presentation2
TRANSCRIPT
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Data Event Type Data Source Notes
Email Send Event /data/tracking/EmailSendEvent
Get the Email send details like click type, section name, type, order, position, size.
Email Click Event /data/tracking/EmailClickEvent Get Email click number
Email View Event /data/tracking/EmailViewEvent Get Email view number
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Preliminary Observations
• From above data, we can know which user click on which email and which specific clicks in the email.
• So I count the distribution on different clicks and click position for both mobile and desktop
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Click Distribution
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Group the click by Section
• We actually interested in the module section order and click in the email.
• So I group the click by SectionNo.• There are at most 7 sections in
‘nu_digest’ emailKeySectionSeq SectionName
0 positions1 milestones2 shares3 profile4 endorsements
5 connections6 pymk
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Section Click Distribution
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Section Click Distribution
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AnalysisInteresting things:• some section in position 5 , but it has more click
distribution than section in position 4.Bias:• what is the order for 7 section? • Is there difference between the section type.• What is the section size?• It includes all the order and all the size.• Does Mobile has more Uctr than Desktop?
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Uctr in this question
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• As the position increases the Uctr decreases.
• 3Profile’s Uctr is higher than 2shares with section size 3 on pos 0.
• 6Pymk and 5connection’s Uctr is higher than the 4endorsements.
• This shows us the original order is not optimized
• The Desktop’s Uctr is higher than the mobile’s Uctr.
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• For endorsement:• As the section pos
increases the Uctr drops.
• As the section size increases the Uctr drops.
• But it is not the same trend for some section
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• Big difference for section shares.
• As the section size increases, the Uctr does not drops.
• For pos >=1 , the Uctr drops a little. Position is not as
• This shows that shares’s performance is different from others.
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• With same section size and same section pos.
• Pymk and connections Uctr is higher than the endorsement
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Bias• But above chart still have bias.• For example:• For section endorsements,with section size 2,
and section pos 2.
• We can have format:• 1, shares;endorsements;pymk• 2, shares;endorsements;connections
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Uctr Difference between setion name on Same Format
Format section name Uctr
shares;endorsements shares 0.070833333
shares;endorsements endorsements 0.027083333
shares;endorsements;connections shares 0.067493113
shares;endorsement;connections endorsements 0.022956841
shares;endorsements;connections connections 0.02892562
shares;endorsements;pymk shares 0.073609732
shares;endorsements;pymk endorsements 0.025819265
shares;endorsements;pymk pymk 0.02599861
Pymk and connection’ Uctr are higher than edorsement.Pymk increase the Uctr for the first section shares.
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Pymk increases Uctr on first section
Format section name Uctr Format section name Uctr increase rate
endorsements;connections endorsements 0.069423175
endorsements;connections;pymk endorsements 0.071578619 3.01%
connections 0.032272702 connections 0.030748472 -4.96%
pymk 0.021006685
profile;endorsements profile 0.140718563
profile;endorsements;pymk profile 0.174781765 19.49%
endorsements 0.041916168 endorsements 0.027158099 -54.34%
pymk 0.025800194
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• Thank you!• You can find more detailed analysis on
Email User Analysis Wiki