Presentation2
Transcript of Presentation2
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
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
Click Distribution
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
Section Click Distribution
Section Click Distribution
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?
Uctr in this question
• 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.
• 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
• 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.
• With same section size and same section pos.
• Pymk and connections Uctr is higher than the endorsement
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
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.
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
• Thank you!• You can find more detailed analysis on
Email User Analysis Wiki