The document describes the predictive analytics life cycle for tracking job seeking behavior and generating a "J-Score". The process involves: 1. Inputting individuals to track and their data. 2. Building/updating a predictive model for each individual by enriching their data with social media information. 3. Deploying the predictive model to output a J-Score and signals about an individual's likelihood to pursue new opportunities based on their online activities and changes to social media behavior.

1. Processforscoring
jobseekingbehavior
...
ThePredictiveAnalyticsLifeCycleincontextofJoberatetechnology
Userinputof
personthey
wanttotrack
Build(update)
person’sunique
predictivemodel
Enrichwith
SocialData
Deploy
predictive
model
OutputJ-Score
movetostep3
(happensdaily)
Prepareand
formatperson’s
datarecord
Validateandtest
thepredictive
model
Selectand/or
Transform
Whoislikelytoleave?
1
1
2
3
4
5
7
8
6
2
Tellthesystemwhichpeopleyou
areinterestedintracking
(manualinput,CSVfile,orAPI)
API
2
Prepareeachperson’suniqueID
forSocialDataenrichment
UID
HRIS/CRM
ATS/Jobboard
SocialProfile
Ormanual
inputor
import
Name
Email
Location
Title
...
3+4
3+4
Analyzeandenricheachperson’sunique
recordusingpubliclyavailableSocialData
Exampleoftriggerscapturedfromtrainingdatathat
changethescoreand/orweightingofthedata:
Personwhoconstantly
followsorlikesnewcompa-
nyaccountsstartstofollow
anewcompany
=1pointincrease
ByusingpeoplesearchenginesandSocialDataaggregators
-Ensurethatthepersonwhoisdesignatedfortrackingiscorrect
-Lookforchangesintheperson’spublishedcontentoractivities
Followinglinksinpeople’s
socialprofiles,addingrele-
vantnewcontent
Followinglinksintheper-
son’ssharedcontenttoiden-
tifyothersocialcontentor
socialprofiles,addingrele-
vantnewcontent
OngoingSocialDatavalida-
tiontoensuretheperson
beingtrackedisthesame
Analyzemeta-dataforthe
siteswherethepersonis
sharingcontent,todiscover
potentialAPIrelatedthatcan
beleveragedviapaidsources
Personwithlittlefollowingor
likingofanyjobrelatedcontent
startstofollow/subscribetoa
newsourceofjobrelatedcontent
=5pointincrease
Personwhoactivelyfollowsor
likesjobrelatedcontentstartsto
follow/subscribetoanewsource
ofjobrelatedcontent
=2pointincrease
Personwhodoesnot
activelyupdateprofession-
alsection(s)ofsocialmedia
profiles,makesanupdate
=9pointincrease
Personwhoactivelyupdates
professionalsection(s)of
theirsocialmediaprofile,
makesanupdate
=3pointincrease
Personwhohasonlya
fewconnectionswith
recruiters,connectswitha
singlenewrecruiter
=4pointincrease
Otherfactorsliketiming(frequency,timeofday)ofthe
SocialDatachanges,andalsosimultaneousSocialData
changesinmultiplesiteshaveacumulativeimpact
Deploymodel:
Personwithverylittle
followingorlikingofany
companyaccountsstarts
tofollowanewcompany
=8pointincrease
©Allrightreserved.Joberate.com
1
2
3 5
4
Contentexplorationviaexternal
paidSocialDataproviders
5-DayReplay
Formatnormalization
URLExpansion
KloutScores
LanguageDetectionandFiltering
PhraseandKeywordFilters
GGeoFilters
UserFilters
Formatnormalization
URLExpansion
Plug-and-PlayStreams
DuplicateExclusion
OptimizedPolling
ChoiceofProtocols
Formatnormalization
URLExpansion
LanguageDetection
DataStream DataStream DataStream
+
+
+
Extractrelevantdata,and
build(update)theperson’sunique
predictivemodel
Validateandtestthecurrentmodel
(leveragetrainingandrealtimedata)
7
Deploypredictivemodel
(basedonwhatactuallyhappened)
3+45+6
5+6
8
J-Score+other
information
isupdateddaily,and
outputviaAPIorto
theJoberatedashboard
API