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HowtoDesignProductsthatleadtoLong-TermBehavioralChange
SunilMaulik,[email protected]
www.sunilm1.biz
“T-Shaped”ApproachToMyCareer.Deepinscienceforthefirstfifteenyears:
• B.Sc.’sPhysics&Biology,KingsCollege.(MauriceWilkins,NobelLaureate.)
• M.Sc.X-RayCrystallography,Birkbeck College.(SirTomBlundell.)
• Ph.D.Biophysics,BrandeisUniversity(DonaldCaspar&AaronKlug,NobelLaureate.)
Broad forthepastfifteenyears:Sales,Marketing,BusinessDevelopment,Product-MarketFit,Design:
• MiningDataforActionableInsights• Iterating&RefiningHypotheses(“Models”)• ChangingBehaviorsWithImprovedModels
AboutMe:
EachShiftinComputingUnlocksOpportunitiesforInnovationinNewDisciplines
WhyWeBehaveTheWayWeDo
OurSystem1 &System2Minds
“ThinkingFast&Slow”-DanielKahnemann
BasicNeuroscience:
Weight:3lbsO2 consumption:25%oftotalO2CaloricConsumption:20%oftotalcaloriesPowerRequirement:12WCapillaries:400milesNo.ofNeurons:86billionNo.ofConnections:5x1014 (500trillion)Calculations/s:1016 (10quadrillion)No.ActionPotentials/s:17.2x1012 (17.2trillion)SensoryProcessing:40millionbits/sCognitiveProcessing:8000bits/sConscious/SubconsciousProcessing:0.02%!
ExamplesofSystem1 Thinking
•Orienttothesourceofasuddensound.•Completethephrase“breadand...”•Detecthostilityinavoice.•Understandsimplesentences.
ExamplesofSystem2 Thinking
• Focusonthevoiceofaparticularpersoninacrowdedandnoisyroom.•Maintainafasterwalkingspeedthanisnaturalforyou.• Filloutataxform.•Calculate247x183inyourhead
“Theintuitivemindisasacredgiftandtherationalmindisafaithfulservant.Wehavecreatedasocietythathonorstheservantbuthasforgottenthegift.”– AlbertEinstein.
HowWeMakeMostOfOurDecisions
• Mostofthetime,wearenotconsciouslydecidingwhattodonext.• Weoftenactbasedonhabits.• Weoftenmakeintuitive,immediatedecisions basedonpastexperiences.• Whenconsciouslythinking,weoftenavoidhardwork.Weoften“wingit”withroughguesses.• Welooktootherpeople,especiallypeersandexperts.
• ExcessiveOptimism• Overconfidence• ConfirmationBias• Anchoring• Groupthink• Egocentrism• LossAversion• Sunk-costfallacy• Escalationofcommitment• Controllabilitybias• Statusquobias• Presentbias
MakingBetterDecisions:UnconsciousBiases
StudentsprimedwithwordsaboutFloridawalkedslowerthanstudentsprimedwithwordsaboutNewYork.
[Areminderofafeatureteesupbehaviorsreminiscentofthatfeature.]
Priming:
Anchoring:
Shoppersshowed$10,$30and$149bottlesofwineboughtthe$30bottlemoreoftenthanifjustshownthe$10and$30bottles.
[Behaviorsclusteraroundacomparisontosupposed”norms”.]
Framing:
Withasign“limit12percustomer”forsoupcans,peopletake5onaverageratherthan2.
[Decisionsgetframedaroundalinguisticconcept.]
LossAversion:
Traderssellsharesthathavebeengoingupsoonerthansharesthathavebeengoingdown.
[Behaviorstypicallyminimizelossratherthanmaximizegain.]
HabitDesign
“Nevertrustanoverweighthabitdesigner.”– Nir Eyal
Habits:Behaviorsdonewithlittleconsciousthought
“ThePowerofHabit”CharlesDuhigg.
Howdoweturndecisions intohabits?
PersuasiveTechnology
Behavior=Motivation+Ability+Trigger
HookModelofHabitFormationHookModelofHabitDesign
ImplementingtheHookModelImplementing“TheHook”
ExternalTriggers:
Cuesthattelltheuserwhattodonext:• Abutton(clicktoTweet,playorstart)
• Aflashinglightorsound• Aprogress-barorcompletionchart
InternalTriggers:
Internaltriggersareemotions thatweassociatewithanactivity:• Whenwe’relonely,wecheckFacebook
• Whenwe’reuncertain,wecheckGoogle
• Whenwe’rebored,wecheckYouTubeorPinterest
UsingTriggersforBehaviorChange
• Removeuserworkwhereverpossible• Automatetheactionbehindthescenes• Initiatewithameaningful trigger• Provideanimmediate,variablereward• Askforsomeinvestment fromtheuser• Buildnewbehaviorsontopofexistingones.
Behavioral“Lenses”thatTriggerBetterDecisions
"Whatpeoplesay,whatpeopledo,andwhatpeoplesaytheydoareverydifferentthings."- MargaretMead
ArchitecturalLens:Positioning
Positioningpedestrian-crossingpush-buttonunitsatananglemakesitmorelikelythatpedestrianswillturntolookatoncomingtraffic.
Error-ProofingLens:Interlock
ModernATMMachineswon’tdispensecashuntilafteryouremoveyourcard,makingitlesslikelythatyou’llleaveitbehind.(Changedwithnewchip-cards,however!)
InteractionLens:Feedforward/Simulation
savings&loansimulators caninfluenceusers’futurebehavioranddecisions.
Ludic(Playful)Lens:UnpredictableReinforcement
Providingvariable,unpredictably-timedrewardsleadstogreaterconsistencywhenchangingpeople’sbehaviors
PerceptualLens:Transparency
Dyson’stransparentdustcontainerbothdemonstratesthevaccumcleaner’seffectivenessandencouragesuserstoemptyitmoreoften.
PerceptualLens:PerceivedAffordances
Reshapingtheholesontrashbinstomatchthe‘form’ofdifferenttypesofwasteincreasesrecycling.
CognitiveLens:SocialProof
Amazon’srecommendationscanhelpbuyersexpandtheirbuyingdecisions,whilesubtlypressurizingthemtoconformtosocialnorms.
MakingProducts“Scale”intotheirTargetMarkets
“Topredictthebehaviorofordinarypeopleinadvance,youonlyhavetoassumethattheywillalwaystrytoescapeadisagreeablesituationwiththesmallestpossibleexpenditureofintelligence.” - FriedrichNietzsche
Scale:Creatingmassbehaviorchange
• Dynamicallyadjustdata/contentshowntousersbasedonsuccessofpastcontent.
• Explorenewcontentwithanewtargetminority ofusers.
• Addnewcontentifitissuccessfulatelicitingthedesiredbehaviorinthenewtargetmarket.
Scaling:Habittestingforscale
• Identifyareaswherecyclingthroughthehabit-modelbecomesfaster,morefrequent,ormorerewarding.
• Identifynascentbehaviors.Thesearenewbehaviorsthatmayfulfilamass-market need.
• Createnewtriggersthatstimulatethesebehaviors.
Scaling:Makescalingcontagious
• Identifysocialcurrency,suchasremarkability,scarcityorexclusivity.Createanemotionalresponse;eitherawe,anxietyor arousal.
• Enablesocialdisplay e.g.“behavioralresidue”–tracesoftheproductorservice.
• Allowforstorytelling – givetheusereveryopportunitytorelatetheirexperience
Examples:
InConclusion…
“Theonlywayofdiscoveringthelimitsofthepossibleistoventurealittlewaypastthemintotheimpossible.”– ArthurC.Clarke
NeedHelpDesigningYourProducts?– SeeMe!
ThankYou