2c:null 2d:["$","title",null,{"children":"Kundenbindung - ein quantitatives Geschäftsmodell | Matthias Berth | Observable"}] 32:T53e,Simulation = function() { this.cohorts = []; this.addCohort = function(name, count) { var cohort = new Cohort(name); cohort.append(name, count); this.cohorts.push(cohort); return cohort; } this.timeStep = function(period, count, retentionRate) { this.cohorts.forEach((cohort) => cohort.retain(retentionRate, period)); return this.addCohort(period, count); } this.asDataFrame = function() { var answer = []; this.cohorts.forEach((cohort) => answer = _.concat(answer, cohort.asDataFrame())); return answer; } this.lastTotal = function(basketValue) { var counts = this.cohorts.map((cohort) => cohort.lastCount()); return basketValue * Math.round(counts.reduce((a, b) => a + b, 0)) } this.totals = function() { var groups = _.groupBy(this.asDataFrame(), row => row.period); var answer = [] for(var group in groups) { var values = groups[group].map(v => v.count); answer.push({period: group, count: _.sum(values)}); } return answer } this.run = function(retention) { var allMonths = _.flatten([2017, 2018, 2019].map((y) => d3.range(1,13).map((m) => "" + y + "-" + _.padStart(m, 2, "0")))) allMonths.forEach( (month) => this.timeStep(month, 1000, retention) ); return this; } }33:[] 30:{"id":"628c3fcb201ebeaa","slug":"kundenbindung-ein-quantitatives-geschaftsmodell","title":"Kundenbindung - ein quantitatives Geschäftsmodell","thumbnail":"86b94956d0cbc1b97dc828d2c6df22d764364a18e142c683eb241aaa674142f6","access_level":"public","create_time":"$D2019-09-27T18:05:04.443Z","update_time":"$D2019-10-01T15:56:40.953Z","view_time":null,"first_public_time":"$D2019-10-01T13:05:14.701Z","has_unpublished_edits":null,"fork":false,"stars":1,"starred":false,"owner":{"type":"team","id":"a50aa619c0e40b41","login":"mberth","name":"Matthias Berth","avatar_url":"https://avatars-next.observableusercontent.com/b8ed279778d50d2a8ac876f3d7c980fdb39847d52cf82912c2a504716a813923","tier":"starter_2024","bio":""},"version":892,"publish_version":892,"role":null,"authored":false,"authors":[{"type":"individual","id":"bff32e41053aecff","login":"mberth","name":"Matthias Berth","avatar_url":"https://avatars-next.observableusercontent.com/b8ed279778d50d2a8ac876f3d7c980fdb39847d52cf82912c2a504716a813923","tier":null,"bio":""}],"members":[{"type":"individual","id":"bff32e41053aecff","login":"mberth","name":"Matthias Berth","avatar_url":"https://avatars-next.observableusercontent.com/b8ed279778d50d2a8ac876f3d7c980fdb39847d52cf82912c2a504716a813923","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Kundenbindung - ein quantitatives Geschäftsmodell","cells":[{"id":0,"value":"md`# Kundenbindung - ein quantitatives Geschäftsmodell`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"md`Ein quantitatives Geschäftsmodell erlaubt schnelle “Was-Wäre-Wenn”-Betrachtungen für die Ziele von Projekten und Initiativen. Hier ist ein einfaches Modell für den Einfluss der Kundenbindung auf den Umsatz.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":107,"value":"md`Die Abwanderungsquote (churn rate) gibt an, welchen Anteil unserer Kunden wir pro Zeiteinheit verlieren:\n\"Wir verlieren 20% unserer Kunden pro Monat\" bedeutet die Abwanderungsquote ist 20%/Monat.\nRetention (Kundenbindung) ist das Pendant dazu, d.h. der Anteil unserer Kunden, den wir behalten.\nIm Beispiel haben wir eine Kundenbindungsquote von 80% / Monat`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":111,"value":"md`Es empfiehlt sich, bei der Analyse den Kundenstamm in *Kohorten* einzuteilen,\neine Kohorte besteht aus Kunden, die wir in einem bestimmten Zeitraum gewonnen haben.\nBeispiel: die Kohorte 2018-05, bestehend aus allen Neukunden vom Mai 2018.\nBei 80% Kundenbindungsquote und Startwert 1000 sieht der Verlauf dieser Kohorte so aus:\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":437,"value":"{\n var cohort = new Cohort('2018-05');\n var periods = \"2018-06 2018-07 2018-08 2018-09 2018-10 2018-11 2018-12 2019-01 2019-02 2019-03 2019-04\".split(\" \");\n cohort.append(\"2018-05\", 1000);\n periods.forEach(p => cohort.retain(0.8, p));\n return vl.markBar()\n .data(cohort.asDataFrame())\n .encode(\n vl.y().field('count').title(\"Kunden\"),\n vl.x().fieldN('period').title(\"Monat\"),\n vl.tooltip(['period', 'count'])\n ).title(\"Kohorte 2018-05\")\n .render()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":450,"value":"md`Nach einem Jahr (April 2019) sind von den ursprünglichen 1000 Kunden nur noch ca. 86 bei uns.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":859,"value":"md`Dieses einfache Modell geht von einer konstanten Abwanderungsrate für alle Kohorten und alle Zeiträume aus.\nDas lässt sich gut rechnen (simulieren), und man kann die Prinzipien der Kundenbindungsanalyse gut daran erklären. In der Praxis kann es natürlich Abweichungen geben:\n\n- Erhöhte Abwanderungsquote im ersten Monat. Das ist ein bekanntes Problem im E-commerce: Kunden, die einmal und nie wieder bestellen.\n- Stammkunden: Manche Kunden behält man für's Leben, im Laufe der Zeit geht die Abwanderungsquote der Stammkunden gegen Null.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":867,"value":"md`Hier soll es um die Frage gehen:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":870,"value":"html`

Lohnt sich eine geplante Investition zur Erhöhung Kundenbindungsquote?

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":875,"value":"md`Dazu simulieren wir, wie sich die Zahl der aktiven Kunden (und damit der Umsatz) ändert,\nwenn man die Kundenbindungsquote steigert.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":462,"value":"md`## Simulation: Höhere Kundenbindung`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":467,"value":"md`Die folgende Grafik zeigt die Entwicklung der Kundenzahl, aufgeteilt nach Kohorten.\nWir starten unser Angebot im Januar 2017 und gewinnen jeden Monat 1000 Neukunden. \nIn jedem weiteren Monat haben wir zusätzlich die Bestandskunden aus den älteren Kohorten.\nJede einzelne Kohorte schmilzt mit ${((1-retentionRate)*100).toFixed(0)}% pro Monat ab\n(${d3.format('.0%')(retentionRate)} Kundenbindungsquote).\nIm letzten Monat haben wir ${simulated.lastTotal(1)} Kunden.\nBei einem Warenkorbwert von ${basketValue}€ entspricht das einem Monatsumsatz von ${simulated.lastTotal(basketValue)} €.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":878,"value":"html`Fußnote: Mit Kundenzahl sind immer aktive Kunden gemeint, also solche, die im betrachteten Monat eine Bestellung gemacht oder ein Abonnement behalten haben.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":30,"value":"{\n var cohorts = vl.markArea()\n .data(simulated.asDataFrame())\n .encode(\n vl.y().field('count').title('Kunden'),\n vl.x().fieldN('period').title('Monat'),\n vl.color().sort(\"ascending\").field('cohort').title('Kohorte').legend({columns:2}),\n vl.order('cohort'),\n vl.tooltip(['cohort', 'period', 'count'])\n );\n \n var baselineTotals = vl.markLine({color: 'black', size: 3, opacity: 0.5, \"strokeDash\": [6, 4]})\n .data(baseline.totals())\n .encode(\n vl.y().field('count').title('Kunden'),\n vl.x().fieldN('period').title('Monat')\n );\n \n var annotation = vl.markText({size:12, fill: 'black'})\n .data([{count: baseline.lastTotal(1)-200, period: '2019-10', text: 'Baseline: 80%'}])\n .encode(\n vl.y().field('count'),\n vl.x().fieldN('period'),\n vl.text('text')\n );\n \n return vl.layer(cohorts, baselineTotals, annotation)\n .width(700)\n .title(d3.format(\".0%\")(retentionRate) + \" Kundenbindungsrate\")\n .render()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":312,"value":"viewof retentionRate = slider({\n min: 0, \n max: 1, \n step: 0.01, \n value: 0.8, \n format: \".0%\",\n description: \"Kundenbindung (retention rate, in %/Monat)\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":332,"value":"viewof basketValue = slider({\n min: 0, \n max: 100, \n step: 1,\n value: 50, \n description: \"Warenkorb in Euro\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":621,"value":"md`**Was schätzen Sie: Wieviel Mehrumsatz macht man, wenn man die Kundenbindungsquote von 80% auf 84% pro Monat erhöht?**\n\nMit den Schiebereglern oben können Sie ausprobieren, welchen Effekt die Erhöhung der Kundenbindungsquote in diesem Beispiel haben würde. \n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":584,"value":"{\n var simTotal = simulated.lastTotal(basketValue);\n var baseTotal = baseline.lastTotal(basketValue);\n return html`\n\n\n \n \n \n \n \n \n\n\n \n \n \n \n \n \n\n\n \n \n \n \n \n \n\n\n \n \n \n\n\n

Szenario	Retention	Kunden	Warenkorbwert	Umsatz
Simulation	${(retentionRate*100).toFixed(0)}%	${simulated.lastTotal(1)}	${basketValue}€	${simTotal} €
Baseline	80%	${baseline.lastTotal(1)}	${basketValue}€	${baseTotal} €
Effekt	\n ${simTotal - baseTotal} €\n	(${d3.format(\".0%\")((simTotal - baseTotal) / baseTotal)})

\n`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":699,"value":"md`## Der Kundenbindungs-Effekt`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":702,"value":"md`Die Simulation zeigt, dass die Kundenzahl sich einem Höchstwert annähert. Wie groß dieser Wert ist,\nkann man sich leicht überlegen:\n\n- Jeden Monat wandern x% des Kundenstammes ab\n- der Kundenstamm wächst solange, bis die Abwanderung gerade durch die Zahl der Neukunden ausgeglichen wird. `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":707,"value":"md`Wenn also beispielsweise jeden Monat 20% der Kunden abwandern, dann sind im stabilen Zustand die Neukunden gerade ausreichend, um diese 20% zu ersetzen. Unsere 1000 Neukunden im Beispiel oben machen also gerade 20% des Kundenstamms aus. Dreisatz: dann haben wir insgesamt 5000 Kunden.\nDie Formel dazu lautet:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":710,"value":"tex.block`Kundenzahl = \\frac{Neukundenzahl}{Abwanderungsquote}`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":807,"value":"md`Die folgende Grafik zeigt, wie sich die Kundenzahl ändert, wenn wir die Kundenbindungsquote erhöhen können.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":723,"value":"viewof oldRetentionRate = slider({\n min: 0, \n max: 1, \n step: 0.01, \n value: 0.8, \n format: \".0%\",\n description: \"Kundenbindung bisher\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":819,"value":"viewof newRetentionRate = slider({\n min: 0, \n max: 1, \n step: 0.01, \n value: 0.8, \n format: \".0%\",\n description: \"Kundenbindung neu\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":822,"value":"md`Änderung der Kundenbindungsquote von bisher ${d3.format('.0%')(oldRetentionRate)} auf ${d3.format('.0%')(newRetentionRate)} ändert den Kundenbestand langfristig um ${d3.format('+.1%')(effect(oldRetentionRate, newRetentionRate))}`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":726,"value":"{\n \n \n var effects = d3.range(0,0.999, 0.01).map(x=>x.toFixed(2)).map(function(newRate) {\n return { newRate: newRate, effect: effect(oldRetentionRate, newRate).toFixed(3)}\n });\n \n var line = vl.markLine({color: 'black', size: 3,clip:true})\n .data(effects)\n .encode(\n vl.x().field('newRate').axis({format: '.0%'}).title('Kundenbindungsquote neu'),\n vl.y().field('effect').scale({domain:[-1,1.5]}).axis({format: '+.0%'}).title('Effekt'),\n vl.tooltip('effect').format('+.0%')\n );\n var marker = vl.markRule({color: 'black', size: 3, opacity: 0.5, \"strokeDash\": [6, 4]})\n .data([{rate: oldRetentionRate}])\n .encode(vl.x().field('rate'));\n \n var dot = vl.markPoint({size:150, filled: true, clip: true})\n .data([{rate: newRetentionRate, effect: effect(oldRetentionRate, newRetentionRate)}])\n //.data([{rate: 0.7, effect: 0.8}])\n .encode(\n vl.x().field('rate'),\n vl.y().field('effect')\n )\n return vl.layer(marker, line, dot).render();\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":688,"value":"html`

ENDE

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"md`# Setup`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":663,"value":"md`Hier folgt der [Observable](https://observablehq.com)-Code für die Kohorten-Simulationen.\nWenn Sie den code sehen wollen, klicken Sie einfach links vom jeweiligen Text.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":356,"value":"simulated = new Simulation().run(retentionRate);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":420,"value":"baseline = new Simulation().run(0.8);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":363,"value":"md`Imports`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"import {slider} from '@jashkenas/inputs'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"import {form} from '@mbostock/form-input'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":22,"value":"import {vl} from '@vega/vega-lite-api'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":185,"value":"_ = require(\"lodash\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"md`Simulate a cohort`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":118,"value":"Cohort = function(name) {\n this.name = name;\n this.counts = new Map();\n \n this.append = function(period, count) {\n this.counts.set(period, count);\n }\n \n this.periods = function() {\n return Array.from(this.counts.keys());\n }\n \n this.lastPeriod = function() {\n return _.last(this.periods())\n }\n \n this.lastCount = function() {\n return this.counts.get(this.lastPeriod())\n }\n \n this.retain = function(retentionRate, nextPeriod) {\n var last = this.counts.get(this.lastPeriod());\n var current = last * retentionRate\n this.append(nextPeriod, current);\n return current;\n }\n \n this.asDataFrame = function() {\n var answer = [];\n for (let [period, count] of this.counts.entries()) {\n answer.push({cohort: this.name, period: period, count: count});\n }\n return answer;\n }\n \n this.toString = function() {return \"\"}\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":424,"value":"md`Simulate customer base`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":205,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":816,"value":"effect = function(oldRetention, newRetention) {\n var oldCustomers = 1 / (1-oldRetention);\n var newCustomers = 1 / (1-newRetention);\n return (newCustomers - oldCustomers) / oldCustomers;\n }","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1"}} 31:"$30:body"