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Customer Centricity With Deep Learning While Maintaining Privacy
- 3. Customer Centricity With Deep Learning While Maintaining Privacy
- 4. Who we are
- 5. Eliot Knepper Founder & CEO, Mnemonic AI, Operations, Sales and Marketing eliot@mnemonic.ai Phil Wennker Founder & AI Engineer, Data Science phil@mnemonic.ai mnemonic.ai hello@mnemonic.ai Mnemonic AI Inc. 201 Spear Street Suite 1100 San Francisco CA. 94105
- 6. 2018 Sept. 2019 todayResearch DL, NLP "[...]one of the brightest “Big Data” startups in Europe" Incorporation PoC Gov B2B B2C Where we're at
- 7. Who we are What we do Why privacy is important
- 9. I know that guy. Just last week he... Primer Personas Marketing Personas are archetypes of your customers. They represent homogeneous groups of customers. With needs, demands, fears, hobbies.
- 10. Marketing Personas are the cornerstone to be customer centric... ...and it pays off. • 171% increase in marketing generated revenue1 • 124% increase in leads from all channels combined1 • 46% increase in conversions1 1: https://www.marketingsherpa.com/article/case-study/targeted-persona-content-marketing-strategy 2: https://www.brighttalk.com/webcast/43/53249
- 11. creates personas automatically & dynamically
- 12. Triggers Emotions regarding product / service NarrativeDemographics
- 13. Automated Persona Creation Internal Data Surveys Interviews CRM eMail Web Analytics Call Logs External Data Social Reviews Third Party Source Agnostic
- 14. Automated Personas Creation Process Named Entity Recognition Topic Modelling Aspect based Emotion Recognition Understanding Data cleaning & pre-processing Gathering Creating Calculating personas First and third party data Cleaning minutes compared to hundreds of staff hours Nummerical & meta data
- 15. θ Threshold
- 16. Markets change, so do your personas
- 17. Who we are What we do Privacy
- 18. GDPR, CCPA, PIPEDA, ...
- 19. Van Veen, F. & Leijnen, S. (2019). The Neural Network Zoo. Retrieved from https://www.asimovinstitute.org/neural-network-zoo
- 21. Group Insurance Commission, William Weld, Gov, MA - 1997, Sweeney Netflix - 2007, Narayanan and Shmatikov, UT Austin Netflix Prize dataset - 2018, MIT AOL Search Queries - 2006, NY Times
- 22. Internal Data Surveys Interviews CRM eMail Web Analytics Call Logs External Data Social Reviews Third Party Could all contain PII
- 23. Rep: This is Paul. How can I help you? Caller: This is Matt. I want to change my insurance plan to silver Rep: Sure, I can help you. Can you give me the plan number? Caller: yes, 1234567 Rep: For verification purpose may I know your date of birth, email id and social security number? Caller: My data of birth is 10-Aug-1980, my email id is matt@gmail.com, 078-05-1120 Rep: Which plan do you want to migrate to Caller: Silver Plan plus Rep: Can I have your full name and date of joining Caller: Matt Mitchell and doj 01-Feb-2015 Rep: Ok.. I have taken your request to migrate plan to silver plus. You will get an update in the next 24h hours. Is there anything else that I can help you with Caller: No Rep: Thanks for calling. Have a good day Caller: you too Name: Paul Mitchell Date of birth: 10-Aug-1980 Plan Number: 1234567 SSN: 078-05-1120 Email id: paul@gmail.com Date of joining: 01-Feb-2015
- 25. Spacy 2.2 Bert ELMO RoBERTa 0 % 20 % 40 % 60 % 80 % 100 % 92,4 % 90,86 % 88,76 % 83,5 % F2 Score
- 26. For now: RoBERTa + RegEx Spacy 2.2 Bert ELMO RoBERTa 0 % 20 % 40 % 60 % 80 % 100 % 92,4 % 90,86 % 88,76 % 83,5 % F2 Score + Special Cases (Gender, Age, Location, Job)
- 27. X̄