How a Support Lead Reviews 18 Agents in 15 Minutes

AndeanBet is a Bogotá-based multi-vertical iGaming platform serving approximately sixteen thousand monthly active players across Colombia, Peru, and Ecuador, with a growing base in Chile. The platform runs casino slots and sports betting — Fútbol Colombiano, Copa América, and European football fixtures carry the wagering weight — with transactions settled in both COP and USDT. At $2.5M per week in gross gaming revenue, AndeanBet operates at a pace that generates a high, consistent volume of player contacts. Eighteen support agents work across two shifts, handling everything in Spanish and Portuguese, fielding questions on payments, account verification, bonus terms, and the occasional live betting dispute.

Products used: Support Analytics, Agent Performance, Training Gap Detection

15 minutes | full 18-agent monthly review time

18 agents reviewed | across resolution time, CSAT, and first-contact resolution rate

2 training gaps identified | CSAT up 4 points month-over-month

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Challenge

The last working day of every month, Valentina Rojas blocks two hours on her calendar and dreads it. Her director expects a performance report that covers every agent on the team — resolution time trends, CSAT scores, first-contact resolution rates, ticket category breakdown — along with a set of concrete recommendations for the month ahead. It's the kind of review that determines who gets a bonus, who gets coaching, and whether Valentina gets more headcount in the next budget cycle.

The problem was never a lack of data. AndeanBet's helpdesk software logged everything. The problem was that "everything" was scattered. CSAT scores lived in one export. Resolution time averages required a separate pull. First-contact resolution rates had to be calculated manually by cross-referencing ticket threads against agent IDs — a task that took Valentina's senior analyst the better part of an afternoon. By the time the spreadsheet came together, Valentina had four hours until the director meeting and a table of averages that told her almost nothing about what was actually causing the gaps.

"Every month I'd get a spreadsheet with averages and I'd spend two hours trying to figure out what it meant. Agent X has an average CSAT of 3.9 — okay, but which ticket types? Which hour of day? What's driving it? The data never told me why. It just told me that something was wrong and left me to guess the rest."

— Valentina Rojas, Customer Support Lead, AndeanBet

The coaching recommendations were the hardest part. Valentina knew her team well enough to spot who was struggling — but she couldn't walk into a director meeting with "I have a feeling about agent twelve." She needed specifics: which ticket categories had the longest resolution times, which agents were handling a disproportionate share of the complex escalations, and whether the CSAT dip she'd noticed in the third week of the month was a training issue, a workload issue, or a product issue. None of those questions had quick answers in a static spreadsheet.

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Solution

On the last Wednesday of the month, Valentina opens Gaming Mind AI and runs her entire monthly review as a single conversation. She shares the session summary with her director the same afternoon, with specific coaching recommendations attached. What used to take two hours of prep plus an analyst's half-day now takes fifteen minutes.

Here's what last month's review looked like:

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Valentina: "Give me the full team performance summary for last month — resolution time, CSAT, first-contact resolution, by agent."

KPI	Current Month	Prior Month	Change	Status
Team CSAT (out of 5.0)	4.1	3.7	+4 points	🟢 Improving
Average Resolution Time	11.4 hours	13.8 hours	−17%	🟢 Improving
First-Contact Resolution Rate	68%	61%	+7 pp	🟢 Improving
Agents below team median (all 3 metrics)	3	—	—	🔴 Needs investigation

⚠️ Gaming Mind flags: Three agents — positions 14, 16, and 18 in the ranking — are sitting significantly below the team median across all three metrics. Gaming Mind recommends drilling into each one separately, because their root causes are likely different.

The overview landed as a ranked view of all eighteen agents, not a table of averages. Overall team CSAT came in at 4.1 out of 5.0 — up four points from last month's 3.7 baseline, which was the clearest signal yet that the new escalation protocol introduced six weeks ago was working. Average resolution time held at 11.4 hours, down from 13.8 hours in the prior period. First-contact resolution rate hit 68%, up from 61%. But Gaming Mind immediately flagged that three agents — positions fourteen, sixteen, and eighteen in the ranking — were sitting significantly below the team median across all three metrics and recommended drilling into each one separately.

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Valentina: "Walk me through the bottom three agents. What's actually going on with their numbers?"

Agent	Key Metric (Issue)	Score	Team Median	Root Cause (Initial)
Agent 14	Avg resolution time	14.1 hours	~11.4 hours	Slow on payment tickets only (22h for that category)
Agent 16	CSAT	3.2	4.1	Low scores concentrated in KYC/verification contacts
Agent 18	First-contact resolution rate	41%	68%	Highest re-open rate on team (2x average)

⚠️ Gaming Mind flags: Three underperformers, three completely different root causes — invisible in aggregate averages. Each requires a separate diagnostic before any coaching decision is made.

The three underperformers had different root causes, which the aggregate averages had completely obscured. Agent Fourteen had a 14.1-hour average resolution time — but only on payment and withdrawal tickets, where she was hitting 22 hours while performing at the team median everywhere else. Agent Sixteen's CSAT was 3.2, a full point below team average, but his resolution times were fine — the low scores concentrated almost entirely in KYC and verification contacts, where players rated the interaction poorly regardless of the outcome. Agent Eighteen had the lowest first-contact resolution rate on the team at 41%, with the highest re-open rate — players were contacting support again within 48 hours of a "resolved" ticket at more than twice the team average. Three agents, three completely different problems.

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Valentina: "What's causing Agent Fourteen's slow resolution time on payment tickets specifically?"

Metric	Agent 14	Team Average	Notes
Time-to-first-response (payment tickets)	18 min	~22 min	Faster than average
Time in "pending" after first response	19.2 hours	~8.5 hours	🔴 Waiting on payment ops
Tickets routed to payments team (crypto withdrawals)	High	Low	Uses ops handoff instead of self-service guide
Use of withdrawal self-service resolution guide	Rarely	Standard	Guide published 3 months ago

⚠️ Gaming Mind flags: Agent 14's slow resolution time is a process training issue, not a skill gap. She is the only morning-shift agent consistently routing crypto withdrawal queries to the payments team instead of using the self-service guide. One coaching session on the guide would likely cut her payment resolution time in half.

Gaming Mind surfaced the pattern without Valentina having to frame the question precisely. Agent Fourteen's time-to-first-response on payment tickets was actually faster than the team average — she was responding within 18 minutes — but her tickets were sitting in "pending" status for an average of 19.2 hours after that first response while she waited for payment operations to confirm. This wasn't a skill gap. It was a handoff problem. She was the only agent on the morning shift consistently routing crypto withdrawal queries to the payments team rather than resolving them from a self-service guide that the payments team had published three months ago. Gaming Mind flagged this as a process training issue, not a performance issue — one coaching session on the withdrawal resolution guide would likely cut her payment resolution time in half.

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Valentina: "Agent Sixteen's CSAT is low on KYC tickets — is that an agent problem or a product problem?"

Category	CSAT (Agent 16)	CSAT (Team Avg)	CSAT (KYC Category Avg)	Gap vs Category
KYC / Verification	3.2	4.1	3.4	−0.2 (within noise)
All other categories	~4.1	4.3	—	On par with team
Players citing wait time in low CSAT	Majority	—	—	72h+ document review delays
Agent tone cited as negative	Rare	—	—	Not the driver

⚠️ Gaming Mind flags: Agent 16 is inheriting frustration from a product bottleneck — players waiting 72+ hours for document review decisions upstream of support. His 3.2 KYC CSAT is only 0.2 below the team's category average. This is an operations escalation, not a coaching item.

The data split the question cleanly. KYC and verification tickets had the lowest CSAT scores across the entire team — the team average for that category was 3.4, compared to 4.3 for all other categories. Agent Sixteen's 3.2 on KYC was below the category average, but only by 0.2 points. Gaming Mind pulled the player comment sentiment for his KYC tickets and found that the low scores consistently referenced verification wait times and document rejection notices — not agent tone, not communication quality, not response speed. For six of his lowest-rated tickets, Gaming Mind flagged that players had been waiting more than 72 hours for a document review decision before the ticket was even passed back to support. Agent Sixteen was inheriting the frustration from a process bottleneck upstream of him. That was a product and operations escalation, not a coaching item.

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Valentina: "Agent Eighteen has a 41% first-contact resolution rate. Why are players reopening tickets?"

Metric	Agent 18	Team Average
First-contact resolution rate	41%	68%
Re-open rate (within 48h of "resolved")	~2x team average	Baseline
Re-opens in bonus/promotions category	67% of total re-opens	Low
Re-opens citing incorrect/incomplete answer	Majority	—
Bonus terms update: 8 weeks ago	Missed internal update	All other agents briefed

⚠️ Gaming Mind flags: Agent 18's re-open problem is concentrated in one topic area — bonus and promotions — where the platform updated its bonus structure 8 weeks ago and he apparently missed the internal update. A structured knowledge check on the new terms, followed by two weeks of reviewed responses in that category, is the specific remediation.

This one was a genuine skill gap. Gaming Mind analyzed the reopen reasons on Agent Eighteen's tickets and found that 67% of reopened tickets were in the bonus and promotions category — players were coming back to say the answer they received was wrong or incomplete, not that the issue hadn't been resolved yet. Gaming Mind cross-referenced his responses against the bonus terms documentation and found repeated instances where he'd confirmed eligibility criteria incorrectly or omitted wagering requirements. This wasn't a random distribution of errors — it was concentrated in one topic area where the platform had updated its bonus structure eight weeks ago, and Agent Eighteen had apparently missed the internal update. A structured knowledge check on the new bonus terms, followed by two weeks of reviewed responses in that category, was the specific recommendation.

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Valentina: "Show me ticket category trends across the whole team — what's changed versus last month?"

Category	MoM Change	Direction	Action Required
Payment & withdrawal contacts	−14%	🟢 Down	Self-service FAQ absorbing routine queries
Bonus disputes	+21%	🔴 Up	Bonus structure update 8 weeks ago causing confusion at scale
Technical issues (mobile casino / Android)	+18%	🔴 Up	Android-specific — escalate to product team
Account access	−8%	🟢 Down	Self-service improvements working
General inquiries	−5%	🟢 Down	Stable
KYC / Verification	+6%	🟡 Up	Upstream document review delays
Live betting disputes	+3%	🟡 Stable	Within normal range
Promotions (general)	+9%	🟡 Up	Related to bonus structure confusion

⚠️ Gaming Mind flags: Two categories need immediate escalation — the 21% bonus dispute rise confirms the bonus structure update is generating confusion across the whole team (not just Agent 18), and the 18% Android technical issue rise needs a product team ticket before it compounds.

The category mix had shifted meaningfully in thirty days. Payment and withdrawal contacts fell 14% as the platform's new self-service payment FAQ absorbed a chunk of routine queries — a concrete return on the investment the product team had made in the knowledge base. But two categories were moving in the wrong direction. Bonus disputes climbed 21%, confirming that the bonus structure update eight weeks ago was generating confusion at scale — not just for Agent Eighteen, but across the whole team. And technical issue reports were up 18% month-over-month, concentrated in the mobile casino category on Android devices. Gaming Mind flagged both signals and recommended escalating the Android issue to the product team, and scheduling a team-wide briefing on the updated bonus terms before the end of the week.

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Valentina: "How is workload distributed across the team? Anyone overloaded, anyone underutilized?"

Segment	Agents	Ticket Volume Share	Escalation Share	Complexity-Weighted Load
3 most-experienced (afternoon shift)	3	31% of total volume	44% of all escalations	🔴 Overloaded
Remaining 15 (mixed shifts)	15	69% of total volume	56% of escalations	🟢 Balanced
Average per agent (all)	18	187 tickets/month	—	Headline balanced; complexity tells different story

⚠️ Gaming Mind flags: Three senior agents are absorbing 44% of all escalations while handling only 31% of total ticket volume — quietly overloaded. Capping consecutive complex tickets per agent and auto-routing to the next available is projected to reduce resolution time on high-complexity contacts by 20%.

The headline number looked balanced — an average of 187 tickets per agent over the month — but Gaming Mind's complexity weighting told a different story. Three agents on the afternoon shift were handling a disproportionate share of escalated and multi-turn tickets: combined, they accounted for 44% of all escalations while handling only 31% of total ticket volume. These were the team's three most experienced agents, and they were being quietly overloaded with the difficult cases while newer agents on the morning shift handled a lighter distribution. Gaming Mind projected that rebalancing escalation routing — setting a cap on consecutive complex tickets for any single agent before auto-routing to the next available — would reduce burnout risk on those three agents and compress average resolution time by an estimated 20% on high-complexity contacts.

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Valentina: "Give me a one-page summary I can send to my director this afternoon — overall performance, key findings, and recommendations."

Section	Finding	Action
Team CSAT	4.1 (+4 pts) — escalation protocol working	No change needed
FCR Rate	68% (+7 pp)	No change needed
Avg Resolution Time	11.4h (−17%)	No change needed
Agent 14	Process gap — payment self-service guide	1 coaching session
Agent 16	Product/ops bottleneck — KYC delays	Escalate to ops; not a coaching item
Agent 18	Knowledge gap — bonus terms update	Structured knowledge check + 2 weeks supervised responses
Escalation routing	3 senior agents absorbing 44% of escalations	Rebalancing change → projected −20% complex resolution time
KYC CSAT floor	Category avg 3.4 driven by 72h+ doc review delays	Product team ticket — not an agent quality issue

⚠️ Gaming Mind flags: Two genuine training gaps were identified and separated from two process/product issues. The director received root causes with specific actions attached — not a table of averages with gut-feel coaching notes.

Gaming Mind produced a structured summary Valentina sent with one edit — she added the date. Overall CSAT was up four points to 4.1, first-contact resolution rate improved seven percentage points, and average resolution time fell 17%. The two identified training gaps were clearly separated from the process and product issues: Agent Fourteen needed one session on the payments self-service guide, Agent Eighteen needed a structured bonus terms knowledge check and two weeks of supervised responses in that category. The KYC CSAT issue and the Android technical contacts were escalated to operations and product respectively, not treated as coaching items. One process change — rebalancing the escalation routing across shifts — was projected to reduce complex-ticket resolution time by 20%.

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Results

Monthly review went from a half-day process to 15 minutes

Valentina's conversation — from team overview to director-ready summary — took fifteen minutes. Her analyst's half-day of spreadsheet work was eliminated entirely. The director received the report the same afternoon with specific, evidence-backed recommendations instead of a table of averages with a covering note.

Two genuine training gaps identified, one process fix scoped

Gaming Mind separated what looked like three underperforming agents into three completely different root causes. Only two required coaching. Agent Fourteen's slow resolution time traced to a process gap, not a skill gap — one briefing on the payment self-service guide resolved it without a formal performance conversation. Agent Eighteen's first-contact resolution problem was a genuine knowledge gap on the updated bonus terms, identified and scoped for structured remediation within the same session.

One process change projected to cut complex-ticket resolution time 20%

The escalation routing imbalance — three senior agents absorbing 44% of all complex tickets — was invisible in the monthly averages. Gaming Mind surfaced it through complexity-weighted workload analysis. The rebalancing recommendation, which Valentina escalated to her operations lead the same afternoon, is projected to reduce resolution time on high-complexity contacts by 20% once implemented in the next scheduling cycle.

CSAT up 4 points, with a clear signal on where the next 4 come from

The team CSAT improvement from 3.7 to 4.1 validated the escalation protocol change from six weeks earlier. More importantly, the analysis showed where the ceiling was: KYC contacts were dragging the category average to 3.4 because of upstream document review delays, not agent quality. Fixing the product-side bottleneck — not coaching agents — was the path to the next CSAT improvement. That recommendation went to the product team with specific ticket data attached.

"I used to walk into the director meeting with a spreadsheet and a set of gut feelings I couldn't fully defend. Now I walk in with root causes, separated from each other, with a specific action for each one. The director spent ten minutes on the report instead of forty, because every number had an explanation attached to it."

— Valentina Rojas, Customer Support Lead, AndeanBet