Call Analytics
Score every call.
Coach every rep.
Plaibook connects to your phone system and runs every inbound and outbound call through Google's Gemini. Each call gets transcribed, classified, and scored across 20+ dimensions: sales outcome, checkpoint adherence, objection types, customer sentiment, talk-time ratio, coaching areas, and contract details. No sampling, no manual QA. 100% of calls, scored automatically.
Most teams are live within 24 hours. Free for 30 days.
What Gets Analyzed
20+ fields extracted from every call
You get more than a sentiment score and a transcript. Every call produces a structured document with the fields below, all filterable, sortable, and exportable across your analytics dashboards.
Sales Outcome
- Outcome classification (sold plan, booked inspection, qualified unclosed, unqualified, referred out, abandoned)
- Close type (pest plan sale, termite inspection booked, general inspection booked)
- Recurring contract value and billing frequency (monthly, quarterly, annually)
- One-time service value
- Contract term length in months
- Appointment date and time window
- Number of close attempts made
- Appointment confidence score
Objections & Barriers
- Each objection with the exact customer quote and timestamp
- Whether each objection was overcome
- The rebuttal the rep used and whether it was effective
- Disqualifiers (not in service area, not the decision maker, no pest problem)
- Objections are clustered automatically so you can see "price too high" across all reps, not 50 different phrasings
Customer Service
- Issue severity (critical, high, medium, low)
- Each service issue with customer quote, timestamp, and root cause
- Whether each issue was resolved
- Churn risk level, cancel intent, cancel reason
- Save attempt made and whether it succeeded
- Retention offer and whether it was accepted
- First-call resolution, escalation details, credits/refunds issued
- Customer frustration (1-10 at start), satisfaction (1-10 at end), effort score
Conversation Quality
- Agent talk-time percentage and words per minute
- Customer sentiment at start and end of call
- Key phrases and competitor mentions
- Whether pricing was discussed, urgency level
- Rapport quality score and buying signals with timestamps
- Price sensitivity level
- Agent interruption count
Extracted Data
- Customer name, property address, email
- Pest types mentioned
- Price quoted and competitive situation
- How the customer heard about the company (referral source and referrer name)
- What triggered the call (marketing, referral, etc.)
- Whether the customer mentioned reviews
Coaching & Quality
- Whether the call needs coaching (with specific skill gaps described)
- Each coaching area with a description, severity score, and the exact timestamp
- Commendations for exceptional moments (with timestamps)
- Compliance flags
- One-line summary, detailed summary, recommended next action, and internal notes
100%
of calls scored
20+
fields per call
<5 min
processing time
The AI also detects call type (sales, customer service, retention, technician coordination, voicemail, abandoned), call direction, and primary intent, so calls route to the right dashboard without manual tagging.
Custom Scorecards
Your playbook, enforced on every call
You define a checklist of steps your reps should follow: greeting, discovery questions, value proposition, objection handling, close attempt, offer the termite add-on, whatever matters to your business. Each step has a label and a description that tells the AI what “met” looks like.
The AI evaluates every call against your checklist. Each item gets a pass, fail, or N/A result plus the exact timestamp where it happened (or should have). There is also a short explanation for each item so a supervisor can understand the decision without re-listening.
The overall checkpoint adherence score is the percentage of applicable items that passed. This score appears on every call card, on the wallboard, in skill profiles, and in the coaching DMs.
Decision tree routing
If you handle multiple call types, Plaibook can route calls to different checklists based on plain-English conditions. For example:
IF “Sales call about termites”
Use: Termite Sales Checklist (8 steps)
IF “General pest sales call”
Use: Inside Sales Checklist (12 steps)
IF “Customer calling to cancel”
Use: Retention Checklist (6 steps)
IF “Customer service inquiry”
Use: CS Resolution Checklist (5 steps)
Conditions are plain English and the AI interprets them. A single call can match multiple conditions. You can also override checklists by department, so inside sales and retention use different scorecards even for the same call type.
Scorecard Result
Inside Sales Checklist
71
/ 100
5 of 7 checkpoints passed
Rep said: 'Thanks for calling Frontline, this is Jake, how can I help?'
Asked 3 discovery questions about ants in the kitchen
Confirmed address at 4821 Oak Dr is in zone
Quoted price but did not mention the guarantee
Customer said 'that seems expensive' -- rep compared to cost of termite damage
Asked: 'Can I get you on the schedule for Thursday morning?'
Never mentioned termite services during the call
Click any timestamp to jump to that moment in the recording. Managers can leave coaching comments on specific checkpoints and the rep gets notified in-app and via Slack.
Marcus Johnson → Sarah Chen
Customer called about recurring ant problem. Rep identified entry points, recommended quarterly plan, closed with Thursday inspection.
Objection Intelligence
Which objections kill deals, and which rebuttals win
Every objection from every call is extracted with the customer's exact words, a timestamp, whether it was overcome, and the rebuttal the rep used. These objections are then automatically clusteredusing embeddings. Instead of 200 variations of “that's too expensive,” you see one cluster called “Price Objection” with the count, win rate, and most effective rebuttals.
The same clustering applies to coaching areas, service issues, and cancel reasons. Instead of reading through individual call notes, you see aggregate patterns: “37 calls this week had a price objection, overcome 54% of the time. Top rebuttal: comparing to cost of termite damage (71% win rate).”
Filter by rep to find their weaknesses. Filter by lead source to see if certain campaigns produce harder objections, or by time period to see if training is actually working.
Top objection clusters, this month
Best rebuttal: Compare to cost of pest damage
Best rebuttal: Limited-time pricing + schedule tentatively
Best rebuttal: Ask what they're unhappy about + guarantee
Best rebuttal: Offer callback + send info packet
“The playbook score shows — did they confirm the address, confirm the payment, offer termite? You just look at it and go, ‘okay, this rep didn't build value and then didn't close. That's what we focus on.’”
Braden, Frontline
AI Coaching
Coaching that reaches reps without a meeting
Dashboards are great for managers. But reps need coaching pushed to them directly, through the tools they already check.
Slack coaching DMs
Each rep can receive a coaching DM via Slack on a daily or weekly cadence. Gemini writes the message using that rep's actual call data: their skill profile, recent coaching areas, development curve, and specific call transcripts.
The DM tells them what they're doing well, what patterns they're missing, and links to specific calls they should re-listen to. It also references their previous DM history so coaching builds on itself over time.
Managers get a separate DM with a team-level summary and per-rep coaching recommendations. Choose between in-depth, concise, or custom prompt formats.
Skill profiles and benchmarking
Every rep gets a profile with four core metrics, each compared against the team average and the top performer:
- Close rate
- Checkpoint adherence score
- Objection overcome rate
- Talk-time efficiency
Drill into objection win rates by cluster: how does this rep close on price objections vs. the team? How about “already has a provider”?
Track development curves over time with weekly metrics showing close rate, checkpoint score, coaching areas, and commendation trends.
Coaching comments and threads
Managers can leave coaching comments on any call, tagged to the rep. Comments support threaded replies and reactions, and the rep gets both an in-app notification and a push notification on mobile.
Each comment has a lifecycle: open → acknowledged → resolved. Managers can see at a glance which feedback is still unread.
There is also an AI Coach chatbot in-app. Ask it “show me calls where we lost on price this week” and get answers with links to specific calls and timestamps.
Screenshot: Slack coaching DM with rep-specific feedback and call links
4:3 Slack DM screenshot
Diego Rivera
Inside Sales · 6 months
Top Coaching Areas
Skipped on 8 of last 12 calls
Rushes past objections instead of probing deeper
Rarely mentions seasonal pressure or limited availability
“My guy Dave has been with me for ten years, he knows exactly what to say. But the new guys just freeze up. If they can click a button and see the answer, that changes the game.”
Scott, Ruva Pest
Wallboard & Competitions
A live sales floor dashboard
Put the wallboard URL on your sales floor TV. It updates in real time via WebSocket. When a rep closes a deal, the leaderboard animates, values tick up, and a toast notification shows the agent name, outcome, and revenue. Auto-refreshes every 60 seconds with no manual input needed.
Leaderboard columns
Columns and top-level metric cards are configurable. Hide anything that doesn't apply to your team, sort by any column, or filter by department.
Today's Leaderboard
Ranked by Revenue
Competitions
Create time-boxed competitions with prizes. Competitions can target all agents, a specific department, or hand-picked reps. They can recur daily or weekly. When you enable the Slack integration, Plaibook creates a dedicated Slack channel, invites participants, and posts daily leaderboard updates with deep links back to the analytics dashboard.
“The TV display is the best part. They're always just looking at the screen — ‘Where am I at? What do I gotta do?’”
Isaac, Ridd
Analytics Dashboards
Seven dashboards, each with a different lens
All dashboards share a consistent filter bar: date range, agent, department, call type, lead source, and direction. Export any view to CSV.
Sales performance (closed won/lost)
Close rates, deal values, revenue trends, outcome breakdown by rep. Filter by lead source to see which marketing channels produce closeable leads vs. tire kickers. Daily or weekly granularity.
Marketing attribution
Revenue attributed to each lead source, campaign, keyword, and ad group. Supports UTM parameters, Google Ads click IDs, CallRail/CTM tracking numbers, and multi-touch attribution (first touch and last touch). Ties ad spend to closed revenue, not just lead count.
Customer service
Service issue clustering, resolution rates, first-call resolution, escalation rates, credits and refunds issued. Tracks customer frustration and satisfaction scores over time so you can see which issues drive the most repeat calls.
Retention intelligence
Cancel reasons clustered and ranked by frequency. Save attempt rates and success rates by rep. Retention offer effectiveness and churn risk levels. See who called to cancel, whether the save worked, and what offer was made.
Team coaching
Coaching areas clustered and ranked by how often they come up. See which skill gaps are most common across the team, then drill into individual reps for their coaching history, development curve, and specific call examples.
Overflow and missed calls
Calls that went unanswered, abandoned, or hit voicemail. See patterns by time of day, day of week, and department to find staffing gaps that are costing you revenue.
Close Rate by Time
Every dashboard supports clicking through to individual calls. When you see a stat you want to investigate, click it and the call list filters to show exactly those calls. Open any call to see the full scored detail: recording playback, transcript, checkpoint results, objections, coaching areas, and the AI-generated summary.
Under the Hood
How call processing works
Recording ingestion
Calls come in from your phone system via webhook or API polling. Plaibook supports Five9, Genesys, CallRail, GoHighLevel, RingCentral, Zoom, Dialpad, CTM, GoTo, and more. Recordings are stored encrypted in S3. Transfer calls with multiple legs get stitched into a single timeline.
Transcription and classification
Audio is transcribed with speaker diarization. The AI classifies the call type (sales, customer service, retention, technician coordination, voicemail, abandoned) and direction (inbound/outbound), which determines the analytics dashboard and checkpoint checklist.
Structured analysis
Gemini processes the full transcript and produces a structured JSON document with all the fields listed above: sales outcome, objections, customer service details, conversation analytics, extracted data, quality metrics, and coaching areas. Every field includes timestamps pointing to the exact moment in the call.
Checkpoint evaluation
If you have a checkpoint tree or checklist configured, the AI evaluates the call against each applicable step. Each checkpoint gets a pass/fail/N/A result, a timestamp, and a context note for supervisors. The adherence score is the percentage of applicable items that passed.
Clustering and enrichment
Objections, coaching areas, service issues, and cancel reasons are embedded as vectors and clustered across your organization. Hundreds of freeform descriptions collapse into a handful of useful categories. Clustering reruns periodically to tighten groupings as more data comes in.
Real-time distribution
The scored call appears in dashboards immediately and the wallboard updates via WebSocket. Calls that need coaching get flagged in the coaching queue. Slack DMs go out on the configured cadence. Unclosed calls with follow-up potential can be routed to the SMS recovery system.
Manual QA vs. Plaibook
What changes when you score 100% of calls
Manual QA
- Listen to 5-10 calls per rep per week
- Subjective scoring by whoever reviews
- Feedback delivered days later in a 1:1
- No aggregate data across objections or coaching areas
- Can't filter by lead source, time of day, or call type
- Hours per week of manager time
Plaibook
- 100% of calls scored, every day, no exceptions
- Consistent, objective scoring against your defined playbook
- Coaching pushed to reps within hours via Slack DMs
- Objections, coaching areas, and service issues clustered and ranked
- Filter and drill into any dimension across all dashboards
- Zero manager time on QA, so they can focus on coaching instead of grading
“Sales reps are gonna lie. The leaderboard said one of my guys was at 100% close rate — because he was only submitting calls he actually sold. Plaibook helps us figure out the leaks.”
Kellin, Vult
Getting Started
What you'll see in your first week
Most teams go from signup to scored calls in under 24 hours. Here is what the first week typically looks like.
Day 1
Phone system connected
We connect your phone system and start ingesting recordings. Your first batch of scored calls arrives the same day.
Day 2
Scorecards configured
Your checkpoint checklists are set up based on your playbook. Calls start scoring against your specific criteria.
Day 3-4
Patterns emerge
Objection clusters, coaching areas, and close rate data start showing meaningful patterns. Your dashboards populate.
Day 5-7
Coaching begins
Slack coaching DMs go out. The wallboard goes live. Managers can see which reps need attention and why.
Call analytics is one piece of the platform
Plaibook connects scoring, coaching, and follow-up into a single system.
See It In Action
Watch a 3-minute walkthrough
Product walkthrough video
Scoring a call, reviewing the scorecard, coaching DMs, and the wallboard
See what your calls are actually telling you
We connect your phone system, configure your checkpoint scorecards, and show you the first batch of scored calls. Usually takes about a day.
Free for 30 days. No credit card. No annual contract.
Questions about your phone system? Check supported integrations or get in touch.