Customer Service
The AI Workspace for Customer Service Teams
Connect tickets, CSAT, call logs, and product data into live Spaces for shared service and product decisions.
Service data is everywhere, but no shared picture
- Metrics scattered across Zendesk, Intercom, call logs, and product telemetry
- Teams repeat: "What's causing repeat tickets?" "Why is CSAT dropping?"
- Weekly reviews require manual exports from multiple systems
- No single view of ticket trends, agent performance, or product issues
Use Cases
Customer service use cases on LamLam
Real questions your team asks every day — answered instantly and saved as live Spaces.
Ticket trends
Ask LamLam
"What's causing our highest volume ticket types this month?"
You know volume is up, but figuring out why means digging through five dashboards. LamLam surfaces top issues, resolution patterns, and repeat drivers instantly.
What you get
- Top ticket categories by volume and growth
- Average resolution time by issue type
- Repeat ticket rate and root causes
- Saved as a live Space the whole team sees
Zendesk
IntercomThought for a few seconds
Let me pull ticket data for this month — I'll group by category, compare volumes to last month, and look at repeat-ticket patterns to find the root drivers.
"Billing & Invoicing" tickets surged 62% MoM, accounting for 34% of total volume. 45% are repeat contacts — most stem from the new pricing page confusion.
ZendeskIntercomAgent performance
Ask LamLam
"Which agents have highest first-contact resolution?"
Coaching conversations are better when backed by data, not gut feel. LamLam gives managers a clear view of agent effectiveness so they can support the right people.
What you get
- First-contact resolution rates by agent
- CSAT scores broken down by agent
- Average handle time and escalation rate
- Trend lines that highlight improvement or dips
Top 3 agents resolve 78% of tickets on first contact vs. team average of 54%. Agents with under 6 months tenure have 2x the escalation rate — coaching could close the gap.
Product pain points
Ask LamLam
"Which product features generate most support tickets?"
Support knows where the product hurts, but that signal gets lost before it reaches product teams. LamLam bridges the gap with shared, always-current data.
What you get
- Ticket volume mapped to product features
- Sentiment analysis by feature area
- Escalation rates and severity distribution
- Shared Space for service + product alignment
"Exports" generates 3x more tickets than any other feature — mostly around CSV formatting and timeouts. The Jira backlog already has 4 related issues open.
Why customer service teams choose LamLam
Collaboration-first
Spaces keep tickets and product decisions together, no more screenshot ping-pong.
Your tools, no rip-and-replace
Zendesk, Intercom, Gong, product telemetry, connect in clicks, not sprints.
Always-live data
Ticket trends and CSAT always current, no manual refreshes.
Managers + agents
Leaders see service health, agents get the context they need.
See your service data in a live Space
Share your Zendesk and call data, we'll build your first Service Space live in 15 minutes.