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Tr@Ins2 User Studies   Tom Evens
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Tr@Ins2 User Studies Tom Evens

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  • 1. User studies Tom Evens IBBT – MICT – UGent
  • 2. Objectives  Predict market adoption potential  Forecast adoption segmentation  Profiling adopter segments  Socio-demographics  Willingness to pay  Drivers and thresholds  Needs and wants … 2
  • 3. Methodology  Electronic survey (www.internetopdetrein.be)  Promoted via  Metro  Bond van Trein-, Tram- en Busgebruikers (BTTB)  UGent  Digimedia  ZDNet  1324 cases were filled in  After cleaning: 964 relevant cases 3
  • 4. Methodology (2)  By means of Product Specific Adoption Potential  Identifying user needs and wants  Predicting adoption potential  Essential input for:  Development business model  Deployment network architecture  Set up introduction strategies 4
  • 5. Product Specific Adoption Potential (PSAP)  Target: offering added value services  Question: which added value to whom?  Answer: segmentation and targeting  Target?  Challenge  Mixed Solution Generating Acquisition  Powerful segmentation  Complex issues ‘Quali’ methodology  Multiple applications  Difficult conceptual level for +  Profiling segments respondent PSAP survey  Clear targeting & marketing 5
  • 6. PSAP is based on recent views of double-peaked adoption curve PULL: PUSH/ Mass Market PULL Adoption Innovation Dislikers Pr oduct Mat ur i t y & Ri sk Aver si on Innovators Early Early Late Laggards Adopters Majority Majority Key char act er i st i cs: • No cl assi cal segm ent si zes • Pr oduct m ur i t y and r i sk aver si on ( x- axi s) r epr esent s r ough, at but no concr et e t i m i ne el • Pot ent i al m ket i s not necessar i l y 10% si nce Innovat i on ar , 6 Di sl i ker s m exi st t hat w l l never be i nt er est ed t o pur chase ay i
  • 7. Adoption potential forecast 40% 35% IOT 30% 25% 20% 15% Rogers 10% 5% 0% innovators early adopters early majority late majority laggards Rogers 2,5% 13,5% 34,0% 34,0% 16,0% IOT 12,8% 14,2% 11,6% 28,9% 32,6% 7
  • 8. Differences between classes 40% 35% 30% Class 1 25% 20% 15% Class 2 10% 5% Rogers 0% innovators early adopters early majority late majority laggards 8
  • 9. Cumulative adoption: S-Curve 120% 100% 80% 60% 40% 20% 0% innovators early adopters early majority late majority laggards Rogers 2,50% 16% 50% 84% 100% IOT 12,80% 27,00% 38,60% 67,40% 100% 9
  • 10. Drivers and motivations  Important factors to accelerate (drivers) or slow down (barriers)  Opportunity to keep informed (information)  Making the most of the journey (utility)  Stay in contact (communication)  Current infrastructure not suitable  Already Internet at home/work  Raise productivity  Prefer talking with passengers (social contact) 10
  • 11. Willingness to pay  Innovators and Early Adopters likely to pay  Early Majority only if price is low enough  Especially for browsing and e-mail applications  Also updated news, travel info and corporate network (VPN) popular  In general:  Innovators business applications  Early Adopters more entertainment oriented 11
  • 12. Quality of Service  Most important features  Cost  Predictability/reliability  High speed  Least important features  Ease of payment  Anonymity  Service desk assistance 12
  • 13. Conclusions  Clear market potential  Short term: 10-15% passengers  Long term: 30% passengers  Small but heavily interested target public  Price is crucial factor for adoption  Willingness to pay highest among I and EA  I business and EA entertainment applications 13
  • 14. Thank you for listening Questions? Further information? Tom Evens Korte Meer 7-9-11 9000 Gent 09/264.68.83 Tom.Evens@UGent.be 14