presentation2

Mobile/desktop user analysis with the effects on email

interaction patternsBo Ma

boma@linkedin.com

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