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ResearchReport
TheImpactofTechnologyonContactCenterPerformance
SPONSOREDBY:
1
ResearchReport
THEIMPACTOFTECHNOLOGY
ON
CONTACTCENTERPERFORMANCE
by
BruceL.Belfiore
SeniorResearchExecutive
CenterforCustomerͲDrivenQualityTM
and
JohnChatterley
DirectorofResearch
BenchmarkPortalTM
and
Dr.NataliePetouhoff
ResearchExecutive
BenchmarkPortalTM
with
DeeBuell
ResearchAssistant
Angel&ChristoTonchev
StatisticalAnalysts
Sponsoredby:
2012
2
HelenThomas
CopyEditor
Copyright © 2012 The information contained in this document is the
property of BenchmarkPortal.LLC. No part of this publication may be
copied,scannedorreproducedwithouttheexpresswrittenconsentof
BenchmarkPortal,LLC,126E.ConstanceAve.,SantaBarbara,CA93105.
AdditionalcopiesmaybepurchasedbyeͲ[email protected].
3
ACKNOWLEDGEMENTS
Wewouldliketothankthemanymembersofourcontactcentercommunitywhoparticipated
inthisresearch.Participationinvolvedcompletingsurveyswithquestionsoncontactcenter
metricsandsupportingtechnology.Ourteamdideverythingpossibletosimplifytheprocess;
however,wearewellawarethatparticipationrequiredadeterminedeffort,andwewishto
acknowledgethateffortwithgratitude.
WearealsogratefultoCiscoSystemsforsponsoringthisgroundbreakingstudy.Inparticular,
wewishtothankLeonGrekinforhissupportandenthusiasmforthisproject.
ColleagueswhospentsignificanttimeassistingthisstudyincludedDeeBuell,AngelandChristo
Tonchev,andHelenThomas.Finally,wewouldliketothankourothercolleaguesat
BenchmarkPortal,especiallyJoePerez,DaynePetersenandDruPhelpsfortheirsustained
supportofthesurveyprocessduringthedataentryprocessandexplainingdefinitionsas
needed.Ourappreciationgoes,aswell,toDavidRaiaforhispeerreviewofthedraft.Thank
youall.
BruceBelfiore
JohnChatterley
Dr.NataliePetouhoff
4
TableofContents
Page
4
Acknowledgements
ExecutiveSummary
7
7
7
Introduction
KeyFindings
BackgroundandPurposeofThisStudy
10
11
TechnologicalMaturityFramework
ResearchMethodology
13
13
13
14
15
16
17
17
17
SurveyAssemblyandFielding
DataQuality
ParticipationbySector
StatisticalAnalyticsApproach
KPISelection
MacroAnalysis
DrillͲdownStatisticalAnalysis
CombinedEffectAnalysis
ResearchFindings:TechnologiesThatImproveKeyPerformanceMetrics
18
MacroFindings
DrillͲdownAnalyses
CombinedEffectResults
18
20
30
ConclusionsFromtheResearch
31
AppendixA–Biographies
32
AppendixB–Spearman’sCorrelationTables
38
AppendixC–TechnologyDrillͲdownChartsandTables
42
AppendixD–Surveys
47
AppendixE–AboutBenchmarkPortal
62
AppendixF–AboutCisco
63
5
ListofFigures
Page
Figure1.TheContactCenterMaturityModel
11
Figure2.PercentageofParticipantsbyIndustry
14
Figure3.KeyPerformanceMetrics
16
Figure4.KeyMetricsThatImproveasOverallTechnologicalMaturityIncreases
18
Figure5.TechnologiesThatImproveFirstContactResolution
20
Figure6.HypotheticalFinancialImpactofImprovedFirstCallResolution
21
Figure7.HypotheticalImprovementinCustomerSatisfaction
22
Figure8.TechnologyImpactonCostperCall(%)
22
Figure9.TechnologyImpactonCustomerSatisfactionTopBox(%)
23
Figure10.TechnologyImpactonCustomerSatisfactionBottomBox(%)
24
Figure11.TechnologyImpactonAgentSatisfactionTopBox(%)
25
Figure12.TechnologyImpactonInboundCallsperAgentperHour(%)
26
Figure13.TechnologyImpactonQueueTime
27
Figure14.TechnologyImpactonfirstContactResolutionEͲmail(%)
27
Figure15.TechnologyImpactonCostperContactEͲmail(%)
28
Figure16.TechnologyImpactonCostperContact–Chat(%)
28
Figure17.TechnologyImpactonFirstContactResolutionChat%)
29
Figure18.CombinedEffectsAnalyses
30
6
EXECUTIVESUMMARY
INTRODUCTION
Contactcentersspendmillionsofdollarseachyearontechnologyinhopesofimprovingtheir
company’scompetitiveposition,operationalperformanceandcoststructure.Managersoften
assumethatmoresophisticatedcontactcentertechnologywillprovidebetterperformance
andwillimproveKeyPerformanceIndicators,suchascustomersatisfaction,firstcontact
resolutionandcostpercontact.
Whilethetruthofthisassumptionissometimestrackedandmeasuredbyindividualcenters
undergoingatechnologyupgradeprocess,therehasneverbeenastatisticallyvalidresearch
study,involvingmanydiversecontactcenters,thatindicateswhetherarelationshiptrulydoes
existbetweenmoreadvancedtechnologyandbetterperformance.Thisresearchpaperisthe
firstofitskindtocollectandanalyzedatafromalargenumberofcontactcenterstodetermine
theexistenceandintensityofthisrelationship.Itincludesvalidateddatasetsfrom143contact
centers,representingabroadcrossͲsectionofindustries.
KEYFINDINGS
Thisresearchprovidespositive,statisticallyrelevantevidenceshowingthatmoreadvanced
contactcentertechnologyprovidesbettercontactcenterperformance.Moreadvanced
technologiesresultinmoreeffectiveandefficientcustomerinteractions.Forinstance,they:
x ImproveCustomerSatisfaction.
x LowerCostperCall
x IncreaseFirstContactResolution
x IncreaseCallsHandledperAgentperHour
x ReduceQueueTime
x ImproveAgentSatisfaction
Inparticularthestudyshowedthatcontactcenterswithmoreadvancedtechnologies:
x Improvetheirfirstcallresolutionratebetween4%to13%usingtechnologiessuchas:
o Contactdataanalytics
o Advancedroutingcapabilities
o Advancedreportingandanalyticaltools
x ReportCostsPerCallthatarelowerbyasmuchas35%withtechnologiessuchas:
7
o
o
o
o
x
PresenceͲbasedexpertescalation
MultiͲcriteriaskillsͲbasedrouting
Courtesycallbacks
IntegrationofAppsandCTI(computerͲtelephonyintegration)
ImproveTopBoxCustomerSatisfaction(i.e.,customerswhoratetheiroverall
satisfactionwithaninteractionas5outof5)bybetween5%and7%usingtechnologies
like:
o CradleͲtoͲGraveReporting
o ContactDataAnalytics
o WorkforceManagement
x
x
x
x
ImproveBottomBoxCustomerSatisfaction(i.e.,customerswhoratetheiroverall
satisfactionwithaninteractionas1outof5)between39%and66%using:
o WorkforceManagement
o SpeechRecognition
o CallRecording&Retrieval
o TouchͲtoneIVR(DTMF)
ImproveCallsperAgentperHourbetween6%and18%usingtechnologieslike:
o MultiͲCriteriaRouting
o CTI&AppsIntegration
o PresenceͲBasedExpertEscalation
o UnifiedCrossͲChannelRouting
o NaturalLanguageIVR
ImproveTopBoxAgentSatisfaction(i.e.agentswhoratetheiroverallsatisfactionwith
theirworkas1outof5)between4%to11%withtechnologiesincluding:
o AdvancedReporting&Analytics
o AgentDesktopwithCTI
o CTI&AppsIntegration
o RealͲtimeAgentFeedbackTools
ReduceAverageQueueTimebetween12%to43%withtechnologiesincluding:
o PresenceͲBasedExpertEscalation
o CourtesyCallͲBackwhileinQueue
o BlendedRouting
o MultiͲCriteriaRouting
x
ImproveMultiͲChannel(eͲmailandchat)performancebyimplementingtechnologies
suchas:
o UniversalMultiͲChannelQueue
o UnifiedCrossͲChannelRouting
8
o CTI&AppsIntegration
o andothers
Theresultsindicatethattoday'scontactcentertechnologiescanbepotentenablersofsuperior
performance,bothintermsofsatisfyingcustomersandintermsofimprovingfinancial
performance.
Also,theresearchfoundthatqualityandcostsarenotnecessarilyatodds.Withincreased
technology,contactcenterscanenjoybothlowercostpercallandhighercustomer
satisfaction.
9
BACKGROUNDANDPURPOSEOFTHISSTUDY
BenchmarkPortalhascollectedcallcentermetricsandconductedresearchoncontactcenter
technologysinceitsbeginningsin1995,atPurdueUniversity.Ourresearchshowsthata
commonattributeofgreatcontactcentersistheirabilitytoassembleandoptimizethree
elements:people,processesandtechnology. i Thepresentstudyfocusesonthestatisticalimpactoftechnologyoncontactcenter
performance.Itisoneofthe"bigpicture"issuesforthecontactcentersectorthathasnever
beensubjectedtorigorousscientificinquiry.Naturally,thisissuehasimportantimplications
formanagementdecisionsregardingtechnologyacquisition,andthusmayhelpdetermine
whethermanagerscanjustifyrequeststotheirseniorexecutivesfortechnologyinvestmentsby
usingscientificallyͲsupportedevidenceaboutcostsavingsandimprovedqualityofservice.(See
"Conundrum"boxbelow).
The"CostCenter"Conundrum
Thecommonperceptionofmanytopexecutivesisthatthecontactcenterisanunavoidable
costcenter.Theyinsistthatmanagerssqueezeevermoreoutoftheirpeople,orfindwaysto
cutwasteoutofprocesses,ratherthanconsideringinvestmentintechnology.However,our
researchoverthelastdecadehasindicatedthatinvestmentinnewtechnologygenerally
improvescontactcenteroperationalprocessesanddeliversbetterfinancialresults.We
frequentlyfindthattechnologyinvestmentsincustomercontactcenterspayforthemselves
withinayearortwo.Infact,technologyacquisitionsforthecustomercontactareaoftenyield
higherROI’sthaninvestmentsmadeinacompany'scoreproductsandservices,indicatingthat
wellͲchosenpurchasesincontactcentertechnologyareanimperativeforoptimizingenterprise
value.However,amajor,statisticallyͲrelevantstudyonthistopichasbeenmissinguntilnow. 10
TechnologicalMaturityFramework
Theframeworkusedinthisstudytodetermineacontactcenter’stechnologymaturityiscalled
theContactCenterMaturityModel,(seeFigure1below).Init,fortyͲeightcontactcenter
technologiesaredividedintosixgroups,or"silos,"whichcorrespondtotheflowand
managementofcontactsfrombeginningtoend:
1.
2.
3.
4.
5.
6.
Connect.Thepointofentryforacustomercontact
Recognize.Thesystemdeterminesthegeneralnatureoftheinquiryand,perhaps,the
identityoftherequestor
Route.Aresource(automatedorhuman)isassignedtoaddresstheinquiry
Queue.Theinquiryis"held"untilaresourceisavailabletoaddressit
Resolve.Thecustomerinquiryisaddressedand,hopefully,resolved,ineitheran
automatedfashionorbyaliveagent.
Review.Theeffectivenessandefficiencyofhandlinginquiriesinphases1through5
abovearemeasuredandassessedtodeterminehowwelltheyweredone.
Receive
Answertoa
prospector
customerinquiry
Web Contact
Chat
E-mail Response
System
E-mail Management
System
Recognize
Determinenature
ofinquiry and
requestoridentity
Speech
Recognition
Route
Assignresourceto
addressinquiry
Universal Multi Channel Queue
Competency Based
Routing
Cross -Sell
Message w hile in
Queue
Unified Cross Channel Routing
Routing beyond
Call Center
Blended Routing
ANI / DNIS for
Customer ID
Routing across
ACDs
ACD
DTMF (Touchtone) IVR
Pre -Routing to
ACDs
Skills Based
Routing
PBX
Separate Toll Free Numbers
Holdinquiry to
optimizeresource
utilization
Multi-Criteria
Routing
Personalized VRU
Natural Language
IVR
Queue
Value Based
Routing
Queue
Prioritization
Courtesy Call Back w hile in
Queue
Virtualized
Enterprise Queue
Resolve
Address/resolve
customerinquiry
Presence - Based
Expert Escalation
Automated
Personal Call Backs
Agent Pop-Ups
for Up-sell/Cross sell
CTI & Apps
Integration
Announced Wait
Time in Queue
Recorded
Message w hile on
Hold
Music on Hold
Speech Synthesis
Apps
Assesseffective
handling of
inquiry
Workforce
Management
Actionable Alerts
w ith Solutions
Real -time Agent
Feedback Tools
Contact Data
Analytics
E-mail
Satisfaction
System
Automated
Customer Survey
(IVR)
Advanced
Reporting &
Analytics
Agent Desktop
with CTI
Figure1.TheContactCenterMaturityModel
11
a t ur i y
t
Call Recording &
Retrieval
Agent Trace
CRM Desktop
System
Silent Call
Monitoring
Source: Cisco CCG and BenchmarkPortal Customer Business Transformation (C BT). Patent Pending
M
Cradle to Grave
Reporting
ACD Based
Queue
No Queue,
Hunt Group
Review
Contactcenterswithonlybasiclevelsoftechnologyarerepresentedbythebottomrowofthe
chart.Sophisticationandadvancedcapabilitiesincreasefromthebottomtothetopofeach
columnandfollowthearrowlabeled"Maturity."
Fromthisconceptualstartingpoint,wewereabletoassemblethesurveycomponentsforthe
studyandalsodesignthestatisticalanalysesthatwouldallowustodrawconclusionsusefulfor
thestudy'sparticipantsandthecontactcentersectoringeneral.
12
ResearchMethodology
Wewereconsciousofthegroundbreakingnatureofthisresearchandthechallengesof
obtaininggood,abundantdata.Thusweoptedforstraightforwardmethodologiesinexecuting
thisstudy,withemphasisonqualityofdata.
SurveyAssemblyandFielding
Technologycomponent:Acomprehensivetechnologysurveywasconstructedbasedonthe
ContactCenterMaturityModel(Figure1),whichincludedquestionsonthosefortyͲeight
technologicalfunctionalities.Thissurveywassenttoparticipantsandprovideduswitharich
databaseofinformationonthetechnologypossessedbyeachparticipant.(Surveyshownin
AppendixD.)
Performancedatacomponent:WeutilizedBenchmarkPortal'swellͲknownbenchmarking
survey,theInͲDepthRealityCheck(IDRC),whichgathersdataonthevoicechannel.TheIDRC
wassupplementedbysurveyquestionsonmultiͲchannelmetrics(eͲmailandchat).Intotal,65
datapointswererequestedfromparticipants,coveringeverythingfromvolumeofinteractions,
tohumanresources,tocostͲrelatedmetricsandqualityͲrelatedmetrics.(Surveysshownin
AppendixD.)Wenotethat,whileanincreasingnumberofcontactcentersarebecomingmultiͲ
channel,thelevelofmultiͲchanneladoptionisstillfairlylow,andsomecontactcenterswhich
haverecentlyaddedextrachannelsdonotyetgatherperformancemetricsonthosechannels.
Only13.7%oftherespondentstothisstudycouldprovidemultiͲchanneldata.Weexpectthis
toincreaseinthefuture,asmanagerstrytobetterunderstandandoptimizeallchannelsunder
theircontrol.
ElectronicinvitationstoparticipatewereEͲmailedtomembersoftheBenchmarkPortal
communityandtoalistofcontactcenterssuppliedbythestudy'ssponsor,Cisco.Weblinks
wereincludedintheinvitationswhichbroughttheparticipanttothesurveys.Participantswho
hadrecentlyfilledoutanIDRCwereallowedtousethatdataforpurposesofthisstudy.
DataQuality
Thefieldingeffortsbroughtin322setsofdatafromparticipants.Weappliedcarefulquality
controlstothedata,whichincludedfixedparametersandformulaͲbasedcrosschecksonthe
performancedatareceived.Wheretherewereerrorsorquestions,wewentbacktothe
participantsoastovalidateorcorrectthesubmission.Ifwewereunabletovalidatedata,the
datasetwaseliminated.Attheendoftheprocess,therewere143datasetsthatmetthe
standardsrequiredforinclusioninthestudy.
13
ParticipationbySector
Theparticipantsincludedinthestudywerefromawidevarietyofsectors;theybrokedownby
industryasfollows:
PercentageofParticipantsbyIndustry
Utilities6.0%
ConsumerProducts
5.4%
FinancialServices
10.9%
Telecom6.5%
Technology11.4%
HealthCare13.6%
Professional
Services7.1%
Other14.1%
Insurance19.6%
Manufacturing
5.4%
Figure2.PercentageofParticipantsbyIndustry
14
STATISTICALANALYTICSAPPROACH
Thestatisticalanalysesperformedinthisstudyweredeterminedbytwomainfactors:the
objectiveofthecurrentresearchandthenatureofthecollecteddata.Sinceourmaingoalwas
toexaminetherelationshipbetweentechnologysophisticationandcallcenterperformance,
weperformedtwotypesofanalysisͲacorrelationanalysisandtͲtest.Acorrelationanalysisisa
statisticaltestusedtomeasuretheassociationbetweentwovariablesnotnecessarily
dependentorindependent.ThetͲtesttakesonevariableandcomparesthedifference
betweenthestatisticalaveragesofthetwogroups(i.e.,agroupwhichhasagiventechnology
andagroupwhichdoesnot).
Asindicatedabove,wecollectedtwomajorsetsofdata:dataontechnologyanddataoncall
centerperformance.Theperformancedatasetwaspredominantlycontinuous.Thesetofdata
fortechnologywasentirely"nonͲparametric"(ornonͲcontinuous,i.e.,“yes”or“no”answers
forpresenceofagiventechnology).
Threemaintypesofanalyses(furtherdescribedbelow)wereperformedonthedata:
1. Thefirstone,whichwenamed"MacroAnalysis,"broughttogetherthedataonall
technologiesandmajorKeyPerformanceIndicator(KPI)metrics.
2. ThesecondtypeofanalysiswasmetricͲbyͲmetric"DrillͲDownAnalysis,"whichsingled
outmajorKPImetricsaffectedbythepresenceofgiventechnologies.
3. Thethirdtypeofanalysis,named“CombinedEffectAnalysis,”examinedtheeffectofall
studiedtechnologiesonselectedKPI’ssimultaneously.
Inthenextsection,wewillindicatetheKPIsonwhichwefocusedfortheresearch.
15
KPISelection
TheKPI'sinthefollowingtableweresingledoutforparticularattention,astheyaremetrics
whichmostexecutivesconsiderbellwethersofhealthycontactcenterperformance,intermsof
qualityand/orfinancialefficiency:
Metric
Definition
FirstCallResolution
(FCR)
Thetotalnumbersofcallscompletely
resolvedduringthecourseofthefirst
callinitiatedbythecustomer(and
thereforedonotrequireacallback)
dividedbytotalnumberofcalls
handledbyagents–inpercent.
CallsperAgentper
Hour
Thenumberofcallshandledbyagents
dividedbythenumberofavailable
agenthours
Keyproductivitymetricwhich
improveswhenworkforce
scheduling,desktoptechnology
andtrainingareoptimized.
CostperCall
Budgetfortheperioddividedbythe
numberofcallshandledinthecall
centerforthesameperiod.
Importantfinancialmetric
whichincludesallappropriate
costs
CustomerSatisfaction
(TopandBottomBox
Scores)
TopBoxisthepercentageofperfect
scores(5outof5)receivedonthe
question"Overall,howsatisfiedwere
youwiththeinteraction?".Bottom
Boxisthepercentageof1outof5
scores.
TopBoxisthepercentageofperfect
scores(5outof5)receivedonthe
question"Overall,howsatisfiedare
youwithyourjob?"BottomBoxisthe
percentageof1outof5scores.
TopandBottomBox
Satisfactionarecoremetrics
whichindicatequalityofservice
asperceivedbythecustomer.
AgentSatisfaction
(TopandBottomBox
Scores)
QueueTime
Thisistheaveragewaittimethata
callerexperienceswaitingforanagent
toanswerthetelephoneafterbeing
placedinthequeuebytheACD.
MultiͲchannelmetrics
EͲmailandChatcostsandfirstcontact
resolution.
Figure3.KeyPerformanceMetrics
16
Significance
Consideredthe"magicmetric"
bymany,FCRisbothaquality
metric(correlatingwithcaller
satisfaction)andafinancial
metric(costsaver).
Calledkey"canaryinthecall
center"metricsbytheauthors,
theyreflecttheefficacyof
technologies,peopleand
processesinthecenter,and
helppredictcustomer
satisfactionaswell.
Whiledependentonthelevelof
staffingofthecenter,queue
timeisalsoheavilyinfluenced
bytechnologythatallowsfaster
closingofcalls.
Whilestillnotmeasured
reliablybyamajorityofcenters,
thesemetricsaregaining
importance.
MacroAnalysis
Tomeasuretheoveralltechnologicalmaturityofacallcenteranditseffectonperformance,
weintroducedatechnologyindexbasedonthepresenceofavailabletechnologies.For
example,acallcenterthatreportedtendifferenttypesoftechnologieshadatechnologyindex
scoreequalto10.AstheContactCenterMaturityModel(Figure1)shows,moretechnology
effectivelymeansmoresophisticatedtechnology,since,forexample,centerswith35ofthe
namedtechnologiesarefartherupthematuritychainthancenterswithonly10ofthenamed
technologies.Themaximumpotentialscorebasedonourquestionnairewas48 ii andthe
averageofthesurveysamplewas24.12.Forthisinitialstudynoweightingofthenamed
technologieswasapplied.
Spearman’srankcorrelationanalysiswasemployedtodeterminethisMacroeffectof
technologyonthecontactcenterperformance.MoreinformationisfoundinAppendixB.
DrillͲdownStatisticalAnalysis
InadditiontotheMacroAnalysis,wewantedtomeasuretheeffectofindividualtechnologies
ontheselectedsetofperformancemetrics.Theresearchteamlookedatcertainkey
performancemetricstodeterminewhichspecifictechnologiesshowedanoteworthyimpact.
Fortheseanalyses,unpairedtwosampletͲtestswereperformed.Thesetestsassessedthe
statisticalsignificanceofthedifferencebetweentheperformancemetricsaveragesofcontact
centerswithandwithoutthepresenceofaparticulartechnology.Thestatisticaldetailisin
AppendixC.
CombinedEffectAnalysis
Finally,wewantedtoexaminethecombinedeffectoftechnologyonseveralpairsofcontact
centerKPI’s,specificallyCostperCallandCustomerSatisfaction,FirstCallResolutionand
CustomerSatisfaction,CostperCallandFirstCallResolution,andCustomerSatisfactionand
AgentSatisfaction.
Bytakingtheoutputfromtheprevious“DrillͲdownAnalysis”weperformedPearson’s
correlationtestsontheaboveKPIpairs.Wecorrelatedthepercentagedifferencebetweenthe
averagesofthesampleswithandwithoutthepresenceoftechnologyforthesepairs;i.e.,soͲ
calledtͲtests.MoredetailisfoundunderCombinedEffectresults(below).
17
RESEARCHFINDINGS:TECHNOLOGIESTHATIMPROVEKEY
PERFORMANCEMETRICS
MacroFindings
ThefindingsattheMacrolevel,whichconsideredtheoverallimpactoftechnologyon
performanceusingSpearmanCorrelationanalysis,includedthefollowing:
KeyPerformanceIndicator
SpearmanCorrelation
(rho)
FirstCallResolution
AverageCallsperAgentperHour
TopBoxAgentSatisfaction
Probability
(p)
0.2137
0.1848
0.1859
Confidence
Interval
0.008
0.012
0.002
95%
95%
95%
Figure4.KeyMetricsThatImproveasOverallTechnologicalMaturityIncreases
Acrossoursample,itwasshownthathigherlevelsoftechnologicalmaturitycorrespondto
improvedlevelsofperformanceinthesekeymetrics.
FirstCallResolution(FCR)
ThedataindicatethatFCRimprovesreliablyastechnologybecomesmoresophisticated.This
findingwaspredictablebutimportant,sinceFCRisanindicatorthatcallsarebeingreceived
androutedtherightwaytosourcesthatcansatisfytheinformationrequestsofthecustomer
withtheinformationathandͲwithouthavingtoresearchtheissueandrevert,orelsereferout
thecustomer.Technologyiskeytoaccomplishingthis.
AverageCallsHandledperAgentperHour
ThedataalsoshowthatmoreadvancedlevelsoftechnologyenablehigherAverageCalls
HandledperAgentperHour.Statistically,moreadvancedtechnologieshelpagentsbecome
moreeffectiveandefficientserviceprofessionals.Thesetechnologiesmakesureacustomeris
directlyconnectedtothesourceofinformationbestsuitedtohelpthem,andenableagentsto
accessandinputnecessaryinformationaboutthecustomer,aswellasaccessinformation
abouttheproductsandserviceswhicharethesubjectoftheircalls.Combinedwithgood
training,thishelpsagentsprocesscallsmorequickly.
18
AgentSatisfaction
Agentsatisfactionalsoisgreaterincenterswithmoresophisticatedtechnology.Agents
generallywanttohelpcustomers.Stressandfrustrationresultwhensystemsareinadequateor
slow,screenslockͲup,manyapplicationsmustbeopenatonce,oragentsdon’thavethe
informationtheyneedinfrontofthemtosolveissues,etc.Stresscausessickness,absence,
underͲperformance,lowmoraleandhighattritionlevels.Technologiesthatfosterapositive
workexperienceandenableagentstocometosuccessfulresolutionswiththeircustomers
provideabetteremployeeexperienceaswellasbettercustomerexperiences.Also,ahigher
levelofagentsatisfactionpromoteslowerturnoverandreducescoststothecenter.
Thus,fromourMacroanalysisweseethatcenterswithhigherlevelsoftechnologycanexpect,
onaverage,to:

Resolvemorecallsonthefirstcall

Handlemorecallsperhour

Increasethepercentageofhighlysatisfiedagents.
TheContactCenterMaturityModel,Figure1,isrepeatedhereasacourtesy
tothereadertoassistinfollowingtheDrillͲDownResearchFindingsbelow.
Recognize
Route
Queue
Answertoa
prospector
customerinquiry
Determinenature
ofinquiryand
requestoridentity
Assignresourceto
addressinquiry
Holdinquiryto
optimizeresource
utilization
Web Contact
Chat
E-mail Response
System
E-mail Management
System
Speech
Recognition
Multi-Criteria
Routing
Universal MultiChannel Queue
Competency Based
Routing
Cross-Sell
Message while in
Queue
Personalized VRU
Unified CrossChannel Routing
Natural Language
IVR
Routing beyond
Call Center
Blended Routing
ANI / DNIS for
Customer ID
Routing across
ACDs
ACD
DTMF (Touchtone) IVR
Pre-Routing to
ACDs
Skills Based
Routing
PBX
Separate TollFree Numbers
Resolve
Value Based
Routing
Queue
Prioritization
Courtesy CallBack while in
Queue
Virtualized
Enterprise Queue
Presence- Based
Expert Escalation
Automated
Personal CallBacks
Agent Pop-Ups
for Up-sell/Crosssell
CTI & Apps
Integration
Announced Wait
Time in Queue
Recorded
Message while on
Hold
Music on Hold
Speech Synthesis
Apps
Assesseffective
handlingof
inquiry
Workforce
Management
Actionable Alerts
with Solutions
Real-time Agent
Feedback Tools
Contact Data
Analytics
E-mail
Satisfaction
System
Automated
Customer Survey
(IVR)
Advanced
Reporting &
Analytics
Cradle to Grave
Reporting
Agent Desktop
with CTI
ACD Based
Queue
Call Recording &
Retrieval
Agent Trace
CRM Desktop
System
No Queue,
Hunt Group
Source: Cisco CCG-Customer Business Transformation (CBT). Patent Pending
19
Address/resolve
customerinquiry
Review
Silent Call
Monitoring
Maturity
Receive
Drill-Down Analyses: Impacts of Technology on Key
Performance Metrics
TheresultsoftheDrillͲDownAnalyses,whichaddressedtherelationshipbetweenindividual
metricsandspecifictechnologies,includedthefollowing:
FirstContactResolution(FCR)
ThetͲtestsindicatethatbyusingthetechnologiesinFigure5contactcenterscan,onaverage,
improvetheirfirstcallresolutionratesubstantially,asseenbelow:
Figure5.TechnologiesThatImproveFirstContactResolution
ImportanteffectswerefoundwithtechnologiesresidingintheRoute,Queue,Resolveand
ReviewgroupsidentifiedinTheContactCenterMaturityModel(Figure1.).Centerswiththese
technologieshadanywherefrom4%to13%betterperformanceinFCRascomparedwith
20
centersinthestudywithoutthesetechnologies.Highlyrankedtechnologieswereclusteredin
thefollowingfourgroups:
Route: RoutingviaACD,skillsͲbased,competencyͲbased,multiͲcriteriaandblendedrouting
Queue: Courtesycallbacks,announcedwaittime
Resolve:PresenceͲbasedexpertescalation,CTIapplicationsintegration,agentdesktopapps
Review:Analytics,callrecording,realͲtimeagentfeedbacktools,automatedcustomersurveys,
reportingandanalytics,callmonitoringandcradleͲtoͲgravereporting
Thedataimplythatthosetechnologiesthatrouteandqueueinquiriesproperlyincreasethe
probabilitythatthecontactswillbehandledappropriatelyandcompletelywhentheyreachthe
"resolve"phase.Inaddition,agentswhoareenabledbytheproperdesktoptechnologies(CRM
andCTIsystems,etc.)areabletofindandcommunicatethecorrectanswerthatthecustomer
needstosatisfyandcloseaninquiry.Thetransparencyandfeedbackthatcomewithsuperior
reviewtools,includingrealͲtimeagentfeedback,alsoappeartobemajorfactors.
Toputthisfindingintomanagerialcontext,weconsiderthesavingsthatcouldresultfrom
installingatechnologyortechnologiesthatimproveFCRby7%,whichisinthemidͲrangeof
theresultsshownabove.Wemaketheconservativeassumptionthatanunresolvedcallwill
haveonlyonefollowͲupcalltoreachfinalresolution.WealsousetheaverageCostperCallfor
thesampleofparticipants,whichwas$5.05.
HypotheticalFinancialImpactof
ImprovedFirstCallResolution
CallsHandledperYear
ReducedFollowͲUpCalls(7%)
AverageCostperCall
TotalCalculatedAnnualSavings
2,000,000
140,000
$5.05
$707,000.00
Figure6.HypotheticalFinancialImpactofImprovedFirstCallResolution
Understandingthatthisisbutoneofthepotentialfinancialimpactsofthistechnology,itis
clearlyworthinvestigatingtechnologiesthatcouldprovidesuchsavings,andthencalculating
thereturnoninvestmenttoseeifitwillbenefitthecenterfinancially.
Inaddition,ifacenter'sdatashowsapositivecorrelationbetweenFCRandCallerSatisfaction,
thenmanagerswouldfindthemselveswithanimportantaddedbenefitintermsofquality
21
measurements.Thehypotheticalsituationbelowreflectsacenterwhosedataindicatethat
CallerSatisfactionimprovesby1%forevery2%improvementinFCR:
HypotheticalImprovementinCaller
Satisfaction
ImprovementinFirstCallResolution
7.0%
Assumingimprovementof1%CallerSatfor
every2%improvementinFCR
ExpectedImprovementinCallerSat
2.0%
3.5%
Figure7.HypotheticalImprovementinCallerSatisfaction
Inthecontactcenterworld,whereeachpointofcallersatisfactionisabattletobefoughtand
won,thiscouldbeofgreatimportancetomanymanagers.
ForadditionalinformationonthedatarefertoAppendixC.
CostPerCall
CostperCallwasreducedsignificantlybythetechnologiesinFigure8:
TechnologyImpactonCostperCall(%)
PresenceͲBasedExpertEscalation
34.51
MultiͲCriteriaRouting
33.22
CourtesyCallͲBackwhileinQueue
23.68
CTI&AppsIntegration
21.97
AutomatedCustomerSurvey(IVR)
21.11
AdvancedReporting&Analytics
20.60
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
Figure8:TechnologyImpactonCostperCall(%)
Theseresultsindicatethatmoreadvancedanduncommontechnologies,suchasMultiͲcriteria
Routing(34.5%positiveimpactoncostpercall)andPresenceͲBasedExpertEscalation(33.2%
positiveimpactoncostpercall),deservenoticeandconsiderationbycontactcentermanagers.
Whilethislistdoesnotincludealltechnologiesthatwemightexpectwouldhaveanimpacton
22
costpercall,itisfocusedontechnologiesthatarefoundinthelastfourgroups(or"silos")of
technologies(indicatedinFigure1above,theContactCenterMaturityModel),whicharethe
silosinwhichmostcontactcentercostsarefound.
Atanaveragecostpercallof$5.05forthesamplegroupincludedinourstudy,asavingsonthe
orderof20%is$1.10.Inacallcenterhandling1,000,000callsperyear,thiswouldbeasavings
ofoveronemilliondollarsͲthesortofsavingsthatcouldprovideanattractiveROIafter
figuringthecostsofnewtechnology.
Notethattheresultsaboveareatthe70%confidencelevelorabove,exceptfortheCTIApps
Integrationresult,whichisata95%confidencelevel.Therefore,theresearchteamconsiders
itprudenttomoderateexpectedoutcomes,whichnonethelesscouldbequitedramatic.
CustomerSatisfaction
Inthisdatacut,topboxcustomersatisfaction(whichisdefinedasreceiving5outof5scoreon
thequestion"Overall,howsatisfiedwereyouwithyourinteraction"),waspositivelyaffected
bythefollowingtechnologies:
TechnologyImpactonCustomerSatisfactionTopBox(%)
CradletoGraveReporting
6.58
ContactDataAnalytics
5.29
WorkforceManagement
4.75
0
1
2
3
4
5
6
7
8
Figure9.TechnologyImpactonCustomerSatisfactionTopBox(%)
Notethatcustomersatisfactionisametricthatisgatheredbyonly62.98%oftherespondents.
However,forcentersthatgathersuchdata,thereisaninterestingmixoftechnologiesin
centersthatreporthigherratesofsatisfaction,asshownabove.CentersthatuseWorkforce
Managementtechnologytostaffproperlyandthattakean"eyeswideopen"approachto
operationsreview(withcradletogravereportinganddataanalytics)arethosethatfarebest.
Thiscorrespondswithourexperienceinassessingcenters:operationsthatcontinuallymanage
tonumbershavecustomersatisfactionhighontheirdashboardofmetrics.Theyregularly
tweaktheirprocessestoseehowtheycanimprovetheirsatisfactionscoresbytryingnew
approachesandmeasuringresults.
23
Byusingtheabovetechnologies,callcenterscan,onaverage,expectimprovementsintheir
TopBoxCustomerSatisfactionbetween4%and7%.GiventhattheaverageTopBoxCaller
Satisfactionwas69.85%inourstudy,a4%to7%boostwouldbringtheaverageoverthe70%
mark.
ForspecificinformationpleaserefertoAppendixC.
BottomBoxCustomerSatisfactionshowedareductioninlevelsofdissatisfactionbyapplying
thefollowingtechnologies:
TechnologyImpactonCustomerSatisfactionBottomBox(%)
66.48
SpeechRecognition
CallRecording&Retrieval
48.16
WorkforceManagement
47.49
DTMF(TouchͲtone)IVR
39.91
0
10
20
30
40
50
60
70
80
Figure10.TechnologyImpactonCustomerSatisfactionBottomBox(%)
Whilethetechnologiesindicatedshowpositiveimpactsata70%confidencelevel,theimpacts
areconsiderableinpercentageterms.ThismetricsharesWorkforceManagementincommon
withTopBoxCustomerSatisfaction.Speechrecognition,whichisamuchdiscussedand
somewhatcontroversialtechnology,topsthelistoftechnologieshere,butnotforTopBox
Satisfaction.Wecanreasonablyinferthat,duetomajorimprovementsinthistechnologyin
recentyears,thisselfͲservicetechnology,whilenotalwayscreatingtopboxratings,is
preferredtothealternative(longerwaittimes)andpreventscustomersfromslippingtothe
verydissatisfiedlevel.Callrecordingandretrievalhelpscentersidentifyandcorrectagent
behaviorswhichcancausebottomboxdissatisfaction.
WewishtopointoutthatBottomBoxSatisfactionlevelsareusuallylownumbers;theaverage
fortheparticipantsinthisstudywas3.34%.Thereforea30%differenceinresultstranslates
intoa1%reduction,from3.34%to2.34%.
24
AgentSatisfaction
Inthisstudy,topboxagentsatisfactionwaspositivelyaffectedbythefollowingtechnologies:
TechnologyImpactonAgentSatisfactionTopBox(%)
AdvancedReporting&Analytics
11.43
AgentDesktopwithCTI
9.89
CradletoGraveReporting
9.59
CTI&AppsIntegration
9.21
RealͲtimeAgentFeedbackTools
5.58
ContactDataAnalytics
4.37
0
2
4
6
8
10
12
14
Figure11.TechnologyImpactonAgentSatisfactionTopBox(%)
Severaltechnologieswereshowntohaveapositiveeffectonagentsatisfaction.Thesedata
supporttheexperientialconclusionsofBenchmarkPortalconsultantsthatagentsatisfaction
canhaveanimportant"canaryinthecoalmine"(orcanaryinthecontactcenter)function
whenitcomestocontactcentertechnology,asenergyandoxygencanbesuckedoutofyour
centerbypooragentmorale.Highagentsatisfactionisareliableindicatorthatthecenterhas
optimizedpeople,processesandtechnology,andthattheoperationsarereallyworkingwell.
Thedataindicatethatwheretherearetechnologiesthatmakeinformationandfeedback
availabletotheagents,theagentsaremoresatisfied.CTIdesktopandappsintegrationsboth
enabletheagenttobetterservetheclientwithconfidence.Customersarelesslikelytobe
irritatedwhentheyconnecttoanagentiftheyknowallalongwhatthewaittimeinqueueis.
Havinggoodreporting,andespeciallyrealͲtimeagentfeedbacktechnologytools,helpsthe
centertohaveadashboardoftheinformationthatmanagerscanmonitorandthatagents
needtohaveandwanttosee.Agentsareempoweredtoimprovetheirownperformanceand
feelmoreincontroloftheirprofessionalliveswhenthesetechnologiesareavailable.
CallsperHour
CallsperAgentperHourisakeyproductivitymetricthatisfollowedbymanagersinmost
reasonablysophisticatedcenters.Eveninsituationswheremanagementhasmadeaconscious
25
decisionnottopressureagentstoreducetalktime,thereremainsadesiretofitasmanygood
callsaspossibleintoeachhouranagentspendspluggedintothesystem.
TechnologyImpactonInboundCallsperAgentperHour(%)
MultiͲCriteriaRouting
17.75
CTI&AppsIntegration
17.69
RoutingbyACD
16.78
PresenceͲBasedExpertEscalation
14.32
ContactDataAnalytics
12.68
NoQueue,HuntGroup
9.29
AdvancedReporting&Analytics
8.28
CustomerCrossͲSellMessagewhileinQueue
7.66
UnifiedCrossͲChannelRouting
6.96
SeparateTollͲFreeNumbers
6.88
NaturalLanguageIVR
6.76
0
2
4
6
8
10
12
14
16
18
20
Figure12:TechnologyImpactonInboundCallsperAgentperHour(%)
Numeroustechnologiesshowedapositiveimpactonthismetric,withresultsvaryingfromover
6%tojustunder18%ͲͲamountsthatcanhaveamajorimpactoncostofoperationsand
providejustificationforinvestmentintechnology.
Ahypotheticalincreaseof10%,from7callsperagentperhourtoasustainable7.7callsper
agentperhour,wouldhaveanimportanteffectonproductivityandfinancialperformancefor
thecenter.
QueueTime
Naturally,thebiggestimpactonqueuetimeisthestaffinglevelsofthecenter;themoreagents
thereare,thefastercustomerswillbeserved.However,therighttechnologiescanhelp
expeditecallhandlingandthereforereduceirritatingandsometimescostlyqueuetimes
withoutanincreaseinresources.
26
TechnologyImpactonQueueTime
43.21
PresenceͲBasedExpertEscalation
34.27
CourtesyCallͲBackwhileinQueue
33.63
BlendedRouting
26.11
MultiͲCriteriaRouting
20.55
NoQueue,HuntGroup
19.18
SkillsBasedRouting
18.36
AgentTrace
16.14
SilentCallMonitoring
12.25
AutomatedCustomerSurvey(IVR)
0
5
10
15
20
25
30
35
40
45
50
Figure13.TechnologyImpactonQueueTime
Logically,courtesycallbackfunctionalitycanimprovequeuetimesubstantially,sinceitprovides
thecallerwithanalternativetowaitinginqueue.However,severalothertechnologiesthat
involveimprovedroutingofcallsandexpeditedescalationofcallsalsoarefoundincenters
whichreportedsignificantlybetterqueuetimesthanthosewithoutthetechnologies.
FirstContactResolutionEͲmail
WithmorecentersbecomingmultiͲchannel,managersarepayingcloserattentiontothe
serviceandthecostsassociatedwitheͲmailresponses.
TechnologyImpactonFirstContactResolutionEͲmail(%)
25.15
CTI&AppsIntegration
24.61
MultiͲCriteriaRouting
23.86
UniversalMultiͲChannelQueue
UnifiedCrossͲChannelRouting
22.90
22
22
23
23
24
24
25
25
26
Figure14.TechnologyImpactonFirstContactResolutionEͲmail(%)
Notsurprisingly,theresearchfoundthatthebiggestbooststofirstcontactresolutionfortheeͲ
mailchannelcamefromadvanceduniversalqueuingandroutingtechnologies,aswellas
applicationstobringinformationtotheagentdesktop.
27
CostperContact:EͲmail
TechnologyImpactonCostperContactEͲmail(%)
UniversalMultiͲChannel…
85.32
UnifiedCrossͲChannel…
85.12
BlendedRouting
74.00
65
70
75
80
85
90
Figure15.TechnologyImpactonCostperContactEmail(%)
ThedataindicatethatadvancedmultiͲchannelroutingandqueuinghaveamajorimpacton
costsforeͲmailhandling.ThismeansthatcenterswhichhavelargeorgrowingeͲmailtraffic
woulddowelltoinvestigatethisenablingtechnologysoastoimprovetheircoststructureinan
importantway.
Chat
Aschatvolumesincreaseinmanycenters,thecostforhandlingtheseinteractionsbecomes
moreofaconcern.
TechnologyImpactonCostperContactChat(%)
BlendedRouting
72.98
WebContactChat
42.61
0
10
20
30
40
50
60
70
80
Figure16.TechnologyImpactonCostperContact–Chat(%)
ThesamethingsindicatedabovefortheeͲmailchannelcanbesaidforthechatchannel.While
thetechniquesformeasuringcostperchatarestilllessmaturethantheequivalentforthe
voicechannel,managersshouldstillconsidernewtechnologyandtheeffectitwillhaveon
themfinancially.
28
FirstContactResolutionͲChat
Severaltechnologieswereshowntohaveapositiveeffectonfirstcontactresolution:
TechnologyImpactonFirstContactResolutionChat(%)
CTI&AppsIntegration
50.57
UniversalMultiͲChannelQueue
50.57
CRMDesktopSystem
39.59
WebContactChat
39.26
0
10
20
30
40
50
60
Figure17.TechnologyImpactonFirstContactResolutionChat(%)
TheresultsindicatethathavingaproperWebcontactchatsystem,alongwithinformationthat
bringsneededinformationtothechatagent(CTI&AppsIntegrationandCRMDesktopSystem)
allowtheagenttofullyservicethechatcustomerandbetterresolvetheinquiryonthefirst
interaction.
29
COMBINEDEFFECTRESULTS
Correlatingtwokeymetricsagainsteachotherproducedsomeinterestingfindings.Though
generallynotstrongstatistically,thecorrelationsweredirectionallyimportantandcanbeseen
inFigure18.
CostperCallvs.CustomerSatisfaction
Thedatashowsasmallnegativecorrelation(Ͳ0.24)betweenCostperCallandCustomer
Satisfaction.Thenegativesignsupportsthehypothesisthatbyusingtechnologycallcenters
canlowertheirCostperCallwhileimprovingtheirCustomerSatisfaction.
FirstCallResolutionvs.CustomerSatisfaction
Thereisasmallpositivecorrelation(0.33)betweenFirstCallResolutionandCustomer
Satisfaction.ThepositivesignindicatesthatbyusingtechnologycallcenterscanimproveFirst
CallResolutionandCustomerSatisfactionatthesametime.
CostperCallvs.FirstCallResolution
CostperCallandFirstCallResolutionarenegativelycorrelated(Ͳ0.25).Thoughthevalueofthe
correlationcoefficientissmall,thenegativesignsupportsthehypothesisthatbyusing
technologycallcenterscanlowertheirCostperCallwhileimprovingtheirFCR.
CustomerSatisfactionvs.AgentSatisfaction
Finally,aweakcorrelation(0.12)existsbetweenCustomerSatisfactionandAgentSatisfaction.
Thepositivesignimpliesthatthesemetricsgohandinhand.
Cost per Call vs First Call Resolution
10
20
y = -0.0479x - 0.1792
R² = 0.0558
8
6
4
2
0
-40
-30
-20
-10
-2
0
10
20
30
-4
-6
10
5
0
-40
-30
-20
-10
15
y = 0.2158x - 1.0549
R² = 0.1101
8
6
4
2
0
0
5
10
-4
-6
15
20
Agent Satisfaction Top Box
Customer Satisfaction Top Box
30
Customer Satisfaction Top Box vs Agent Satisfaction Top Box
10
y = 0.1804x + 2.5352
R² = 0.0143
10
5
0
-8
-8
-6
-4
-2
0
2
4
-5
-10
First Call Resolution
Customer Satisfaction Top Box
Figure18.CombinedEffectsAnalyses
30
20
Cost per Call
First Call Resolution vs Customer Satisfaction Top Box
-2
10
-10
-8
-5
0
-5
Cost per Call
-10
y = -0.0775x + 4.2639
R² = 0.0616
15
First Call Resolution
Customer Satisfaction Top Box
Cost per Call vs Customer Satisfaction Top Box
6
8
10
CONCLUSIONSFROMTHERESEARCH
Thisresearchrepresentsthefirstofitskindtocorrelatetechnologywithcontactcenter
performanceacrossalargenumberofcenters.Weexpectthatmoreresearchwillbesparked
bythisinitiativeandthatadditionalvaluableinsightswillbeuncoveredinfuturestudies.We
knowfromexperiencethatcenterswhichhavecertaintechnologiesdonotalwaysdeploythem
optimally,andafutureresearchprojectmaydelvemoreintotheutilizationoftechnology.
Themethodologyusedforthisinitialstudywaspowerfullystraightforwardandmatchedthe
natureoftheinformation.Wedidnotaskmanagersfortheiropinions,feelings,plansor
experiencesregardingtechnology.WeaskedthemonlyfortheirdataͲͲdataontheircenter's
technologyanddataontheircenter'sperformance.
Theresultsofthestudyindicatethatmorematurelevelsoftechnologydrivebetter
performanceonimportantcontactcentermetrics.Forinstance,they:
x IncreaseFirstContactResolution
x IncreaseAverageCallsHandled
x LowerCostperCall
x DecreaseQueueTime
x ImproveCallerSatisfaction
x IncreaseAgentSatisfaction
Thetechnologiesthatalignorcorrelatestatisticallywithindividualmetricscomefromacross
theContactCenterMaturityModelspectrum.Certainly,wedonotalwaysseetheexpected
technologiesleadingthelistforaspecificmetric,andwesometimesseetechnologiesthat
seemtohavelittleincommonwithametricnonethelessstatisticallyassociatedwithit.
Overall,however,thedataclearlyindicatethatmoreadvancedtechnologiesimproveboththe
efficiencyandeffectivenessofcontactcenters.Technologiesthatensureproperstaffing,
ensureproperconnectionandrecognitionofinquiries,promoteproperrouting,queuingand
resolution/escalationofcontacts,andprovidereportingandanalyticstobothagentsand
management,arepotentenablersofsuperiorperformance.
Whileinvestmentsintechnologymustalwaysbeanalyzedandtrackedindividuallyto
determineoperationalandfinancialbenefit,thisresearchprovidesapositive,statistically
relevantbackdropthatfavorsinvestingintechnologicalmaturitytoimprovecontactcenter
financialandqualityperformance.
31
APPENDIXAͲBIOGRAPHIES
BruceBelfioreisSeniorResearchExecutive,CenterforCustomerͲDrivenQualityTMand
CEOofBenchmarkPortal(www.benchmarkportal.com).BenchmarkPortalprovides
bestpracticesreports,researchandconsultingtothecustomercontactindustry
worldwide.
Brucefirstbecameinvolvedinthecontactcentersectoroveradecadeago.Hejoined
BenchmarkPortalin2000.BruceistheauthorofnumerouswhitepapersandthebooksBenchmarking
forProfits!,amanualforbestpracticescontactcenterbenchmarking,aswellasitssequel,
BenchmarkingatitsBestforContactCenters.Heiscurrentlyworkingonanotherbook,Shareholder
ValueandCustomerContact.
BruceisDeanoftheCollegeofCallCenterExcellence(www.benchmarkportal.com/callͲcenterͲtraining),
whichprovidescoursestocontactcentermanagersandsupervisors.Heisalsothehostoftheinternet
radiotalkshowCallTalk,(www.benchmarkportal.com/callͲcenterͲnewsresources/calltalkͲonlineͲradioͲ
show)whichexplorescontactcentertopicswithindustryexperts.
HeiscoͲinventorofapatentforasymboliclanguagesystem,Simbly™,withimportantcontactcenter
applications.HehastaughttheCallCentermanagementcourseatPurdueUniversitywithProfessor
RichardFeinberg.
BrucehasdividedhiscareerbetweenNorthAmericaandEurope,andhasfulfilledworkassignmentsin
AsiaandAfricaaswell.Hepreviouslyworkedinthefinancesectorwithinternationalcommercialand
investmentbanksandwiththeBain&Co.ManagementConsultinggroupinItaly.WhileinEurope,
BrucewasalsoaspeakerandwriteronbusinesstopicsinEnglishandItalian.
BruceholdsanA.B.degreefromHarvardCollege,aJ.DdegreefromHarvardLawSchool,andanM.B.A.
degreefromHarvardBusinessSchool,wherehealsoattendedtheHBSEntrepreneur’sToolKitprogram
in2000.HehaspublishednumerousarticlesandhasbeenafeaturedspeakerinbothEnglishand
Italianonavarietyofbusinesstopics.
[email protected].
32
JohnChatterleyisaSeniorConsultantandDirectorofResearchandAnalysisfor
BenchmarkPortal,specializingincontactcenterperformanceresearch,analysis,
technicalwriting,andcontentediting.Johnhaspublishednumerouscustomized
benchmarkingreports,researchreports,OneͲMinute™Surveyreports,andWhite
Papers.
Johniseditor,writerandanalystofBenchmarkPortal’sannualseriesof48detailed
industryreportscoveringthespectrumofcontactcenterindustrysectors,andchiefeditorandanalyst
ofBenchmarkPortal’sseriesofOneͲMinute™Surveys.HeauthoredacomprehensiveWhitePaperstudy
entitled“ImprovingContactCenterPerformancethroughOptimizedSiteSelection.”Johnhassharedhis
contactcenterexpertisewithnumerousclients,bothdomesticallyandinternationally.Heisafaculty
memberwiththeCollegeofCallCenterExcellence.
JohncoͲauthoredoreditednumerousbookswithDr.JonAnton,including:
1. CoachingCallCenterAgents
2. DefiningCustomerCare
3. AutomatedSelfͲServiceUsingSpeechRecognition
4. ListeningtotheVoiceoftheCustomer
5. ContactCenterManagementbytheNumbers
6. OffshoreOutsourcingOpportunities
7. SelectingaTeleservicesPartner
8. InterpretingtheVoiceoftheCustomer
John’sprofessionalcareerspansmorethan25yearsofexperienceincallcentermanagementand
consulting.Johndesigned,implemented,staffedandmanagedthree500+seatcontactcentersitesin
Arizona,Nevada,andCalifornia,andhasextensivecallcenteroperationalmanagementexperience.He
possessesfirsthandexperienceatalllevelsofacontactcenterincludingfrontͲlinetechnicalsupport
agent,supervisor,teamlead,analyst,designer,callcentermanager,andoperationsdirector.
JohnisaCertifiedContactCenterAuditor,CertifiedCallCenterCollegeInstructor,BenchmarkPortal
CertifiedBenchmarkingInstructorandAnalyst.John’sprofessionaleducationwasinElectrical
Engineering&ComputerScienceatSouthernUtahUniversityandtheUniversityofUtah.
[email protected]
33
Dr.NataliePetouhoffisaResearchExecutiveattheCenterforCustomerͲDriven
Quality(foundedatPurdueUniversity)andBenchmarkPortal,whichservesthecontactcenterindustry
withadvancedbenchmarking,certification,researchandeducation.
Natalie,authoroffourbusinessbooks,hasbeenspeakingaboutcustomers,companiesandthebottom
linefor20years.AstheDirectoroftheUCLAExecutiveEducationProgramandaninstructorforSocial
Media,sheguidescompaniesasabusinessstrategisttounderstandwherethepotentialisandhowto
leadcompaniestogreatersuccess.
Natalie’suniqueperspectiveonbusinessandthoughtleadershipiscurrentlybeingappliedtosocial
media,asshehelpscompanieslearnhowtouseittoincreasethebottomline.Hersocialmedia
assessmentsandROIcalculatorsprovidetacticalstrategies,planningandrealͲworldexecution
capabilities.
Natalie’sworkandWhitePapersarethesubjectofhundredsofarticlesinpublicationslikeUSAToday,
Adage,BusinessWeek,FastCompany,TheNewYorkTimes,TheWallStreetJournal,PeppersandRogers
1ͲtoͲ1MagazineandCRMMagazineaswellasnationaltelevisionandradio.
PresidentoftheLosAngelesSocialMediaClub,NataliehasheldpositionsasaForresteranalyst,chief
strategistforaWeberShandwickPR/MarketingAgency,managementconsultantatPWCandHitachi
andinmanagementatHughesElectronics,GMandGE.
Herfocusincludeshelpingclientstodriverevenueandprofits,developsocialbusinessstrategiesand
tacticalplansaswellascreatingtrainingprogramsforleadership,employeemotivationand
organizationalchange.NataliealsoteachesPR,MarketingandLeadershipcoursesattheUniversityof
SouthernCaliforniaandPepperdineUniversity.
NataliecanbereachedatNataliePetouhoff@BenchmarkPortal.com.Examplesofherworkare
availableat:
Ebook:SocialMediaROIMythsandTruths
YouTubeVideos:OnROIofSocialMedia
WhitePapers:SocialMediaROI
NewBookonFacebook:LikeMyStuffͲHowtoMonetizeYourFacebookFansWithSocialCommerce&AFacebookStore
Twitter:@drnatalie
LinkedIn:DrNataliePetouhoff
website/blog:www.drnatalienews.com/blog
G+:GooglePlusposts
34
AngelTonchevfirstcollaboratedasastatisticalanalystwith
BenchmarkPortalalmostadecadeago.Withhisbrother,Christo,heisacoͲ
developeroftheTonchevPerformanceIndexforcallcenters,originally
developedfortheCenterforCustomerͲDrivenQualityatPurdueUniversity
andstillutilizedbyBenchmarkPortal.Hehasmorethantenyearsof
benchmarkingexperienceinavarietyofindustries,includingcallcenters,oil
andgas,procurementandinformationtechnologies.
AngelisamanagerandcoͲfounderofPerformathics,LLC–aconsultingcompanyspecializing
inmathematicalmodelingandstatisticalanalysesforbusinesses.AngelisalsoacoͲinventor
oftheJuranHydrocarbonsIndex,whichiswidelyusedtomeasuretheoperational
performanceofassetsthroughouttheentireoilandgasvaluechain.
Heholdsamaster'sdegreeinEconomicsfromMaastrichtUniversity(theNetherlands),a
bachelor’sdegreeinBusinessfromSofiaUniversity(Bulgaria)andanEngineeringdegree
fromtheTechnicalUniversityinSofia.HeisacertifiedSixSigmaBlackBeltandacertifiedCall
CenterAuditor.Additionally,AngelisacoͲauthorofseveralacademicarticlesandhas
publicationsinleadingindustryjournals(Oil&GasJournal)andbusinessbooks(JuranQuality
Handbook,6thedition).
͸Ͷ
͵ͷ
Copyright © 2012 BenchmarkPortal, LLC.
ChristoTonchevfirstcollaboratedasastatisticalanalystwith
BenchmarkPortalalmostadecadeago.Withhisbrother,Angel,heisacoͲ
developeroftheTonchevPerformanceIndexforcallcenters,originally
developedfortheCenterforCustomerͲDrivenQualityatPurdueUniversity
andstillutilizedbyBenchmarkPortal.
ChristoisaManagerandCoͲfounderofPerformathics,LLC–aconsulting
companyspecializinginmathematicalmodelingandstatisticalanalysesforbusinesses.He
hasmorethantenyearsofbenchmarkingexperienceinavarietyofindustries,includingcall
centers,oilandgas,procurementandinformationtechnologies.ChristoisalsoacoͲinventor
oftheJuranHydrocarbonsIndex,whichiswidelyusedtomeasuretheoperational
performanceofassetsthroughouttheentireoilandgasvaluechain.
Christoholdsamaster'sdegreeinEconomicsfromMaastrichtUniversity(theNetherlands)
andabachelor'sdegreeinBusinessfromSofiaUniversity(Bulgaria).Inaddition,hestudiedat
theHigherInstituteofPhysicalCulture(Bulgaria).HeisacertifiedSixSigmaBlackBeltanda
certifiedCallCenterAuditor.Christoisanauthorofseveralacademicarticlesandhas
publicationsinleadingindustryjournals(Oil&GasJournal)andbusinessbooks(JuranQuality
Handbook,6thedition.
͸Ͷ
͵͸
Copyright © 2012 BenchmarkPortal, LLC.
DeeBuellhasover20yearsofCallCentermanagementexperienceinthe
financialindustry.Shehasmanagedandoperatedinboundandoutbound
serviceteams,aswellasinboundandoutboundsalesteams.
AsaSeniorBusinessConsultant,DeeisaCertifiedAuditorandacallcenter
subjectmatterexpert(SME)withafocusonQualityManagement.She
hasexperienceinbuildingaqualitymanagementsystemthatusesagentperformance
metrics,customersatisfactionanalysis,andcustomerrelationshipmanagement(CRM)data
todriveaneffectiveandefficientcustomerexperience.
ShemanagedthequalityandtrainingteamsforMetLifeInsurance,withastaffof1200+
agents,bothinͲhouseandoutsourced.Thetrainingteamsupported17differentcallgroups
insixsitesacrosstheUnitedStatesandinthreesitesoffshore.Customizedtraining
curriculum,onlinetrainingtools,andvirtualtechnologywereusedtoinsureconsistencyin
thevirtualcallcenterenvironment.
[email protected]
͸Ͷ
͵͹
Copyright © 2012 BenchmarkPortal, LLC.
APPENDIXB–SPEARMAN’SCORRELATIONTABLES
Spearman’srankcorrelationisanonͲparametricstatisticaltestwhichmeasuresthestatistical
relationshipbetweentwovariables.Spearman’srankcorrelationcoefficient(rho)varies
betweenͲ1and1.Thesignofthecoefficientindicatesthedirectionofassociationbetween
thevariables.Ifoneofthevariablestendstoincreasewhentheotheroneincreases,the
Spearmancorrelationcoefficientispositive.Incontrast,ifoneofthevariablestendsto
decreasewhentheotheroneincreases,theSpearmancorrelationcoefficientisnegative.A
Spearmancorrelationofzeroindicatesthatthereisnorelationshipbetweenthevariables.
PleasenotethatforsomeKPIsanegativecorrelationbetweenthesemetricsandthe
technologymayimplyapositiveimpact.Forexample,theAUXTimeandTechnologyIndex
haveanegativecorrelationcoefficient(Ͳ0.15).Thisindicatesthatasthetechnologyincreases
theactualAUXTimedecreases.SincetheshorterAUXTimeisbetterforthecontactcenters,
theoverallimpactoftechnologyonthisparticularmetricispositive.
Note:Greencellsindicatestatisticalsignificanceat95%confidencelevel.;Yellowcellsadd
thestatisticallysignificantcorrelationsat80%confidencelevel.
Spearman's Correlation: All Industries
Variables
AUX Time
Agent Utilization
Average Calls per Hour
Agent to Supervisor Ratio
Calls Resolved on First Call
Top Box Agent Satisfaction
Correlation coefficient (rho) Probability (p)
Technology Index
0.107
-0.1503
0.0993
0.177
0.1848
0.012
0.1353
0.110
0.2137
0.008
0.1859
0.002
͸Ͷ
͵ͺ
Copyright © 2012 BenchmarkPortal, LLC.
Spearman's Correlation: Bank Industry
Variables
Performance Index
Efficiency Score
Cost per Call
Average Talk Time
Average After Call Work Time
Agent Occupancy
Adherence to Schedule
Agent Attendance
Agent to Supervisor Ratio
Annual Turnover FTA
Average Speed of Answer 80%
Average Speed of Answer
Average Hold Time
Abandoned Calls
Customer Satisfaction Top Box
Correlation coefficient (rho) Probability (p)
Technology Index
0.8857
0.047
1.0000
0.025
0.089
-0.7827
-0.6000
0.177
-0.8857
0.047
0.8286
0.063
0.6957
0.116
0.7590
0.084
0.8208
0.097
0.8000
0.165
0.177
-0.6000
-0.6000
0.177
0.8286
0.063
-0.7714
0.084
1.0000
0.025
Note:Greencellsindicatestatisticalsignificanceat95%confidencelevel.Yellowcellsadd
thestatisticallysignificantcorrelationsat80%confidencelevel.
Spearman's Correlation: Financial Industry
Variables
Performance Index
Efficiency Score
Effectiveness Score
Agent Utilization
Correlation coefficient (rho) Probability (p)
Technology Index
0.6530
0.038
0.6758
0.032
0.5662
0.072
0.4136
0.174
͸Ͷ
͵ͻ
Copyright © 2012 BenchmarkPortal, LLC.
Spearman's Correlation: Insurance Industry
Variables
Performance Index
Efficiency Score
Effectiveness Score
Average Talk Time
Average After Call Work Time
Agent Occupancy
Agent Attendance
Agent Utilization
Average Calls per Hour
Annual Turnover FTA
Average Speed of Answer 80%
Average Speed of Answer
Average Queue Time
Abandoned Calls
Calls Resolved on First Call
Customer Satisfaction Top Box
Top Box Agent Satisfaction
Correlation coefficient (rho) Probability (p)
Technology Index
0.5018
0.007
0.4568
0.013
0.4416
0.016
-0.3130
0.129
-0.4144
0.041
0.2353
0.180
0.2676
0.134
-0.2953
0.159
0.5171
0.005
-0.3354
0.110
0.002
-0.6333
-0.6333
0.002
0.3520
0.051
-0.2787
0.187
0.4379
0.017
0.3340
0.064
0.3712
0.037
͸Ͷ
ͶͲ
Copyright © 2012 BenchmarkPortal, LLC.
Note:Greencellsindicatestatisticalsignificanceat95%confidencelevel.Yellowcellsadd
thestatisticallysignificantcorrelationsat80%confidencelevel.
Spearman's Correlation: Large Call Centers (Calls Handled >801498)
Variables
Cost per Call
Adherence to Schedule
AUX Time
Average Calls per Hour
Calls Resolved on First Call
Top Box Agent Satisfaction
Correlation coefficient (rho) Probability (p)
Technology Index
0.171
-0.2060
0.2414
0.082
0.043
-0.3204
0.1820
0.184
0.3751
0.010
0.2930
0.014
Spearman's Correlation: Medium Call Centers (Calls Handled <801498)
Variables
Cost per Call
Adherence to Schedule
AUX Time
Average Calls per Hour
Calls Resolved on First Call
Top Box Agent Satisfaction
Correlation coefficient (rho) Probability (p)
Technology Index
0.171
-0.2060
0.2414
0.082
-0.3204
0.043
0.1820
0.184
0.3751
0.010
0.2930
0.014
Spearman's Correlation: Small Call Centers (Calls Handled <146001)
Variables
Cost per Call
Average Talk Time
Adherence to Schedule
Average Hold Time
Abandoned Calls
Customer Satisfaction Bottom Box
Correlation coefficient (rho) Probability (p)
Technology Index
0.2744
0.057
0.2518
0.080
-0.2376
0.171
-0.2124
0.180
0.2246
0.114
0.2679
0.126 ͸Ͷ
Ͷͳ
Copyright © 2012 BenchmarkPortal, LLC.
APPENDIXC–TECHNOLOGYDRILLͲDOWNCHARTSANDTABLES
TechnologydrillͲdownanalysesarebasedonunpairedtwosampletͲtests.ThetͲtestisa
statisticalanalysisthatlooksatonevariable(oneKPI)andassesseswhetherthemeansof
twogroups(i.e.agroupwhichhasagiventechnologyandonewithoutit)arestatistically
differentfromeachother.ThemostimportantresultsfromthetͲtestarethepͲvalue,relative
difference(sizeofthedifferencebetweenthemeansinpercentageterms)andconfidence
interval.Inthisregard,wheninterpretingtheresultsfromthetablesbelow,thesmallerpͲ
valuesandhigherrelativedifferenceswillindicatethattheKPIaveragesofthesampleswith
andwithoutaspecifictechnologydiffersignificantly.Therefore,wecanconcludethatthis
technologyhasanimpactontheKPI.Iftherelativedifferencehasanegativesignthisimplies
thatthetechnologydecreasestheKPIvalue(notnecessarilyanindicationfornegative
impact).
͸Ͷ
Ͷʹ
Copyright © 2012 BenchmarkPortal, LLC.
Technology Adoption
ACD
100.00
Skills Based Routing
83.69
PBX
78.01
DTMF (Touch-tone) IVR
71.63
Call Recording & Retrieval
65.25
Workforce Management 59.57
E-mail Management System
56.03
CRM Desktop System
47.14
Recorded Message while on Hold
40.43
ANI / DNIS for Customer ID
39.72
Speech Recognition
39.01
Routing by ACD
39.01
ACD Based Queue
38.30
Queue Prioritization
37.59
Silent Call Monitoring
37.59
Separate Toll-Free Numbers
36.17
Music on Hold
34.75
Contact Data Analytics
31.21
CTI & Apps Integration
29.08
Web Contact Chat
28.37
Automated Customer Survey (IVR)
27.66
E-mail Response System
26.95
Agent Desktop with CTI
26.95
Natural Language IVR
26.95
Agent Pop-Ups for Up-sell/Cross-sell
21.28
Routing across ACDs
19.15
E-mail Satisfaction System
18.44
Unified Cross-Channel Routing
17.02
Announced Wait Time in Queue
17.02
Routing beyond Call Center
17.02
Real-time Agent Feedback Tools
17.02
Agent Trace
16.31
Pre-Routing to ACDs
16.31
Cradle to Grave Reporting
15.60
Universal Multi-Channel Queue
14.89
Personalized VRU
14.18
Advanced Reporting & Analytics
14.18
Blended Routing
12.77
Actionable Alerts with Solutions
12.77
Customer Cross-Sell Message while in Queue
11.35
No Queue, Hunt Group
10.64
Speech Synthesis Apps
10.64
Courtesy Call-Back while in Queue
10.64
Competency Based Routing
9.22
Virtualized Enterprise Queue
9.22
Multi-Criteria Routing
7.09
Automated Personal Call-Backs
6.38
Presence- Based Expert Escalation
3.55
10
20
30
40
50
60
70
80
90
100
%
0
͸Ͷ
Ͷ͵
Copyright © 2012 BenchmarkPortal, LLC.
Technologies With A Positive Impact On Cost Per Call (CPC)
Relative
Difference
between
Means (%)
Technology
P value
The mean of
Group "Yes"
95% CI
95% CI
Mean "Yes"
minus Group Lower Limit Upper Limit
Group
"No"
CTI Apps Integration
-21.97
0.043
-1.42
-2.79
-0.05
5.03
6.45
Autom ated Custom er Survey (IVR)
-21.11
0.057
-1.35
-2.75
0.04
5.06
6.41
6.18
Multi-Criteria Routing
-33.22
0.098
-2.05
-4.49
0.38
4.13
Real-tim e Agent Feedback Tools
-20.17
0.137
-1.26
-2.93
0.41
4.99
6.25
Custom er Cross-Sell Message w hile in Queue
-23.08
0.155
-1.43
-3.41
0.55
4.77
6.20
Courtesy Call-Back w hile in Queue
-23.68
0.156
-1.47
-3.50
0.57
4.73
6.19
Advanced Reporting & Analytics
-20.60
0.161
-1.28
-3.08
0.52
4.94
6.22
Presence- Based Expert Escalation
-34.51
0.222
-2.11
-5.51
1.29
4.00
6.11
Routing by ACD
-12.06
0.243
-0.76
-2.05
0.52
5.57
6.33
Contact Data Analytics
-12.06
0.272
-0.76
-2.11
0.60
5.52
6.27
Autom ated Personal Call-Backs
-19.62
0.359
-1.20
-3.78
1.38
4.91
6.11
Universal Multi-Channel Queue
-11.27
0.441
-0.69
-2.46
1.08
5.45
6.14
Natural Language IVR
-7.65
0.513
-0.47
-1.89
0.95
5.69
6.16
6.47
Skills Based Routing
-7.95
0.552
-0.51
-2.22
1.19
5.95
Agent Desktop w ith CTI
-5.14
0.663
-0.31
-1.74
1.11
5.81
6.12
Pre-Routing to ACDs
-4.64
0.744
-0.28
-1.99
1.43
5.80
6.08
Routing beyond Call Center
-2.20
0.876
-0.13
-1.81
1.55
5.93
6.06
Silent Call Monitoring
-0.85
0.938
-0.05
-1.36
1.25
6.00
6.06
95% Confidence Level
70% Confidence Level
Mean "No"
Group
͸Ͷ
ͶͶ
Copyright © 2012 BenchmarkPortal, LLC.
Technologies With A Positive Impact On First Call Resolution (FCR)
Relative
Difference
between
Means (%)
Technology
The mean of
Group "Yes" 95% CI Lower 95% CI Upper Mean "Yes"
Limit
Limit
Group
minus Group
"No"
Mean "No"
Group
Contact Data Analytics
12.99
0.000
0.10
0.05
0.15
0.83
0.74
PBX
14.83
0.001
0.10
0.04
0.16
0.79
0.69
Call Recording & Retrieval
12.06
0.001
0.09
0.04
0.13
0.79
0.71
CTI Apps Integration
11.02
0.002
0.08
0.03
0.13
0.82
0.74
Skills Based Routing
12.41
0.010
0.09
0.02
0.15
0.78
0.69
Workforce Managem ent
8.50
0.013
0.06
0.01
0.11
0.79
0.73
Web Contact Chat
7.50
0.039
0.06
0.00
0.11
0.81
0.75
Autom ated Custom er Survey (IVR)
7.50
0.041
0.06
0.00
0.11
0.81
0.75
Real-tim e Agent Feedback Tools
8.80
0.043
0.07
0.00
0.13
0.82
0.75
DTMF (Touch-tone) IVR
7.23
0.054
0.05
0.00
0.11
0.78
0.73
Routing by ACD
6.42
0.058
0.05
0.00
0.10
0.79
0.75
E-m ail Managem ent System
6.22
0.064
0.05
0.00
0.09
0.79
0.74
Com petency Based Routing
9.67
0.085
0.07
-0.01
0.16
0.83
0.76
Courtesy Call-Back w hile in Queue
7.72
0.143
0.06
-0.02
0.14
0.82
0.76
Silent Call Monitoring
4.74
0.163
0.04
-0.01
0.09
0.79
0.75
Presence- Based Expert Escalation
11.58
0.187
0.09
-0.04
0.22
0.85
0.76
Pre-Routing to ACDs
4.90
0.267
0.04
-0.03
0.10
0.80
0.76
Agent Desktop w ith CTI
4.06
0.271
0.03
-0.02
0.09
0.79
0.76
Announced Wait Tim e in Queue
4.44
0.306
0.03
-0.03
0.10
0.79
0.76
Advanced Reporting & Analytics
4.76
0.308
0.04
-0.03
0.11
0.80
0.76
Multi-Criteria Routing
6.37
0.315
0.05
-0.05
0.14
0.81
0.76
Cradle to Grave Reporting
4.12
0.359
0.03
-0.04
0.10
0.79
0.76
CRM Desktop System
2.88
0.384
0.02
-0.03
0.07
0.78
0.75
Custom er Cross-Sell Message w hile in Queue
4.36
0.395
0.03
-0.04
0.11
0.79
0.76
Agent Trace
3.74
0.397
0.03
-0.04
0.09
0.79
0.76
Blended Routing
4.02
0.409
0.03
-0.04
0.10
0.79
0.76
Speech Recognition
2.71
0.420
0.02
-0.03
0.07
0.78
0.76
Music on Hold
2.76
0.423
0.02
-0.03
0.07
0.78
0.76
Speech Synthesis Apps
3.87
0.463
0.03
-0.05
0.11
0.79
0.76
ACD Based Queue
2.10
0.531
0.02
-0.03
0.07
0.77
0.76
Agent Pop-Ups for Up-sell/Cross-sell
2.22
0.575
0.02
-0.04
0.08
0.78
0.76
Unified Cross-Channel Routing
2.24
0.604
0.02
-0.05
0.08
0.78
0.76
ANI / DNIS for Custom er ID
1.57
0.638
0.01
-0.04
0.06
0.77
0.76
Universal Multi-Channel Queue
1.81
0.693
0.01
-0.05
0.08
0.78
0.76
Autom ated Personal Call-Backs
2.57
0.699
0.02
-0.08
0.12
0.78
0.76
Personalized VRU
1.76
0.705
0.01
-0.06
0.08
0.78
0.76
Natural Language IVR
1.38
0.707
0.01
-0.04
0.07
0.77
0.76
Actionable Alerts w ith Solutions
1.51
0.757
0.01
-0.06
0.08
0.78
0.76
E-m ail Response System
1.10
0.766
0.01
-0.05
0.06
0.77
0.76
Routing across ACDs
1.06
0.798
0.01
-0.05
0.07
0.77
0.76
Routing beyond Call Center
0.73
0.866
0.01
-0.06
0.07
0.77
0.76
Virtualized Enterprise Queue
0.51
0.928
0.00
-0.08
0.09
0.77
0.76
95% Confidence Level
P value
70% Confidence Level
͸Ͷ
Ͷͷ
Copyright © 2012 BenchmarkPortal, LLC.
Technologies With A Positive Impact On Customer Satisfaction Top Box (CSTB)
Technology
Contact Data Analytics
Relative
Difference
between
Means (%)
5.29
The mean of
95% CI
95% CI
Mean "Yes" Mean "No"
Group "Yes"
Group
Group
minus Group Lower Limit Upper Limit
"No"
0.207
0.04
-0.02
0.09
0.70
0.67
P value
Cradle to Grave Reporting
6.58
0.217
0.04
-0.03
0.11
0.72
0.67
Workforce Management
4.75
0.237
0.03
-0.02
0.08
0.69
0.66
Advanced Reporting & Analytics
4.66
0.398
0.03
-0.04
0.11
0.71
0.68
Presence- Based Expert Escalation
7.65
0.461
0.05
-0.09
0.19
0.73
0.68
Call Recording & Retrieval
2.51
0.540
0.02
-0.04
0.07
0.69
0.67
Real-time Agent Feedback Tools
2.75
0.591
0.02
-0.05
0.09
0.70
0.68
Courtesy Call-Back while in Queue
3.20
0.608
0.02
-0.06
0.11
0.70
0.68
Agent Desktop with CTI
1.82
0.675
0.01
-0.05
0.07
0.69
0.68
Automated Customer Survey (IVR)
1.79
0.677
0.01
-0.05
0.07
0.69
0.68
Web Contact Chat
1.73
0.688
0.01
-0.05
0.07
0.69
0.68
Unified Cross-Channel Routing
1.73
0.738
0.01
-0.06
0.08
0.69
0.68
Competency Based Routing
2.14
0.748
0.01
-0.07
0.10
0.69
0.68
Separate Toll-Free Numbers
1.20
0.766
0.01
-0.05
0.06
0.69
0.68
Routing beyond Call Center
1.42
0.782
0.01
-0.06
0.08
0.69
0.68
Speech Synthesis Apps
1.33
0.831
0.01
-0.07
0.09
0.69
0.68
Actionable Alerts with Solutions
1.05
0.856
0.01
-0.07
0.08
0.69
0.68
CRM Desktop System
Routing across ACDs
0.63
0.15
0.870
0.976
0.00
0.00
-0.05
-0.06
0.06
0.07
0.68
0.68
0.68
0.68
95% Confidence Level
70% Confidence Level
Technologies With A Positive Impact on Customer Satisfaction Bottom Box (CSBB)
Technology
Speech Recognition
Relative
Difference
between
Means (%)
-66.48
The mean of
Group "Yes"
95% CI
95% CI
Mean "Yes" Mean "No"
minus Group Lower Limit Upper Limit
Group
Group
"No"
0.023
-0.07
-0.13
-0.01
0.04
0.10
P value
Call Recording & Retrieval
-48.16
0.099
-0.06
-0.12
0.01
0.06
Workforce Management
-47.49
0.106
-0.05
-0.11
0.01
0.06
0.11
DTMF (Touch-tone) IVR
-39.91
0.219
-0.04
-0.11
0.03
0.06
0.11
PBX
-38.91
0.268
0.04
-0.12
0.03
0.07
0.11
Advanced Reporting & Analytics
-46.12
0.338
-0.04
-0.12
0.04
0.04
0.08
Contact Data Analytics
-25.98
0.487
-0.02
-0.08
0.04
0.06
0.08
Actionable Alerts with Solutions
-31.70
0.548
-0.03
-0.11
0.06
0.05
0.08
Skills Based Routing
-25.92
0.598
-0.03
-0.12
0.07
0.07
0.10
Automated Customer Survey (IVR)
CRM Desktop System
-19.20
-2.86
0.644
0.942
-0.02
0.00
-0.08
-0.06
0.05
0.06
0.06
0.07
0.08
0.08
95% Confidence Level
70% Confidence Level
0.11
͸Ͷ
Ͷ͸
Copyright © 2012 BenchmarkPortal, LLC.
APPENDIXDͲSURVEYS
SurveyEͲmailInvitation:
Technology&PerformanceSurvey(TM)
ReceiveacomplimentarycopyoftheWhitePaper&achancetowinaniPad!
DearCallCenterProfessional:
Weareexcitedtoinviteyoutoparticipateinanimportantresearchprojectfrom
BenchmarkPortalandTheCenterforCustomerDrivenQuality(foundedatPurdue
University).Thepurposeofthestudyistounderstandthecorrelationbetweenlevelof
technologyandcontactcenterperformance,asmeasuredthroughobjectivemetrics.
YoucanfindmoreinformationaboutthisresearchstudybywatchingourvideoHERE
(http://youtu.be/GCLduHvPZcI)
Yourparticipationwillprovideyouwith:
•FreecopyoftheWhitePaperresults
•AchancetowinaniPad
•Afreebenchmarkreportandareadoutofyourindividualbenchmarkreportbyoneof
ourcertifiedexperts
It'sourwayofshowingourappreciationtoyouforyourinput.
Thesurveylinkbelowwillbenchmarkyourcallcenterandaskyouquestionsaboutyour
callcentertechnology.
PleaseTakeour22KPIBenchmarkingSurveyFollowedbytheCiscoSponsoredTechnology
&PerformanceSurvey:[invite("surveylink")]
OncecompletedyoucouldeitherreͲvisitthesurveylinkabovetoinputdata,eͲmailto
[email protected],orfaxto805Ͳ618Ͳ1557.
Thankyouverymuchforyourparticipation.
BruceBelfiore,CEO
BenchmarkPortal,LLC.&
SeniorResearchExecutive
CenterforCustomerͲDrivenQuality
ThankYou!
͸Ͷ
Ͷ͹
Copyright © 2012 BenchmarkPortal, LLC.
SurveyQuestionnaire:
ContactCenterPerformance
1.
Howmanyinboundcallsperyeararedirectedtoyourcallcenter?
2.
Callsofferedannually
(Callsofferedisthetotalnumberofcallsyoureceiveina
givenyear.ThisnumberisprovidedbyyourACD.)
Oftheinboundcallsdirectedtoyourcallcenter,howmanyarehandledbyaliveagentand/oryourIVR?
3.
Callshandledannually
(Thesearethetotalnumberofuniqueinboundcalls
receivedinagivenyearbythecenterthatarecompletedby
aliveagent,plusthosecompletedbyyourIVR.Thevalue
forcallshandledmustbeequalto,orlessthancallsoffered,
andshouldbeapproximatetothevalueofcallsofferedless
thoseabandoned.Thisnumberisoftenprovidedbyyour
ACD.)
Ofallthecallshandledannuallybyyourcenter,howmanyarehandledbyeachofthefollowingtwocategories?
Annualcallvolumehandledbyyouragents
AnnualcallvolumehandledcompletelybyyourIVR
4.
Ofthecallshandledannuallybyyouragentshowdotheybreakdowninthefollowingtwocategories?
(Thesearethetotalnumberofuniqueinboundcalls
receivedinagivenyearbythecenterthatarecompletedby
aliveagent.Thesumofthisvalue,whenaddedtothesum
ofcallshandledbytheIVR,shouldequalthevalueforcalls
handledbythecenter.Thisnumberisoftenprovidedby
yourACD.)
(Thesearethetotalnumberofuniqueinboundcalls
receivedinagivenyearbythecenterthatarecompletedby
yourIVR.Thesumofthisvalue,whenaddedtothesumof
callshandledbyagents,shouldequalthevalueforcalls
handledbythecenter.Thisnumberisoftenprovidedby
yourACD.)
Businesstobusiness
%
Thisisthepercentageofcallsexchangedwithother
businessesasopposedtoendͲuser(private)callers.)
Consumertobusiness
%
(ThisisthepercentageofcallsexchangedwithendͲuser
(private)callersasopposedtocallsfrombusinesses.)
Total100%
͸Ͷ
Ͷͺ
Copyright © 2012 BenchmarkPortal, LLC.
5.
Howmanyagentsworkatyourcallcenter?
FullͲtimeagents_____
PartͲtimeagents_____
6.
HowmanyFullTimeEquivalentagents(FTE)workatyourcallcenter?
FullͲTimeEquivalents(FTEs)_____
(Thisisanoperationsandworkforcemetricthatshowsthe
amountoflaborusedintermsoffullͲtimeworkforce.Itis
derivedbyaddingthecumulativesumoflaborhoursfor
bothfullͲtimeandpartͲtimeemployeesforaspecified
periodanddividingitssumby40.
TotalFTE’s=(totalaveragehoursoffullͲtimeagents+total
averagehoursofpartͲtimeagents)/40
7.
Areyouragentsrepresentedbyalaborunion
(AfullͲtimeagentisconsideredasonewhoworks40hours
ormoreperweek,orwhateverequivalentusedbyyour
center.Insomecases,fullͲtimeagentsarecountedat36
hourperweek.Asthisisanoperationalmetric,thespecific
hoursworkedislessasimportantthanthenumbersof
agentsworkinginthecapacityofafullͲtimeagent.)
(APartͲtimeagentisonewhoworksapartͲtimeschedule
oflessthan36hoursperweekorwhateverequivalentpartͲ
timecapisusedbyyourcenter.Insomecases,partͲtime
agentsarecountedasagentsthatdonotworkmorethan
36hourperweek.Asthisisanoperationalmetric,the
specifichoursworkedislessasimportantthanthenumbers
ofagentsworkinginthecapacityofapartͲtimeagent.)
Yes_____
No_____
(Alegallyrecognizedprofessionalbodyorganized
forthepurposeofsupportingtheneedsofits
membersthroughthecollectivebargainingof
wages,benefits,andworkingconditions.)
8.
Ifyouragentsdomorethanjustanswerinboundcalls,whatotherfunctionsdotheyperform?
AgentFunctions
OutboundCalls
%
RespondtoEͲmails
%
RespondtoOnͲlineWebͲchats
%
Other
%
AveragePercentageofAgentTime
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Ͷͻ
Copyright © 2012 BenchmarkPortal, LLC.
9.
Whichofthefollowingtypesofcallsdoyouragentshandleasapercentageoftheirtotalcallshandled?
CustomerService
%
(Providingcallerswithquickandaccurateanswersto
theirquestions,and/orloggingandupdatingcustomer
information.)
OrderTakingandOrderTracking
TechnicalSupporttoExternalCustomers
Complaints
ReͲdirectingInboundCalls
Others
10.
Whatisthetotalannualbudgetforyourcallcenterforthisyear?
(Fillintheannualoperatingbudgetallocatedforyourcallcenterforthis
year.Theannualcallcenterbudgetisthetotalannualdollaramount
allocatedforallexpensesassociatedwiththeoperationofthecallcenter
forwhichthecallcentermanagerisaccountable.Theannualbudget
shouldincludeallfullyloadeddirectandindirectcostsforbudgetaryline
itemssuchaslabor,benefits,andincentivesforagents,management,
training,andsupportpersonnel;HRcosts(e.g.,recruiting,screening,
training);telephonyexpenses(toll,trunks,equipment);technology
purchases/installation(hardware,andsoftware);technology
maintenance(hardware,andsoftware)network;furniture,fixtures,
decorations,etc.;utilities(gas,water,power,UPSbackup);maintenance
(repair,janitorial,upkeep);supplies;overheadexpensesandchargeͲbacks
forsharedcorporatecosts(e.g.,legal,riskmanagement,payroll
administration,ITsupport,security,accounting,groundskeeping,real
estate,floorspace,commonareas,etc.)asapplicable.)
%
TotalFTE’s=(totalaveragehoursoffullͲtimeagents+total
averagehoursofpartͲtimeagents)/40
%
(Takingandtrackingordersforproductsand/orservices.)
%
(Handlingcustomercomplaints.)
%
(Routingcallerstonextavailablespecialist.)
%
(Fillinthepercentageofcallshandledthatareofatype
otherthananyoftheoptionsprovidedabove.)
11.
Howdoyoucompensateyouragents?
SumofpercentagesmustTotal100%
$
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ͷͲ
Copyright © 2012 BenchmarkPortal, LLC.
AveragehourlywageforfrontͲlineagents
$
AveragehourlystartingwageforfrontͲlineagents
$
12.
Whatisyouraveragecostpercallindollars?
13.
Overthepast12consecutivemonths,whatwereyouraverageinboundperformancetimeͲbasedmetrics?
a
.
b
.
Averagespeedofanswer(ASA)inseconds
c
.
Averagetalktime(ATT)inminutes(includesholdtime)
d
.
Averageaftercallworktime(ACWT)inminutes
e
.
Averagetimeinqueueinseconds
(Thisisthesumofallcostsforrunningthecallcenter(refertodefinition
forannualbudgetinquestion11)fortheperiod,dividedbythenumberof
callshandledinthecallcenterforthesameperiod.Thiswouldincludeall
callswhetherhandledbyanagentorbytheIVR.)
$
80%ofyourcallsareansweredinhowmanyseconds
(Thisisaproductivitymeasurementoftheaveragetimein
secondsitrequiresforthecentertoanswer80%ofitscalls
offered.Thisdiffersfromstandardservicelevel
measurementsthatsetagoalintimetowhichthecenter
shallattempttohandleaprescribedvolumeofcallswithin.
Usethefollowingformulatocalculatethisvalue:LetX=
yourserviceleveltime;letY=yourservicelevelpercentage;
S=thetimeinwhich80%ofcallsareanswered.S=(X*
.80)/Y).Forexample,ifyouanswer93%ofyourcallsin20
secondstheresultsareasfollows:S=(20*.80)/.93=17.20
seconds.)
(Thisisthetotalanswertime(ringtimeandqueuetime)
dividedbythetotalnumberofcallsansweredduringthe
targetperiod.ThisvalueisoftenprovidedbyyourACD)
(Thisisthesumtotalofagentstimeintalkmodedividedby
thetotalnumberofcallshandledbyagents.)
Thisisthesumamountoftimeagentsspendonperforming
followͲupworkaftertheagenthasdisconnectedfromthe
caller,dividedbythetotalnumberofcallshandledby
agents.Thedataforaftercallworktimeistakenfromthe
ACDandshouldbecalculatedbyindividualandgroup,
daily,weekly,andmonthly.MostACDsystemsprovidethis
number.)
͸Ͷ
ͷͳ
Copyright © 2012 BenchmarkPortal, LLC.
(Thisistheaveragewaittimethatacallerendureswaiting
foranagenttoanswerthetelephoneafterbeingplacedin
thequeuebytheACD.Thisdiffersfromaveragespeedof
answerbecausethiscalculationincludesonlycallsthat
actuallyhadawaittime.Thismetricisalsoknownas
averagetimeofdelay.MostACDsystemsprovidethis
number.)
f
.
Averagecallerholdtimeinsecondswhileonthephonewithan
agent
14.
Overthepast12consecutivemonths,whatwereyouraverageinboundperformancepercentageͲbasedmetrics?
a
.
Averageabandonedinpercent
b
.
Callsresolvedonfirstcallinpercent
(Thecumulativesumtotalofallholdtime,dividedbythe
numberofcallsplacedonholdfortheperiodmeasured.
MostACDsystemsprovidethisnumber.)
c
.
AgentOccupancyinpercent
d
.
Adherencetoscheduleinpercent
e
.
Averageattendanceinpercent
%
(Thisisthepercentageofcallsthatwerecompletely
resolvedduringthecourseofthefirstinboundcallinitiated
bythecustomer,andthereforedonotrequireacallback.)
%
(Thisisthepercentageofcallsthatwereconnectedtothe
ACD,butweredisconnectedbythecallerbeforereaching
anagent,orbeforecompletingaprocesswithintheIVR.)
%
(ThisisthetotalstaffedtimeloggedintotheACD
(includingready/available,engagedoncall,inACW,in
AUX,orotheractivestates),dividedbythetotalscheduled
hoursatwork.)
%
(Thispercentagerepresentshowcloselyanagentadheres
tohis/herdetailedworkscheduleasprovidedbythe
workforcemanagementsystem.100%adherencemeans
thattheagentwasexactlywheretheyweresupposedtobe
atthetimeprojectedintheirschedule.Thescheduledtime
allowsformeetingswiththesupervisor,education,plus
answeringcustomerphonecalls,eͲmails,&chats.)
%
(Thisisapercentagerepresentinghowoftenanagentis
NOTabsentfromworkduetoanunplannedabsence(not
͸Ͷ
ͷʹ
Copyright © 2012 BenchmarkPortal, LLC.
toincludeexcusedabsences,i.e.,vacation,FMLA,juryduty,
etc.).Takethetotalnumberofunexcusedabsencesand
divideitbythetotalnumberofdaysthattheagentwas
expectedtobeatwork,andsubtractthatnumberfrom
100.)
f
.
Averagecallstransferredinpercent
g
.
AverageAuxiliary(Aux)Timeinpercent
h
.
AverageUtilizationinpercent
%
(Thisistheaverageamountoftimepershift,inpercent,
thatanagentisloggedintoanAuxstate.Thisshould
includeallauthorizedoffͲlinetime,i.e.timesetasidefor
handlingeͲmails,training,orotherjobͲrelatedtasks.)
%
(Agentutilizationisacalculatedmetricreflectingthe
percentageofanagent’sshiftwheretheagentislogged
intothesystem,engagedinactive“telephonemode”which
involves“talktime(ATT)”,“holdtime(AHT)”,and“afterͲ
callͲworktime(ACWT).”Utilizationequalstheproductof
averagecallhandletime(talktime+holdtime+aftercall
worktime)andtheaveragenumberofinboundcallsper
Agentpershift(ACPS),dividedbytotaltimetheAgentis
connectedtotheACDandreadytohandlecallsduringa
shift,i.e.,occupancyinminutes.)
(
ATT ACW ACPS ) X 100
Occupancy _ in _ min .
15.
Whatistheaveragenumberofcallsthatanagenthandlesperhour?
16.
Whatistheaveragenumberofshiftsperyearworkedbyyouragents?
%
(Thetotalnumberofcallstransferredbyagents(dueto
theirinabilitytoproperlyhandlethecall–forwhatever
reason),dividedbythetotalnumberofuniquecalls
handledbyagents.Thiswouldnotincludevoluntary
transferstootherdepartmentsafterresolutionoccursfor
theinitialcallreason.)
Utilization
(Thetotalnumberofcallshandledperagentpershift
dividedbythetotalhoursworked.)
(Onaverage,afullͲtimeagentworksapproximately250
shiftsperyear;however,thenumberofshiftsworkedby
partͲtimeagentsmayactuallybemoreorlessthanthis
dependingupontheaveragelengthofshiftsandnumbers
ofshiftsworkedperday.Thismayalsobeinterpretedas
theaveragenumberoftimesthatanagentreportsto
͸Ͷ
ͷ͵
Copyright © 2012 BenchmarkPortal, LLC.
work.)
FullͲTimeagents_____
PartͲTimeagents_____
17.
Whatistheaverageshiftlengthinminutesofyouragents?
(PleaseprovidescheduledworkͲtimeminutesonly.Donot
includelunch.Forexample480minutes–30minutesfor
lunch=450workͲtimeminutes.)
FullͲTimeagents_____
PartͲTimeagents_____
18.
Doesyourcallcenterhaveaformalprocesstocollectthecaller’ssatisfactionregardingtheirexperiencewithhow
theircallwashandled?
Yes_____
No_____
19.
Onaverage,inthepast90dayswhatpercentageofyourcallersgaveyouaperfectscoreonthequestion,“Overall,
howsatisfiedwereyouwiththeserviceyoureceivedduringyourcalltoourcenter?”
(Byformalprocess,wemeananestablished
routineprocessofgatheringcustomer
feedbackregardingtheirrecentcalling
experience,suchasafterͲcallIVRsurveys,
followͲupoutbound(liveagent)calls,followͲup
eͲmailsurveys,etc.)
(A“highest”scoreof5outof5,orthetopofwhatever
scaleyouuse.)
20.
Onaverage,inthepast90days,whatpercentageofyourcallersgaveyouthelowestscoreonthequestion,
“Overall,howsatisfiedwereyouwiththeserviceyoureceivedduringyourcalltoourcompany?”
%
21.
Doesyourcallcenterhaveaformalmechanismforgatheringagentfeedback?
Yes_____
No_____
(A“lowest”scoreof1outof5,orthetopofwhateverscale
youuse.)
%
(Byformalprocess,wemeananestablishedroutineprocess
ofgatheringcustomerfeedbackregardingtheirrecent
͸Ͷ
ͷͶ
Copyright © 2012 BenchmarkPortal, LLC.
callingexperience,suchasafterͲcallIVRsurveys,followͲup
outbound(liveagent)calls,followͲupeͲmailsurveys,etc.)
22.
Onaverage,inthepast90days,whatpercentageofyouragentsgaveyouaperfectscoreonthequestion,“Overall,
howsatisfiedareyouwithyourposition?”
(A“highest”scoreof5outof5,orthetopofwhatever
scaleyouuse.)
%
23.
Onaverage,inthepast90days,whatpercentageofyouragentsgaveyouthelowestscoreonthequestion,
“Overall,howsatisfiedareyouwithyourposition?”
(A“lowest”scoreof1outof5,orthetopofwhateverscale
youuse.)
%
24.
Whatistheratioofagentstosupervisors(spanofcontrol)?
Agentspersupervisor
25.
WhatistheannualpercentageturnoverofyourfullͲtimeagents?
26.
HowdoesyourtotalannualfullͲtimeagentturnover(Question26above),howdoesthisbreakdownintothe
followingtwocategories(bypercentage)?
#
(Totalagentheadcountdividedbytotalnumberof
supervisors,roundedtonearestwholevalue.)
(PleaserefertoAppendixBforguidelinesandtheformula
tocalculatetheannualpercentageofturnoverofyourfullͲ
timeagents.)
%
Promotionalturnover
%
(Thisistheturnovercausedbypromotionswithinthecall
centerfrom“agent”tosomeotherpositioninthecall
center,and/orpromotionswhereagentsgotoother
departmentswithinthecompany.)
AllOtherTurnover
%
(Thisisallotherturnovernotrelatedtopromotions,
butrelatedtoandincludingvoluntaryand
involuntarytermination.)
SumofpercentagesmustTotal100%
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ͷͷ
Copyright © 2012 BenchmarkPortal, LLC.
ContactCenterPerformance–AlternateContactChannels
27. ForyourinboundEmailcontactchannel,whatisyourcurrentaverageforthefollowingKeyPerformance
Indicators?
DescriptionOfAnswer
Average
AverageannualvolumeofEmailshandled
AverageresponsetimeINHOURS(usedecimalifnecessary)
Averageoverallprocessingtime,INMINUTES(usedecimalifnecessary)
AverageFirstͲContactResolutionRateinpercent
%
UpͲsell/CrossͲsellCloseRateforEmailsinpercent
%
AveragecostperEmailin$US(useUSdollars&cents)
28. ForyourWebChatcontactchannel,whatisyourcurrentaverageforthefollowingKeyPerformanceIndicators?
DescriptionOfAnswer
Average
AverageannualvolumeofWebChatshandled
AveragespeedofanswerINSECONDS(usedecimalifnecessary)
AveragechatsessiontimeINMINUTES(usedecimalifnecessary)
AverageFirstͲContactResolutionRateinpercent
%
UpͲsell/CrossͲsellCloseRateforWebChatsinpercent
%
AveragecostperWebChatin$US(useUSdollars&cents)
͸Ͷ
ͷ͸
Copyright © 2012 BenchmarkPortal, LLC.
InstalledTechnology
Software/
HardwareType
Have?
(Y/N)
Definition
Vendor
Model/Version/
Release
PBX
PublicBusiness(orBranch)eXchange:atelephone
switchingdeviceownedbyaprivatecompanyvs.
oneownedbyacommoncarrier.
ACD
AutomaticCallDistributor:adeviceusedtomanage
anddistributeincomingcallstoaspecificgroupof
terminals(agents).
IVRprovidesselfͲserviceoptionstocallersviamenu
choicesselectedwithkeysonatouchͲtone
(TouchͲtone)IVRtelephonesystem.
Technologythatidentifiesthecaller’sidentityusing
ANI/DNISfor
automaticnumberidentification(ANI)ordirect
CustomerID
numberidentificationsystem(DNIS).
EnhancedIVRthatprovidesserviceoptionstocallers
viaspokenmenuchoicesandiscoupledwithspeech
recognitiontechnologytorecognizespoken
responsesfromthecaller.
Technologydesignedtouseinterpretedhuman
speechthatenablespeopletointeractwithanatural
languageIVR.
Personalized AVRUthatdeliversapersonalizedmessagebased
VRU
upontheidentityofthecaller.
EͲmail
Management Providestrackingandroutingofemail.
System
Technologythatofferscustomers&prospectsan
EͲmailResponse
alternatecontactchannelforcommunicatingwitha
System
customerservicecontactcenter.
WebContact
Technologythatenablescustomers&prospectsthe
Chat
abilitytodirectlycommunicatewithaliveagentby
keyboardviaachatlinkfromthewebsite.
DTMF
Natural
Language
IVR
Speech
Recognition
͸Ͷ
ͷ͹
Copyright © 2012 BenchmarkPortal, LLC.
Software/
HardwareType
Have?
(Y/N)
Definition
AsetoftollͲfreetrunkswhichallowcallersto
SeparateTollͲ
directlycallintoaspecificdepartment;alsousedfor
FreeNumbers
highͲvaluecustomers.
Vendor
Model/Version/
Release
AprogrammableformofSkillsBasedRouting
ValueBased targetedatCustomerValuewherecustomersare
Routing
rankedinvalueandtheircallsaredirectedto
designatedagents.
Theabilitytorouteacustomertoaspecificagent
PreͲRoutingto
withspecializedskills(i.e.English,Spanish,etc.)by
ACDs
havingthecustomerpressinganumericoption.
Anadvancedroutingtechnologythatroutescallsto
Routingacross
thenextͲavailableͲagentthroughnetworkedcall
ACDs
centers.
Theabilitytorouteallchannelsofinquiries(email,
BlendedRouting chat,phone)toablendedagent.Thishelpsanagent
tobefullyutilizedandefficientwiththeirtime.
Theabilitytoroutethecustomertoanotherservice.
Routingbeyond Thisisanotherrevenuechannelforthecompany.
CallCenter
(i.e.SouthwestAirlinesroutingthecallerstoHertz
forrentalcalls)
Theabilitytoescalateinquirestoanotherchannelof
UnifiedCrossͲ
communication(i.e.fromchattocoͲbrowse,phone
ChannelRouting
call,etc.)
Theabilitytorouteacalltoanagentwiththatisthe
mostcompetentinhandlingthecallbylookingat
theattributesofanagent.(i.e.callercallingfor
Competency
Spanishandthealltheagentsthatareprimary
BasedRouting
Spanishspeakersareoccupied.Thecallwillget
routedtothenextagentthatspeaksSpanishasher
secondarylanguageversusherfirst.
Theabilitytoroutebasedonmulticriteria.(i.e.call
MultiͲCriteria
callingforcable,internet,andphoneservice.This
Routing
callisroutedtoanagentthatcanserveallthree.)
SkillsBased
Routing
Technologyenablingtheroutingofcallstoagents
assignedaparticularskillorsetofskills.Acommon
componentofmostACDsystems
͸Ͷ
ͷͺ
Copyright © 2012 BenchmarkPortal, LLC.
Software/
HardwareType
Have?
(Y/N)
Definition
NoQueue,Hunt
Thisistheabilitytoringallphonesatthesametime.
Group
Vendor
Model/Version/
Release
Acallqueuingsystemthatisincludedasa
componentoftheACD.
Technologythatplaysmusictocallersinthehold
queue.
Technologythatpresentstheoptiontocallersinthe
CourtesyCallͲ
holdqueuetohangupwithoutlosingtheirplacein
Backwhilein
queue,andbecalledbackwhentheircallreaches
Queue
thetopofthequeue,ratherthanwaitingonhold.
Technologythatprioritizesthequeuingofcallers
Queue
baseduponthecaller’sidentity,movinghighͲvalue
Prioritization
callerstowardthefrontofthequeue.
CustomerCrossͲ Technologythatplaysrecordedsalesmessagesfor
SellMessage othercompanyproductswhilecallersarewaitingin
whileinQueue theholdqueue.
UniversalMultiͲ Theabilitytointegrateallcontactchannelsintoone
ChannelQueue queuesothattheagentisfullyutilized.
ACDBased
Queue
MusiconHold
Recorded
Messagewhile
Technologythatplaysrecordedmessagestocallers
on
intheholdqueue.
Hold
AnnouncedWait Technologythatintermittentlyannouncesthe
TimeinQueue estimatedwaittimetocallersintheholdqueue.
Virtualized
Enterprise
Queue
Theabilitytoqueuethecallsatacentralized
locationuntilthenextavailableagent(atanysite)
cantakethecall.
͸Ͷ
ͷͻ
Copyright © 2012 BenchmarkPortal, LLC.
Software/
HardwareType
Have?
(Y/N)
Definition
Vendor
Model/Version/
Release
ComputerTelephonyIntegration:thetechnology
AgentDesktop thatenablesthecoordinationandintegrationof
with
computerandtelephonesystems.FunctionsofCTI
include:CallingLineInformationDisplay,Screen
Population(oncallanswer),OnScreenDial,Preview
andPredictiveDial,&OnScreenCallControl
TheabilitytousetheCTItoautomaticallyupdate
datainotherapplications.
TechnologythatautomaticallypopsͲupsalesscripts
ontheagents’monitors.
CustomerRelationshipManagementsystemstrack
CRMDesktop
customerinformationandinteractionswiththe
System
company
Automated
Theabilitytocallbackacustomerthatselectedthe
PersonalCallͲ
callͲbackoptionwhiletheywereinqueue.
Backs
CTI
TheabilityfortheIVRtoprovideselfͲservicetothe
SpeechSynthesis
customerbeforetheygetroutedtoanagentto
Apps
resolvetheissue(i.e.checkingsavingsbalance)
CTI&Apps
Integration
Agent
PopͲUps
forUpͲsell/
CrossͲsell
PresenceͲBased TheabilitytouseanIMclienttoconnectthe
ExpertEscalationcustomertoanexpertinstantly.
SilentCall
Monitoring
Technologythatenablescallcentersupervisorsand
qualitymonitorstocapture,monitor,record,and
evaluatemostcustomer/agentinteractions
AgentTrace
Basictechnologythatpermitstracingofanyagent
actionswhileloggedintotheACD.
Technologythatenablescallcentersupervisorsand
CallRecording& qualitymonitorstocapture,monitor,record,and
Retrieval
evaluatecustomer/agentcallswithouttheagents’or
thecallers’knowledge.
͸Ͷ
͸Ͳ
Copyright © 2012 BenchmarkPortal, LLC.
Software/
HardwareType
Have?
(Y/N)
Definition
ContactData
Reportmanagementsystem
Analytics
Vendor
Model/Version/
Release
RealͲtimeAgent Theabilitytoconsultanagentduringacallviaa
FeedbackTools “whisper”orchatwindowontheagentdesktop.
Theabilitytokeepthecenter’sperformancelevelat
parthroughanalertthatshowsanagentorKPIis
ActionableAlerts
outofcompliance,enablingmanagementto
withSolutions
undertakeappropriateactiontorestore
performancetoanacceptablelevel.
Technologyoftenusedforcallforecastingandagent
schedulingthroughhistoricalcalldata.Other
Workforce functionsofworkforcemanagementmayinclude
Management skillsͲbasedscheduling,scheduleadherence,timeͲ
offadministrations,performancemanagementtools
andreporting.
Gravereportingprovidestheexactchronologyof
CradletoGrave
eachcallonyoursystemfromthemomentthecall
Reporting
hityourphoneswitchtotheinstantthecallended.
Advanced
Reporting&
Analytics
Theabilitytohavedatathatshowtrends(AHT,FCR,
etc.)andalsoenablesadvancedstatisticalanalysis
(correlation,crossͲtab,regression,etc.).
Automated Asystemthatgathersandanalyzescaller
CustomerSurveysatisfactionimmediatelyfollowingthecallviathe
(IVR)
IVR.
EͲmail
Satisfaction
System
AsystemthatgathersandanalyzeseͲmailcustomer
satisfactiontobetterunderstandandserve
customers
͸Ͷ
͸ͳ
Copyright © 2012 BenchmarkPortal, LLC.
APPENDIXEͲABOUTBENCHMARKPORTAL
BenchmarkPortalistheleaderinCallCenterBenchmarking,CallCenterTrainingandCallCenter
Consulting.Sinceitsbeginningsin1995underDr.JonAntonofPurdueUniversity,
BenchmarkPortalhasgrownwiththecontactcenterindustryandnowhoststheworld'slargest
callcentermetricsdatabaseinconjunctionwiththeCenterforCustomerDrivenQuality.
LedbyCEOBruceBelfiore,theBenchmarkPortalteamofprofessionalshasgainedinternational
recognitionforitscallcenterexpertiseandinnovativeapproachestoBestPracticesforthecall
centerindustry.BenchmarkPortal'sactivitiesincludeTheCollegeofCallCenterExcellence,a
leaderincallcentertrainingandcertification,andCallTalk,thefirstonͲlinetalkshowspecifically
focusedonthecallcenterindustry.
BenchmarkPortal'sstatedmissionistohelpcustomercontactmanagersinallsectorstooptimize
theircentersintermsofefficiencyandeffectiveness.
Website:www.BenchmarkPortal.com
͸Ͷ
͸ʹ
Copyright © 2012 BenchmarkPortal, LLC.
APPENDIXFͲABOUTCISCO
AboutCisco
Cisco(NASDAQ:CSCO)istheworldwideleaderinnetworkingthattransformshowpeopleconnect,
communicateandcollaborate.InformationaboutCiscocanbefoundatwww.cisco.com.Forongoing
news,pleasegotonewsroom.cisco.com.
AboutCiscoCollaboration
FromawardͲwinningIPcommunicationstomobility,customercare,Webconferencing,messaging,
enterprisesocialsoftware,andinteroperabletelepresenceexperiences,Ciscobringstogether
networkͲbased,integratedcollaborationsolutionsbasedonopenstandards.Thesesolutionsoffered
acrossonͲpremises,cloudͲbasedorvirtualizedplatforms,aswellasservicesfromCiscoandour
partners,aredesignedtohelppromotebusinessgrowth,innovationandproductivity.Theyarealso
designedtohelpaccelerateteamperformance,protectinvestments,andsimplifytheprocessof
findingtherightpeopleandinformation.InformationaboutCiscoCollaborationcanbefoundat
www.cisco.com/go/collaboration
͸Ͷ
͸͵
Copyright © 2012 BenchmarkPortal, LLC.
Footnotes
i
IntegratingPeoplewithProcessandTechnologybyDr.JonAnton,Dr.NatalieL.PetouhoffandLisaM.
Schwartz,AntonPress,2004.
SeealsoBenchmarkingAtItsBestforContactCentersbyBruceBelfiorewithDr.JonAnton,AntonPress,2004
͸Ͷ
͸Ͷ
Copyright © 2012 BenchmarkPortal, LLC.

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