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Sometimes more web traffic hurts. What happens when more visitors cause poor Web performance? As a marketer, ecommerce manager or IT professional, your responsibility is to maximize online revenue, protect your brand, and ensure customer loyalty by providing consistent quality Web experiences at all times. But did you know that a lack of readiness resulting in poor web performance during peak traffic times significantly impacts your business results? A new survey of retail, travel and financial services online consumers found that customers spend a significant percentage of their budgets during peak traffic times, and 67% expect websites to work well regardless of the number of visitors. Moreover, 72% stated that their expectations were not met during 2009 peak traffic periods, and this is what they did about it: •78% went to a competitor’s site due to poor performance at peak traffic times •88% were less likely to return to a website •47% left with a negative perception of the company •42% discussed it either with friends or online Want to know more about how to protect revenue, brand and customer loyalty during peak traffic periods?
Citation preview
Contents
ExecutiveSummary Pg4‐5
CustomersSpendBigDuringPeakTrafficTimes,andWon’tToleratePoorWebPerformance Pg7‐11
UserExpectationsWereNotMetin2009DuringPeakTrafficPeriods Pg13‐16
PoorExperiencesDuringPeakTrafficTimesDirectlyImpactBusinessResults Pg18‐23
BestPracticesforManagingPeakTrafficTimes Pg25‐26
AppendixI–Methodology Pg28
2
PeakOnlineTrafficPeriodsarecriticalsincemoreWebvisitorsmeanmorerevenueopportunities.Yetwhatareconsumers'expectationsduringpeaktraffictimes,andhowdotheybehavewhentheyexperiencepoorwebperformance?
Tofindout,GomezcommissionedEquationResearchtoconductastudyofconsumerInternetusageexperiencesduringpeaktraffictimes 1,538respondentinterviewswerecarriedoutbetweenDec16–22,2009 Studywasconductedacross3verticals:Retail,TravelandFinancial
ExamplesofPeakTrafficPeriods: HolidayShoppingSeason,Valentine’sDay,Mother’sday,4thofJuly,Summer,TaxSeason,FinancialMarketMeltdowns,BacktoSchoolShopping.Thanksgiving,Xmastoendoftheyear...
Introduction
3
KeyFinding1 Customersspendbigduringpeaktraffictimes,andwon’ttoleratepoorwebperformance 51%spendasignificantpercentageoftheirretailbudgetduringpeaktimes 67%expectwebsitestoworkwellregardlessofhowmanyvisitorsthesitegetsduringpeaktraffictimes
KeyFinding2 Userexpectationswerenotmetduring2009peaktrafficperiods
72%experiencedslowerwebsitesmorefrequentlyduringpeaktraffictimesthanatothertimes
KeyFinding3 Poorexperiencesduringpeaktraffictimesdirectlyimpactbusinessresults
78%wenttoacompetitor’ssiteduetopoorperformanceatpeaktimes Afterapoorexperience…
88%arelesslikelytoreturntoawebsite 47%leftwithanegativeperceptionofthecompany 42%discussediteitherwithfriendsoronline
ExecutiveSummary
4
ExecutiveSummaryAcrossIndustryVerticals
Vertical KeyFindings
Retail
• 51%spendasignificantpercentageoftheirbudgetduringpeaktimes
• 41%wouldabandonaretailer’sWebsiteatpeaktimesandshopsomewhereelseafteronlyoneortwobadexperiences
• 33%hadabadexperienceonaretailWebsitethis2009HolidayShoppingSeason
Travel
• 35%makeasignificantpercentageoftheirtravelbookingsduringpeaktimes
• 53%wouldabandonatravelWebsiteatpeaktraffictimesandbooksomewhereelseafteronlyoneortwobadexperiences
• 24%hadanegativeexperienceonatravelWebsiteduring2009peaktravelseason
FinancialServices
• 51%offinancialserviceusers&65%ofonlinestocktradershadpoorWebexperiencesduringpeakusagetimesin2009
• 42%offinancialserviceusers&57%ofonlinestocktraderswouldswitchtoacompetitorifdissatisfiedwiththeirfinancialprovider’sWebsite
5
Key Finding 1 Customers Spend Big During Peak Traffic
Times and Won’t Tolerate Poor Web Performance
6
51%SpendaSignificantPercentageofTheirRetailBudgetDuringPeakTrafficTimes
9%
40%
37%
14%Most
Asignificantpercentage
Alittle
None
51%
RetailFindings
Figure2:Percentageofretailonlinespendingthatoccursduringpeaktraffictimes
7
35%MakeaSignificantPercentageofTheirTravelBookingsDuringPeakTrafficTimes
TravelFindings
17%
48%
28%
7%Most
Asignificantpercentage
Alittle
None
35%
Figure3:Percentageofonlinetravelbookingsdoneduringpeaktraffictimes
8
67%ofOnlineConsumersExpectWebsitestoWorkWellRegardlessofHowManyVisitorstheSiteGetsDuringPeakTrafficTimes
67%
26%
4%
Iexpectwebsitestoworknomatterhowmanyvisitorstheyhave
Iunderstandthatmorevisitorswillslowwebsitesdown
Nospecificexpectations
Figure4:Onlineconsumers'expectationsduringpeaktraffictimes
Customers are just as demanding during peak traffic times
9
Cross‐VerticalFindings
41%WouldAbandonaRetailer’sWebsiteatPeakTrafficTimes&ShopSomewhereElseAfterOnlyOneorTwoBadExperiences
10%wouldgotoacompetitivesiteafteronlyonebadexperience
10%
31%
33%
11%
6%
10%
None,I'dleaveafterthefirstbadexperience
2
3
4
5ormore
PoorexperienceswillnotimpactthewebsitesIusetoshop
41%
Figure5:Numberofpoorwebexperiencestoleratedduringpeaktraffictimesbeforeshoppingsomewhereelse
RetailFindings
10
• Onlineconsumersarelesstolerantwithtravelsitesthanretailsites• 17%wouldgotoacompetitivesiterightaway
TravelFindings
53%WouldAbandonaTravelWebsiteatPeakTrafficTimes&BookSomewhereElseAfterOnlyOneorTwoBadExperiences
17%
36%
26%
7%
4%
10%
None,I'dleaveafterthefirstbadexperience
2
3
4
5ormore
PoorexperienceswillnotimpactthewebsitesIusefortravel
Figure6:Numberofpoorwebexperiencestoleratedatpeaktraffictimesbeforebookingtravelsomewhereelse
53%
11
Key Finding 2 User Expectations Were Not Met in 2009
During Peak Traffic Periods
12
72%ofOnlineConsumersExperiencedPoorPerformanceMoreFrequentlyDuringPeakTrafficPeriodsthanatOtherTimes
51%
58%
72%
ProblemsCompletingTransactions
ErrorsonWebPages
SlowerWebSites
Figure1:Typeofissuesencounteredmorefrequentlyduring2009peaktrafficperiods
SlowerWebSiteswastheproblemmostcommonlyencountered
13
Cross‐VerticalFindings
33%HadaBadExperienceonaRetailWebsitethis2009HolidayShoppingSeason
15%foundproblemsencounteredduringthe2009HolidayShoppingSeasontobe‘unacceptable’
15%
18%
67%
Yes‐anditisunacceptable
Yes‐butitdoesn'tbotherme
No‐Ihaven'thadabadexperience
33% Had a bad experience?
Figure8:PoorwebexperiencesencounteredonaretailWebsitethis2009HolidayShoppingSeason
RetailFindings
14
24%HadaNegativeExperienceonaTravelWebsiteDuring2009PeakTravelSeason
Slowloadtimewasthemostfrequentlycitedissueat18%
18%
11%
10%
1%
Slowloadtime
Problemscompletingtransactions
Errorsonwebpages
Other(specify)
Figure9:PoorExperiencesEncounteredonTravelWebsitesDuring2009PeakTrafficTimes(SummerandThanksgiving/Decemberseasons)
TravelFindings
24%
76%
Yes
No
Had a bad experience?
15
51%ofFinancialServiceUsers&65%ofOnlineStockTradersHadPoorWebExperiencesDuringPeakUsageTimesin2009
43%
23%
20%
2%
Slowloadtime
Problemscompletingtransactions
Errorsonwebpages
Other(specify)
58%
28%
31%
1%
Slowloadtime
Problemscompletingtransactions
Errorsonwebpages
Other(specify)
Figure10:PoorExperiencesEncounteredonaFinancialWebsiteDuring2009PeakUsageTimes
FinancialFindings
51% financial service users reported these problems
65% online traders reported these problems
Slowloadtimewastheproblemmostcommonlyencountered
16
Key Finding 3 Poor Experiences During Peak Traffic
Times Directly Impact Business Results
17
• 78%havegonetoacompetitor’ssiteduetopoorperformanceatpeaktimes
Afterapoorexperience..
• 88%arelesslikelytoreturntoasite• 47%leftwithalesspositiveperceptionofthecompany
• 42%havediscusseditwithfamily,friends,peersoronline
PoorWebExperiencesDuringPeakTrafficTimesDirectlyImpactBusinessResults
Brand
CustomerLoyalty
Poorwebexperiencesimpactsrevenue,brand&loyalty
18
Cross‐VerticalFindings
78%HaveGonetoaCompetitiveSiteBecauseofPoorPerformanceDuringPeakTrafficTimes
30%havegonetoacompetitivesiterightawayduetopoorperformanceduringpeaktrafficperiods
22%
48%
30%Yes‐Ihavelittlepatienceforpoorwebsiteperformance
Yes‐butonlyafterseveralbadexperiences
Noimpact
78%
Figure11:PercentageofconsumersthatswitchedtoacompetitiveWebsiteafterapoorWebexperienceduringpeaktraffictimes
19
Cross‐VerticalFindings
88%AreLessLikelytoReturnAfteraPoorWebExperience
28%haveverylittletoleranceforpoorperformanceandarelesslikelytogivethewebsiteanotherchance
13%
60%
28%I'mlesslikelytoreturn‐Ihavelittlepatienceforpoorwebsiteperformance
I'mlesslikelytoreturn‐butonlyafterseveralbadexperiences
Noimpact
Figure12:PercentageofconsumerslesslikelytoreturnafterapoorWebexperience
88%
20
Cross‐VerticalFindings
AfteraPoorWebExperience,47%LeftwithaNegativePerception
47%
34%
8%
Leftwithalesspositiveperceptionofthecompany
Toldfriends,familyorcolleaguesabouttheexperience
WroteabouttheexperienceonFacebook,Twitter,ablogora
forum
Figure12:Impactonbrand&actionstakenafterapoorWebexperience
42%
42% Discussed poor experiences either with friends or online
21
Cross‐VerticalFindings
52%ofFinancialServiceUsersand68%ofOnlineStockTradersTookSomeNegativeActionasaResultofaBadWebExperience
29%
17%
13%
7%
Lesslikelytopurchaseadditionalservicesfromthem
Tellmyfriends/family/peersorwriteaboutitonthe
Internet
Useanotherfinancialprovider'ssite
Closemyaccount
40%
29%
27%
14%
Lesslikelytopurchaseadditionalservicesfrom
them
Tellmyfriends/family/peersorwriteaboutitonthe
Internet
Useanotherfinancialprovider'ssite
Closemyaccount
FinancialFindings
Figure13:Actionstakenasaresultofpoorfinancialwebsiteexperiences
52% financial service users took these actions after a poor Web experience
68% online stock traders took these actions after a poor Web experience
22
42%ofFinancialServiceUsers&57%ofOnlineStockTradersWouldSwitchtoaCompetitorifDissatisfiedWithTheirFinancialProvider’sWebsite
42%
58%
Yes
No 57%
43%
Financial Service Users Online Stock Traders
Figure14:WouldSwitchtoacompetitorasaresultofabadexperienceonafinancialprovider’sWebsite
FinancialFindings
23
Best Practices for Managing Peak Traffic Times
24
25
BestPracticesforManagingPeakTrafficTimes
LoadTestingistheonlywaytoknowhowanapplicationwillperformunderpeaktrafficconditions:
• End‐UserExperience:WillweprovidequalityuserexperienceswhenwehavemoreWebsitevisitors,orwillcustomersencountermoreWeberrorsorproblemscompletingtransactions?
• WebPerformance:Willthewebsiterespondfastenough?
• Scalability:Willtheapplicationhandletheexpecteduserloadandbeyond? –beforeitgets“slow”? –beforeitstopsworking? –willitsustain?
• Stability:Istheapplicationstableunderexpectedandunexpecteduserloads?Whatif….
–therearemoreusersthanweexpect? –alltheusersdothesamething? –wegettoomanyorders?25
26
Best Practices for Managing Peak Traffic Times (Cont’d)
1. Getready‐plantoloadtestwheneverthereisachange Launchingmarketingandsalescampaigns RollingoutnewWebsites,applicationsandfeatures
Planningforseasonalandholidayspikesinwebtraffic Upgradingorvirtualizinginfrastructures
2. Adoptan“outside‐in”customerpointofview
Test&monitoryourwebperformancefromtheInternet,whereyourcustomersare
Focusonkeygeographies(newmarkets,mostvisitors,toprevenue‐generatingregions,…)
3. EnsurethatyourbusinessgoalsaresupportedbyIT Discussupcomingplans&eventswithyourITcounterparts
26
Appendix
27
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DesignandMethodology
Overview
• GomezInc.engagedEquationResearchtoconductanonlinestudytounderstandconsumerInternetusageexperienceduringpeaktraffictimes
• InterviewsconductedfromDecember16‐22,2009
Methodology
• RespondentsrecruitedfromEquation’snationallyrepresentativepanel
• Surveyresultsmayhaveamarginoferrorofplusorminusthreepercentata95percentlevelofconfidence
Sample:1,538totalrespondents• N=500respondentswhohaveboughtaproductorserviceonlineinthepast9months• N=506respondentswhohavebookedtravelinthepast9months
• N=532respondentswhohaveperformedafinancialtransactioninthepast9months(includingn=183respondentswhobought/soldstockonline)
28