3e:null 3f:["$","title",null,{"children":"Sales Call Analytics: Tracking Team Call Performance | CallSync App | Observable"}] 45:T48a,(() => { const reps = ["Ava","Liam","Maya","Noah","Zoe"]; let s = 42; const r = () => (s = (s * 1664525 + 1013904223) >>> 0) / 4294967296; const calls = Array.from({length: 1500}, () => { const u = r(); const o = u < 0.28 ? "Connected" : u < 0.58 ? "Voicemail" : u < 0.80 ? "No answer" : u < 0.88 ? "Busy" : u < 0.96 ? "Meeting booked" : "Deal advanced"; const c = o === "Connected" || o === "Meeting booked" || o === "Deal advanced"; return {rep: reps[(r() * 5) | 0], outcome: o, duration: c ? 120 + ((r() * 1380) | 0) : 10 + ((r() * 110) | 0)}; }); const conn = ["Connected","Meeting booked","Deal advanced"]; const kpi = reps.map(rep => { const v = calls.filter(d => d.rep === rep); const cv = v.filter(d => conn.includes(d.outcome)); const mt = v.filter(d => d.outcome === "Meeting booked" || d.outcome === "Deal advanced"); return {rep: rep, dials: v.length, connectRate: +(cv.length / v.length).toFixed(3), avgHandleSecs: Math.round(cv.reduce((a,d) => a + d.duration,0) / Math.max(1,cv.length)), meetings: mt.length, dialsPerMeeting: +(v.length / Math.max(1,mt.length)).toFixed(1)}; }).sort((a,b) => b.meetings - a.meetings); return Inputs.table(kpi); })()46:[] 43:{"id":"d013aab0b68f5b2a","slug":"sales-call-analytics-tracking-team-call-performance","title":"Sales Call Analytics: Tracking Team Call Performance","thumbnail":"4bcdbb38b812056305c3a8720a58aed7d90df799e560a1945aac71fdec2fc9b6","access_level":"public","create_time":"$D2026-10-15T16:06:13.820Z","update_time":"$D2026-10-15T16:08:44.612Z","view_time":null,"first_public_time":"$D2026-10-15T16:08:52.595Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"d24848781c38aa75","login":"callsync-app","name":"CallSync App","avatar_url":"https://avatars-next.observableusercontent.com/3adc1198442c876a4bc049bd59506917d6529da77376f22c7bc1c4cd1ef9d641","tier":"free_2026","bio":""},"version":12,"publish_version":12,"role":null,"authored":false,"authors":[{"type":"individual","id":"1868c2387642cfb1","login":"callsync-app","name":"CallSync App","avatar_url":"https://avatars-next.observableusercontent.com/3adc1198442c876a4bc049bd59506917d6529da77376f22c7bc1c4cd1ef9d641","tier":null,"bio":""}],"members":[{"type":"team","id":"d24848781c38aa75","login":"callsync-app","name":"CallSync App","avatar_url":"https://avatars-next.observableusercontent.com/3adc1198442c876a4bc049bd59506917d6529da77376f22c7bc1c4cd1ef9d641","tier":"free_2026","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Sales Call Analytics: Tracking Team Call Performance","cells":[{"id":1,"value":"# Sales Call Analytics: Tracking Team Call Performance\n\nSales teams make hundreds of calls each week, and the teams that improve are the teams that measure. This notebook analyses a sample of sales-call records — the same kind of structured call data captured by [sales call tracking software](https://callsyncapp.com) — to compute the KPIs sales leaders rely on: call volume, connect rate, average handle time, outcome mix, and dials per meeting.\n\n*All data below is synthetic sample data generated in the notebook for demonstration.*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2,"value":"$45","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3,"value":"(() => { let s = 42; const r = () => (s = (s * 1664525 + 1013904223) >>> 0) / 4294967296; const calls = Array.from({length: 1500}, () => { const u = r(); const o = u < 0.28 ? \"Connected\" : u < 0.58 ? \"Voicemail\" : u < 0.80 ? \"No answer\" : u < 0.88 ? \"Busy\" : u < 0.96 ? \"Meeting booked\" : \"Deal advanced\"; return {day: (r() * 30) | 0, outcome: o}; }); const byOutcome = Array.from(d3.rollup(calls, v => v.length, d => d.outcome), ([outcome, n]) => ({outcome: outcome, n: n})); const byDay = Array.from(d3.rollup(calls, v => v.length, d => d.day), ([day, n]) => ({day: day, n: n})); return [Plot.plot({title: \"Call outcome mix (sample data)\", marks: [Plot.barX(byOutcome, {x: \"n\", y: \"outcome\", sort: {y: \"x\", reverse: true}})], x: {label: \"Calls\"}, y: {label: null}}), Plot.plot({title: \"Daily call volume (sample data)\", marks: [Plot.barY(byDay, {x: \"day\", y: \"n\"})], x: {label: \"Day\"}, y: {label: \"Dials\"}} )]; })()","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W46","stdlib":"2"}} 44:"$43:body"