The document outlines a roadmap for utilizing the USPA framework to enhance data collection, segmentation, processing, and personalization for businesses in the age of dataism. It emphasizes the importance of adapting to new business norms and unifying customer data to improve marketing strategies and customer engagement. Additionally, it provides insights into customer data types, segmentation techniques, and the need for a coherent database or customer data platform for operational efficiency.

1. Data Collection,
Processing & Organization
with USPA framework
How to think in the age of Dataism

2. Roadmap
How to think in the age of Dataism with USPA framework ?
Unified Data Collection, Segmentation Processing, Personalization model and Activating your business
How to collect customer data
Data Segmentation Processing
Data Organization for personalization and business activation
1.
2.
3.
4.

3. Data about myself
● Former Lead Software Engineer at FPT Telecom and FPT Online
● Former Head of Platform at Blueseed Digital
● Former Backend developer at Tiki
● In 2020, founded USPA.tech as Software Technology Company
Details at https://www.linkedin.com/in/tantrieuf31/

4. Roadmap
How to think in the age of Dataism with USPA framework ?
Unified Data Collection, Segmentation Processing, Personalization model and Activating your business
How to collect customer data
Data Segmentation Processing
Data Organization for personalization and business activation
1.
2.
3.
4.

5. https://en.wikipedia.org/wiki/Dataism
What is the Data-ism ?

6. Source: https://witanworld.com/blog/2019/05/23/database-a-general-introduction/

7. Fact: Data is invisible asset.
You can feel it only when it explodes in your brain

8. One of best books about Dataism for everyone

9. Dataism is the ideology that has main focus on the “intelligent reality design”
with big data, digital platform, human identity and smart algorithms

10. How to apply dataism in practical business
(Google, Facebook, Amazon and Ad Tech Industry)

11. The first question:
“How to think
in the age of Data-ism”

12. Source: https://www.amazon.com/Predictive-Marketing-Marketer-Customer-Analytics/dp/1119037360
Customer Data is the new gold
for business in 21st century

14. Types of data to build Unified Customer Analytics

16. The second question:
“how to adapt to new
normal World ?”

17. Fact: We must adapt to “new normal World” in 2020
https://news.cgtn.com/news/2020-02-29/New-Business-Trends-Brought-by-Covid-19-Ou0gExnYju/index.html
O2O Retail
can be the key
for growth

19. Roadmap
How to think in the age of Dataism with USPA framework ?
Unified Data Collection, Segmentation Processing, Personalization model and Activating your business
How to collect customer data
Data Segmentation Processing
Data Organization for personalization and business activation
1.
2.
3.
4.

20. Data Collection Flow in Customer Data Platform

22. Collect right data from Customer Journey for segmentation
is the key action for successful campaign
First-party data source from owned media
Third-party data source from shared media
Second-party data source from partner network

24. To build a Customer Persona, you can apply OODA loop for
target market research and customer data seeding
Pilot campaign
with small budget

25. Sampling data from social media to build customer persona

29. Roadmap
How to think in the age of Dataism with USPA framework ?
Unified Data Collection, Segmentation Processing, Personalization model and Activating your business
How to collect customer data
Data Segmentation Processing
Data Organization for personalization and business activation
1.
2.
3.
4.

30. Data Segmentation in high-level structure

31. Types of customer segments in retail industry

32. RFM Analysis For Successful Customer Segmentation

33. Source: https://github.com/joaolcorreia/RFM-analysis

34. Purpose of data segmentation to do personalization better

35. Roadmap
How to think in the age of Data-ism with USPA framework ?
Unified Data Collection, Segmentation Processing, Personalization model and Activating your business
How to collect customer data
Data Segmentation Processing for flexibility and scalability
Data Organization for personalization and business activation
1.
2.
3.
4.

36. Implicit data is gathered by predictive analytics from
second-party data and third-party data.
It also includes loyalty, length of relationship,
purchasing history, and prior responses to marketing
campaigns.
Explicit data is easier to gather and analyze
because it is usually provided to the company
directly from the customer.
Data Organization
should begin with
customer profile schema

37. Source: https://www.computer.org/publications/tech-news/research/customer-data-platform
Customer Data Model in the 21st century for data-driven organization

39. Example of customer journey flow in book retail

40. Multi-model database can be good solution for data storage
1. Graph data model is best for customer journey management
2. Homogeneous document model can be used for customer profile
3. Flexibility of ArangoDB is the key to scale system easier
4. Scalability of ArangoDB can help business analytics grow faster
Graph databaseDocument + Key-Value

41. The final question:
“Why do we need to
unify data into a single
database or CDP ?”

42. Remarketing example flow
What if Bob already
bought your offered
product ?

43. Example of a Digital Advertising Efficiency Use Case

44. Example of an Outbound Marketing Re-engagement Use Case

45. Example of a CDP Integration for Personalization

46. Key takeaway

47. How can we think
in the age of Dataism?
USPA mindset can be the pivot framework
for your data strategy

49. How to adapt to
new normal World ?
O2O (Offline To Online) Business Model
can be the key for solution

51. Why do we need to unify data
into a single database or
Customer Data Platform?
To connect with your customers on a
personal level and activate business growth

52. Source: https://getthematic.com/insights/unified-data-analytics/

53. Thank you!
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