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Samenvatting Waarde creëren met big data analytics van Peter Verhoef, Edwin Kooge en Natasha Walk

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Gestructureerde en volledige samenvatting van Waarde creëren met Big Data Analytics geschreven door Peter Verhoef, Edwin Kooge, Natasha Walk. De zelfde structuur als het boek, daardoor gemakkelijk aan te vullen wanneer nodig. Succes :)

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1

,Samenvatting Waarde creëren met big data analytics

Inhoudsopgave
...................................................................................................................................................................................... 1

Hoofdstuk 1 Uitdagingen van big data............................................................................................................................ 4

Hoofdstuk 2 Waarde creëren met big data analytics....................................................................................................... 4
1. Mensen...........................................................................................................................................................................6
2. Systemen........................................................................................................................................................................6
3. Processen........................................................................................................................................................................6
4. Organisaties....................................................................................................................................................................6
Strategieën voor het analyseren van big data...................................................................................................................6
Big data veranderen analytics............................................................................................................................................6
Visualisatie van gegevens...................................................................................................................................................7
Waardecreatieconcepten...................................................................................................................................................7
De balans tussen V2F en V2C.............................................................................................................................................7
Metrics voor V2F en V2C....................................................................................................................................................8

Hoofdstuk 3 Waarde-voor-klantmetrics.......................................................................................................................... 8
e
1 dimensie = tijd.............................................................................................................................................................11
Online bronnen; reviews;.................................................................................................................................................12

Hoofdstuk 4 Waarde-voor-bedrijfmetrics...................................................................................................................... 12
1. Relatievoortzettings- of relatieduurmetrics.................................................................................................................14
2. Relatieuitbreidingsmetrics...........................................................................................................................................14
3. Relatiekosten- en relatierisicometrics..........................................................................................................................10
CLV-componenten............................................................................................................................................................10
Berekening klantlevensduur.............................................................................................................................................11
CLV-formule  pagina 81 pagina 81....................................................................................................................................................11
Ad 1 Klantbinding.............................................................................................................................................................11
Ad 2 Digitale customer journey Customer journey metrics:............................................................................................12
Marketing ROI...................................................................................................................................................................12

Hoofdstuk 5 Databronnen............................................................................................................................................ 13
Merkgegevens..................................................................................................................................................................14
Klantgegevens..................................................................................................................................................................14
Relationele databasestructuren.......................................................................................................................................15

Hoofdstuk 6 Data-integratie......................................................................................................................................... 15
ETL-proces:.......................................................................................................................................................................16
Extraheren........................................................................................................................................................................16
Transformatie...................................................................................................................................................................16
Laden................................................................................................................................................................................16
Declared data (door klanten verstrekte gegevens)..........................................................................................................16
Appended data (toegevoegde gegevens)........................................................................................................................16
Overlaid data (overkoepelende gegevens)......................................................................................................................16
Implied data of Impliciete gegevens................................................................................................................................17
Technische uitdagingen....................................................................................................................................................17
Analytische uitdagingen...................................................................................................................................................17
2

, Zakelijke uitdagingen........................................................................................................................................................17

Hoofdstuk 7 Klantprivacy en gegevensbeveiliging......................................................................................................... 17
Cloud.................................................................................................................................................................................20

Hoofdstuk 8 Hoe big data de analytics veranderen........................................................................................................ 20
Statistische versus dynamische analyses.........................................................................................................................20
Probleemoplossing...........................................................................................................................................................20
Gegevensmodellering.......................................................................................................................................................20
Datamining of gegevensontginning..................................................................................................................................20
Bijvangst (collateral catch)...............................................................................................................................................21
Volume en betrouwbaarheid...........................................................................................................................................23

Hoofdstuk 9 Klassieke data analytics............................................................................................................................. 23
Klantkruistabellen.............................................................................................................................................................23
Decielanalyse....................................................................................................................................................................23
Externe profilering............................................................................................................................................................23
Migratiematrix..................................................................................................................................................................25
Like-4-like-analyse............................................................................................................................................................25
Diepgaande migratieanalyses..........................................................................................................................................25
Geavanceerde migratieanalyse........................................................................................................................................25
Uitvoeren van clusteranalyse...........................................................................................................................................25
Praktische overwegingen.................................................................................................................................................27
Introductie........................................................................................................................................................................27
Stated importance measurement....................................................................................................................................27
Regression based approach..............................................................................................................................................27
Conjointanalyse................................................................................................................................................................27
Geavanceerde conjointanalyses en marktvoorspellingen...............................................................................................27
RFM...................................................................................................................................................................................27
Decision trees...................................................................................................................................................................27
Logit..................................................................................................................................................................................27
Computergestuurde modellen.........................................................................................................................................27
Voorspellende prestatiemaatstaven Hit rate...................................................................................................................27
Gini-coëfficiënt.................................................................................................................................................................28

Hoofdstuk 10 Nieuwe big data analytics........................................................................................................................ 28
Zeven vormen van big data analytics – pagina 232.........................................................................................................28
Analyse van clickstream data...........................................................................................................................................28
Grootschalige experimenten: A/B testen.........................................................................................................................28
Factorial designs...............................................................................................................................................................28
Kwalitatieve benadering...................................................................................................................................................29
Kwantitatieve benadering................................................................................................................................................29
Cookies.............................................................................................................................................................................29
Aanbevelingssystemen.....................................................................................................................................................29
Hybride vormen van content- en collaborative-filteringsystemen..................................................................................30
Personalisatie...................................................................................................................................................................30
Adaptieve personaliesatiesystemen (APS).......................................................................................................................30
Hierarchial Bayesian model estimation............................................................................................................................30
Eén aggregatieniveau.......................................................................................................................................................30
Opinieanalyse...................................................................................................................................................................30
Taggen..............................................................................................................................................................................30
Positieve oriëntatie Negatieve oriëntatie........................................................................................................................31
C2C-interacties.................................................................................................................................................................31

Hoofdstuk 11 Impact creëren met verhalen en visualisaties.......................................................................................... 31
Sweet spot van data, verhaal en visualiatie.....................................................................................................................31
11.3.1 Piramide-principe..................................................................................................................................................32
3

, Chronologische volgorde Miller’s wet..............................................................................................................................32
Relatie tussen gegevenspunten.......................................................................................................................................32
Vergelijking van gegevenspunten....................................................................................................................................32
Samenstelling van gegevens.............................................................................................................................................32
Verdeling van gegevens....................................................................................................................................................30
Analytische basispatronen...............................................................................................................................................30




Hoofdstuk 1 Uitdagingen van big data
1.2 Explosieve gegevensgroei
Veel bedrijven hebben nu data dagelijks of zelfs in realtime gegevens tot hun beschikking.
Het idee heerst dat creëren van waarde uit deze gegevens een motor is van groei en dus de
komende jaren waardevol voor economieën.

Online zijn consumer-to-consumer markten (C2C) steeds belangrijker geworden in
vergelijking met B2C en B2B markten.
Bedrijven investeren steeds meer in sociale media. Sociale media zorgen voor enorme
toename in klantinzicht. Blogs, productbeoordelingen, discussiegroepen, productscores
enzovoort zijn nieuwe en belangrijke bronnen van informatie, waarin consumenten reageren
op elkaar en op de producten en diensten die ze gebruiken. Het toenemend gebruik van
online media, waaronder mobiele telefoons, stelt bedrijven ook in staat om het
aankoopproces van klanten te volgen.

1.3 Kanttekeningen bij big data
Big data zijn inmiddels de norm geworden en bedrijven zien in dat ze een betere
concurrentiepositie bemachtigen door deze gegevens te analyseren.
Bedrijven worstelen met waarde creëren uit deze gegevens  pagina 81 raken gemakkelijk
teleurgesteld wanneer ze na alle moeite geen succes behalen. Eerder voorgekomen ook bij
datarevoluties zoals CRM. Verder hebben ontwikkelingen in big data geleid tot levendige
discussies, die de publieke onrust over privacy hebben aangewakkerd.

1.5 Onze aanpak
Customer life-time value (CLV)= klantlevensduurwaarde.




Hoofdstuk 2 Waarde creëren met big data analytics

2.1 Introductie
Tijdens zo’n periode als de CRM-revolutie, doorlopen bedrijven doorgaans drie fasen:
1. Dataenthousiasme – investeringsfase
Ondernemingen geloven in de voordelen van nieuwe technologie.
2. Datateleurstelling – frustratie- of deinvesteringsfase
Na paar jaar hebben explosieve data-investeringen en –initiatieven voornamelijk
teleurstellende resultaten en zijn veel projecten mislukt.  pagina 81 desinvesteren en
gegevensstrategieën heroverwegen.
3. Datarealisme – herinvesteringsfase
Heroverweging strategieën leidt een volgende fase in met relistischere ambitites en een
sterkere focus op de waardecreërende kracht van op data gebaseerde initiatieven en het
rendement van investeringen.

2.2 Big-datawaardecreatiemodel Figuur 2.1 – Pagina 23


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Hallo :)! Graag deel ik mijn samenvattingen om Slim te Leren. Mijn samenvattingen zijn volledig en wanneer mogelijk met oefenexamen. Ik probeer de feedback te verwerken van andere kopers. Op deze manier zorg ik ervoor dat ze goed blijven. Voor een normale prijs :)! Succes! Voor vragen kan je altijd een berichtje sturen! Groeten, Bart

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