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Cattolica Go

Sponsored · Ship Features Fearlessly Turn features on and off without deploys. Used by thousands of Ruby developers. →
Avatar for Tiago Martinho Tiago Martinho
May 01, 2018
Technology
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Cattolica Go

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Tiago Martinho

May 01, 2018
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Transcript

  1. #call4cattolica Verona, 22.04.2017

  2. Generazione Y

  3. Trend negativo

  4. È tempo di cambiare…

  5. I reali ‘user needs’ 1. Disponibilità immediata (on-the-go)

  6. I reali ‘user needs’ 1. Disponibilità immediata (on-the-go) 2. Online

    & in-app (one-tap)

  7. I reali ‘user needs’ 1. Disponibilità immediata (on-the-go) 2. Online

    & in-app (one-tap) 3. Personalizzazione (profiling)

  8. I reali ‘user needs’ 1. Disponibilità immediata (on-the-go) 2. Online

    & in-app (one-tap) 3. Personalizzazione (profiling) 4. ‘Quel tanto che basta’ (pay-as-you-go)

  9. Indice di rischio & offerta Database Apps AI fraud detection

  10. 1 motore 2 modelli di business

  11. 1 motore 2 modelli di business B2C Micro-polizze predittive

  12. 1 motore 2 modelli di business B2C Micro-polizze predittive Suggerite

    imparando da chi è l’utente e dalle sue abitudini

  13. …e i casi sono illimitati - Nuovo device - Attività

    anomala - Acquisti - Viaggio - Furti - Dati sanitari - Visita medica - Macchina - Smart Home - Animali

  14. 1 motore 2 modelli di business B2C Micro-polizze predittive Suggerite

    imparando da chi è l’utente e dalle sue abitudini

  15. 1 motore 2 modelli di business B2C Micro-polizze predittive Suggerite

    imparando da chi è l’utente e dalle sue abitudini B2B APIs per piccoli commercianti

  16. 1 motore 2 modelli di business B2C Micro-polizze predittive Suggerite

    imparando da chi è l’utente e dalle sue abitudini B2B APIs per piccoli commercianti Infrastruttura per permettere ad altri di assicurarsi → clienti gratis
  17. None
  18. None
  19. None
  20. None
  21. None
  22. None

  23. Competizione (in US, solo B2C) Source: http://burnmark.com/wp-content/uploads/2016/11/Burnmark-Report-November-2016.pdf

  24. Value Proposition 1. ML → apprende chi è l’utente

  25. Value Proposition 1. ML → apprende chi è l’utente 2.

    AI → personalizza l’offerta in base

  26. Value Proposition 1. ML → apprende chi è l’utente 2.

    AI → personalizza l’offerta in base 3. Nuova relazione con l’utente → PAYG

  27. Value Proposition 1. ML → apprende chi è l’utente 2.

    AI → personalizza l’offerta in base 3. Nuova relazione con l’utente → PAYG 4. API → Nuovi ‘assicuratori’ → + clienti

  28. iOS Developer CEO @Elit Luca SW Developer @Belka Silvia Product

    Designer @Viabo Silvio SW Developer @UniTN Tiago Max Franz Biz Developer @EIT Digital UX Designer @Belka

  29. Survey 45

  30. Pricing B2C → algoritmo AI-based (basato su originale) B2B →

    idem - % per il vendor