgent changes if needed. Track your overall level of SLA breaches, and set up dashboards to track the specific metrics and targets you’ve agreed on with each customer.

Team efficiency

Use efficiency metrics to track your team’s productivity and make sure the workload is distributed evenly. 

Important metrics include:

• Average handling time
• Tickets resolved per team member
• Escalation volume by team or team member
• Team utilization
• Workload distribution across team members

See how Pylon surfaces the numbers that drive real support. Book a demo.

How to get the most out of your support analytics from week one

Here are some practical tips to help you get up to speed quickly and start seeing real value from your customer support analytics:

• Start with the default dashboards. Pylon’s support analytics come with default dashboards covering all the metrics that matter most for B2B support teams. They’re a great place to start exploring analytics because you can quickly establish a baseline understanding of ticket volumes, response times, customer satisfaction, and team performance. Then, once you know which metrics you need to track in more detail, you can build custom charts and reports that address those.
• Build a leadership dashboard early. Create a simple executive dashboard that gives a high-level summary for business leaders. This should exclude the operational details and focus on business outcomes like SLA performance and customer satisfaction. By creating a report that updates automatically, you keep key stakeholders informed and reduce the need for manual reporting.
• Use AI reports for proactive monitoring. Take advantage of AI analytics tools to identify patterns in large amounts of data and get alerts to issues like sudden spikes in ticket volume, recurring customer issues, and potential retention risks.
• Connect your data warehouse. You’ll get more value from your analytics when you pull in more data. Connect your customer support software to your data warehouse and CRM systems to create a comprehensive picture of support performance, customer retention, product usage, revenue, and account health.
• Review weekly, not quarterly. When you only review performance quarterly, it becomes a backward-looking reporting task and a mere box-ticking exercise. Instead, treat analytics as an ongoing operational tool. Monitor data in real time and conduct in-depth analysis on a weekly basis. That way, you can spot issues quickly and make small, fast improvements instead of needing to fix major problems later.

Turn support data into decisions with Pylon

To gain great analytics, you need great data. And that comes from centralizing inputs across all your support touchpoints. 

Pylon is the modern B2B support platform that offers true omnichannel support across Slack, Teams, email, chat, ticket forms, and more. Our AI Agents and Assistants automate busywork and reduce response times. Plus, with Account Intelligence that unifies scattered customer signals to calculate health scores and identify churn risk, we're built for customer success at scale.

Book a demo

FAQ

What kinds of analytics does Pylon offer for B2B support?

Pylon offers seven prebuilt analytics dashboards covering:

• General support metrics (issue volume, TTFR, TTR, touches)
• CSAT
• NPS
• SLA adherence
• Workforce performance
• Community
• AI Agent effectiveness

Every dashboard is filterable by time, tags, assignee, team, and custom attributes. Beyond defaults, teams can build fully custom dashboards with their own charts, formulas, and AI-assisted chart creation.

Want to see which dashboards fit your team’s workflow? Book a demo and we’ll walk you through the analytics that matter most. 

Can I build custom reports and dashboards?

Yes. Pylon’s custom dashboard builder lets you create new dashboards, add custom charts with any combination of metrics and dimensions, build formulas for derived metrics, and use AI to generate charts from plain-language descriptions. Dashboards can be shared with specific teams or roles, so leadership sees high-level KPIs while your support team sees operational details.

Curious about what a custom dashboard looks like? Schedule a demo and we’ll build one live with you.

Can Pylon send automated analytics reports?

Yes. AI Reports lets you schedule automated summaries delivered directly to Slack. You can configure reports to surface escalated issues, product feedback hotspots, accounts with declining satisfaction, or any other pattern you want to monitor. 

Want to see AI Reports in action? Book a demo and we’ll show you how automated summaries work. 

Can I export support data to my data warehouse?

Yes. Pylon supports warehouse sync to Snowflake and BigQuery. This lets you combine support data with product usage, revenue, and other business data for cross-functional reporting. It’s especially useful for teams that need to feed support metrics into executive dashboards or BI tools.

Need help setting up a warehouse sync? Talk to us and we’ll walk through the integration.

Do I need technical skills to use Pylon analytics?

No. Pylon’s Analytics feature is designed for support and CS teams, not data engineers. Default dashboards work out of the box, custom dashboards use a visual builder with drag-and-drop, and the AI chart builder lets you describe what you want in plain language. No SQL, no code, no BI tool expertise required.

See how intuitive it is — book a 30-minute demo and we’ll explore the Analytics features together.