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Enhance Product Experience Through Data Analysis. Join Today.
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Learning Objectives
1. Emphasizing Data-Driven Argumentation
Advocating for utilizing data to strengthen arguments for more persuasive discussions and decision-making processes.
2. Integration of Industry Insights in Research
Encouraging a holistic research approach that combines academic papers with industry reports to gain a comprehensive understanding of the subject matter.
3. In-Depth User Research Techniques Exploration
Exploring various user research methodologies, particularly user interviews and diary studies, to gain insights into user behavior and preferences.
Highlighting the significance of product telemetry in collecting user data and demonstrating its practical applications through a marketer's strategy at Flipkart.
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Who's it for
Product designers
Data analysts
User experience researchers
Marketing professionals
Ecommerce specialists
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What will I learn
Chapter 1
Self-Reflection and Purpose
In this chapter, the speaker reflects on the importance of self-reflection and questioning one's purpose. The speaker shares personal experiences and insights on how introspection can lead to a better understanding of oneself and one's goals.
Chapter 2
Desire for Connection and Understanding
The text delves into the speaker's desire for connection and understanding with others. The importance of building meaningful relationships and seeking guidance and reassurance from others is emphasized.
Chapter 3
Using Data for Product Experience
The focus shifts towards the significance of using data to build product experience. The speaker discusses the role of data in influencing decisions and how relying on data can lead to more compelling arguments compared to personal opinions or beliefs.
Chapter 4
Types of Data for Comprehensive Perspective
This chapter explores different types of data, including qualitative data, that are valuable in developing a comprehensive perspective. The speaker highlights the importance of utilizing academic papers and industry reports for research purposes.
Chapter 5
User Research Techniques
The text discusses various user research techniques, such as user interviews, diary studies, and product telemetry, for understanding user behavior and preferences. Practical examples are provided to showcase the implementation of these techniques in real-world scenarios.
Chapter 6
Campaign Strategies for User Engagement
The chapter focuses on campaign strategies aimed at re-engaging inactive users and encouraging purchases from users who abandoned their carts. The importance of understanding user behavior and timing in triggering campaigns is highlighted, along with the use of simulation features for testing complex scenarios.
Chapter 7
Usability Testing and Personalization Features
This chapter delves into usability testing and the development of a new personalization feature that allows users to customize their experience. The process of competitive benchmarking and the importance of flexibility in product design are discussed.
Chapter 8
Team Dynamics and Future Goals
The text provides insights into the team structure and future goals of the product development team. The emphasis is placed on accommodating various industries and domains through flexible design, with the goal of covering a wide range of sectors like fintech and ecommerce. Contact information for further inquiries is also provided.
Meet your Mentor
Arindam Roy
Design Leader @ Moengage | Ex Microsoft
Arindam Roy is a Design Leader at Moengage, with prior experience at Microsoft. Based in Bengaluru, Karnataka, he excels in conference speaking, training, and workshops. Arindam is active in the design community, contributing as a reviewer and speaker at notable events like the India HCI and UX Designcon Bangalore. His journey spans over 9 years, showcasing his expertise and passion for creating desirable user experiences.
Frequently Asked Questions
What are the main pillars of Data Analysis?
Data collection, data cleaning, data exploration, data visualization, data interpretation, and decision-making are main pillars.
What is Data Analysis, and why is it important to learn about?
Data analysis is the process of inspecting, cleaning, transforming, and modeling data to uncover insights crucial for decision-making.
Is this Data Analysis course designed for corporate training and workforce upskilling?
Yes, this course is tailored for individuals seeking corporate training and workforce upskilling in data analysis.
How long can I access the free data analysis course content?
You can access the free data analysis course content indefinitely once you enroll in the course.
Will I receive a certification upon completion of the free data analysis course course?
Yes, upon successful completion of the free data analysis course, you will receive a certification.
Enhancing Product Experience through Data Analysis
4.4
(330 ratings)
Intermediate
29th July 2024 at 3:30 pm GMT
24k Learners enrolled
Mentor
Arindam Roy
Design Leader @ Moengage | Ex Microsoft
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