Ops Activity Analysis — Gururaj & Sonali

Last 2 months · 2026-04-08 → 2026-06-08 · Data sources: Knowlarity calls + Google Meet sessions (argonaut_task.meet_participants) + Spaces messages + SIP dialer subset

Executive Summary — total touchpoint time

Three time-spend buckets now tracked: (1) Phone calls from Knowlarity (master log of mobile + SIP dialer), (2) Google Meet sessions joined as a participant — meet_code-deduplicated so a meet is counted once even if multiple tasks reference it, (3) Spaces messaging as messages authored.
Why this matters: Sonali looked "low output" on calls alone — but she does ~3× more time in Google Meet than the phone. The full picture is materially different.

GURURAJ R Operations Associate

Phone calls

882

62h 30m

Meet sessions

204

66h 09m

Spaces msgs

5,906

~73h effort

Total voice/face

128.7h

calls + meets

Total visible

~202h

over 60 days

SONALI BISHT Study Abroad Ops Executive

Phone calls

280

11h 54m

Meet sessions

153

36h 57m

Spaces msgs

3,721

~46h effort

Total voice/face

48.8h

calls + meets

Total visible

~95h

over 60 days

Bottom line. Adding Google Meet flips the picture meaningfully. Gururaj still does 2.6× more visible work per day (~3.4h vs ~1.6h), but Sonali isn't idle — she's shifting her time to video consultations (3.1× more Meet time than phone). Her phone funnel is the weakest part of her week. The right intervention is to fix her phone connect-rate, not to ask her to do more meetings.

Where the time goes — aggregate split

Gururaj — visible time mix

Sonali — visible time mix

Phone talktime Google Meet Messaging effort (45s/msg)

Pie segments are total seconds over the 2-month window. Messaging is estimated effort, calls/meets are measured. Note how Sonali's Meet slice dwarfs her phone slice — she's primarily a video-consultation rep.

Daily total working time (stacked: phone + meet + messaging)

Gururaj — minutes per day

Sonali — minutes per day

Phone talktime Google Meet Messaging effort (msg × 45s)

Monthly breakdown — with Meet column added

User	Month	Calls	Conn %	Call talktime	Meets	Meet duration	Avg meet	Messages	Voice+face total
G	2026-04 (Apr 8→30)	325	74.8%	24h 03m	83	29h 36m	21m 24s	2,475	53h 39m
G	2026-05	432	79.4%	30h 19m	107	31h 57m	17m 55s	2,840	62h 16m
G	2026-06 (Jun 1→8)	125	63.2%	8h 08m	14	4h 36m	19m 42s	591	12h 44m
G Total	2 months	882	75.4%	62h 30m	204	66h 09m	19m 27s	5,906	128h 39m

S	2026-04 (Apr 8→30)	55	83.6%	2h 28m	68	15h 30m	13m 40s	1,324	17h 58m
S	2026-05	178	76.4%	7h 50m	65	16h 50m	15m 32s	2,052	24h 40m
S	2026-06 (Jun 1→8)	47	44.7%	1h 37m	20	4h 37m	13m 53s	345	6h 14m
S Total	2 months	280	72.5%	11h 54m	153	36h 57m	14m 29s	3,721	48h 51m

Daily Meet time only

Daily phone talktime + connection rate

Daily Spaces messages

GURURAJ R — Performance summary & next steps

Visible work / day

~3.4 hr

across 60 active days

Voice + face daily avg

~2.1 hr

phone + meet

Engagement consistency

High

7+ calls on almost every workday

What's working

Volume engine. 882 calls + 204 meets + 5,906 messages over 60 days is consistent high-output behaviour. He's the floor-setter for the team.
Call connect rate of 75–79% in April–May is healthy and indicates good lead targeting / TOD discipline.
Adopted the in-platform SIP dialer — share moved from 54% → 64% across the period, the kind of platform-hygiene we want.
Strong peak days on Tuesdays/Thursdays (May 15: 39 calls, 8h talktime). Pattern reads like a deliberate "high-touch days" rhythm.

What needs attention

June dip in connect rate: 63% vs 79% in May. Worth checking whether the lead source mix changed (which marketing campaign / which intake?). Treat as a leading indicator before it shows up in pipeline.
Meet load is heavy: 19m 27s average per meet × 204 meets = 66h. Coupled with 62h phone, that's ~2.1h/day of live voice/face. Risk of decision-fatigue late afternoon — check his call quality post-3pm IST.
Messages-to-calls ratio: 6.7 messages per call. Some of this is Instagram DMs (visible in sample data). Make sure he's not stuck in low-conversion DM threads.

Recommended next steps for Gururaj

Cap Meet volume at ~5/day and protect 2 dedicated calling blocks. Right now Meets compete with phone time on his busiest days.
Audit the June 5 + June 7 low days (only 6 and 0 calls). If they're planned leaves, fine. If not, root-cause.
Promote his call cadence pattern as a team standard — he's the natural benchmark for what 60-day consistency looks like.
Re-look at lead-source quality for June — the connect-rate drop is more likely an intake/campaign issue than a Gururaj issue, given his prior numbers.

SONALI BISHT — Performance summary & next steps

Visible work / day

~1.6 hr

across 60 active days

Voice + face daily avg

~49 min

phone + meet

Phone connect rate (Jun)

44.7%

vs 83.6% in April

What's working

Strong Meet engagement. 153 video sessions × ~14m average = 36h 57m. She's clearly carrying the consultation load — Meet is 3.1× her phone time.
Messaging ramped up: 1,324 → 2,052 across April → May = +55% MoM. She's actively engaging on Spaces, not just sitting on inbound.
Adopted SIP dialer fast: 11% in April → 66% in May. Strong platform-adoption signal.

What needs attention (critical)

Phone connect-rate collapse in June (44.7%, down from 83.6%). June 2 alone she made 24 attempts and connected only 6. This is the single most actionable signal in the dataset.
Phone talktime is only 11.9h over 2 months — that's ~6 minutes per active workday. If her role expects significant outbound phone, she's not hitting it.
Average phone call is 2m 33s (vs Gururaj's 4m 15s). Short calls usually mean discovery/qualification — fine if intentional, problematic if leads are dropping off after first connect.
Many low / single-digit weekdays: Apr 12, 16, 18, 22–25 (some workdays with only 1-3 calls). Check whether she was assigned other duties on those days.

Recommended next steps for Sonali

Diagnose the connect-rate drop urgently. Pull her June phone attempts: are they fresh leads, age-old MQLs, or re-tries on cold numbers? This is the most important investigation.
Set a phone floor: aim for ≥10 connected calls per day. Currently she averages 4.3 connected/day. The leverage is high — she's already in 153 meets, those leads were calls first.
Audit short-call conversions. If 2m 33s calls aren't progressing leads to a Meet booking, change the script. If they are, she's actually efficient — but we need the funnel data to know.
Lean into her Meet strength: she's likely the right person to own consultation-day operations. Codify her cadence (~14m per Meet × 3 per day) into a SOP for the team.
Pair her with Gururaj for 1 week on phone-cadence. The gap is structural, not effort-based — she'd benefit from observing his calling block rhythm.

Methodology & caveats

Window: 2026-04-08 00:00 UTC → 2026-06-09 00:00 UTC.
Calls source: argonaut_counsellors_call_history, matched on crm_user. Knowlarity is the master log — includes both direct-mobile and SIP-dialer calls (verified via May 15 spot-check).
Meet source: argonaut_task with meet_participation_processed: true, unwound on meet_participants array, filtered to email. Deduplicated by meet_code so a meet appearing in two tasks (lead + counsellor) counts once. duration field on each participant taken as their attendance seconds.
Messages source: conversationmessages where author = gamePlayerId.
Messaging effort assumption: 45 seconds per message — covers read+think+type. Conservative; some are one-liners, some are long replies.
"Total visible work" = phone talktime + meet duration + messaging effort. Does NOT include: time spent reading inbound, internal-team Spaces, CRM/doc review, planning, breaks. So real workdays are larger than shown.
Identity map: Gururaj R = gururaj@navigus.in / gamePlayerId 6992afeef560500014817c75; Sonali Bisht = sonali@navigus.in / gamePlayerId 69a830fb3fbb4c001325940b.

Daily Metrics Tracker

A consolidated daily log of all visible activity across phone, Google Meet, and Spaces messaging. Use the filters to scope by date range or person. Export as CSV for sharing or spreadsheet tracking. Weekends are shaded; the column "Total" sums phone talktime + meet duration + messaging effort (msg × 45s).

Legend: Calls count + connected count + talktime (HH:MM:SS) Meet session count + duration Msgs messages authored on Spaces Uniq Leads = distinct leads reached via connected call, Meet, or message Total = phone + meet + (msgs × 45s)

Date	Day	GURURAJ							SONALI
Date	Day	Calls	Connect%	Call time	Meet (n / time)	Msgs	Uniq Leads	Day total	Calls	Connect%	Call time	Meet (n / time)	Msgs	Uniq Leads	Day total

How to use this as a daily standup tracker

Daily standup (10 min): Open this tab, set "From" to yesterday's date, scan the row. Anything below the 30-day rolling median is a discussion point.
Weekly review (Friday 30 min): Set "From" to Monday of this week. Look at totals at the bottom — compare against last week's bar in the Analysis tab.
1:1 prep: Filter to one person + last 2 weeks. Pair the trend with the Analysis-tab connect-rate chart to spot whether the issue is volume or quality.
Share with the team: Click "Export CSV" — the file works directly in Google Sheets / Excel for whoever doesn't have CoWork access.