Quantitative vs. Qualitative in UX

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Please evaluate this statement as being fair or not, based on your UX expertise: When the candidate talked about quantitative data such as user interviews with 6 people or testing a flow with 8 people, the team would push back looking for reassurances of quantitative data. It seems like the team hasn’t worked with UX before. This is a classic problem and source of misunderstanding and weaker product. For example: One caricature of this problem is Google A/B testing for the perfect shade of blue on a button. Google as an organization has acquired all of it’s its key B2C apps that people use and love and has a poor track record of shipping great user experiences. They are obsessed with qualitative data and backing decisions based on that data. In design, you are often early to a problem space otherwise you wouldn’t be doing design. You want to interview users and then you don’t design what they ask for, but you use qualitative data, hunches, taste, and UX principals to form a solution and test it, often in a qualitative way which may never get quantitative testing. Or the quantitative may come years later for the next iteration.The provided statement raises several points concerning the relationship between qualitative and quantitative data in user experience (UX) design, as well as perceptions of Google's approach to product design. Let's break down the statement to evaluate its fairness:

1. Quantitative vs. Qualitative Data in UX: The statement highlights a challenge that many UX professionals face. Quantitative data is based on numerical measurements and can provide statistically significant insights, while qualitative data is based on observations, interviews, and other non-numerical sources and can offer in-depth understanding. UX design often starts with qualitative data to understand user needs, desires, and pain points. Once a solution is developed, it can then be tested quantitatively to refine it further. It's fair to say that solely relying on one type of data can be limiting, and both are essential at different stages of the design process.

2. Perception of Team's Experience with UX: The statement suggests that if a team is consistently pushing back against qualitative data, they may not have extensive experience with UX. This assertion can be seen as both fair and unfair. It's fair if the team indeed lacks experience and is unaware of the value of qualitative insights. However, it's also possible that the team values quantitative data because of other legitimate concerns, like scalability or ensuring data-driven decision-making. Without knowing the full context, it's hard to judge.

3. Google's Approach to Product Design: The statement asserts that Google has a history of prioritizing quantitative data over qualitative insights and implies that this approach may have led to less-optimal user experiences. This is a contentious point. Google's A/B testing of various shades of blue is a well-known anecdote, but using it as a representation of Google's entire UX philosophy might be an over-generalization. Google has successfully developed and acquired numerous products that millions, if not billions, use daily. The statement's claim that Google's key B2C apps were all acquired and that they have a poor track record in UX might be an unfair generalization.

4. Design Approaches and Iterations: The statement correctly notes that initial design solutions are often informed by qualitative data and intuition, with quantitative testing possibly coming in later stages or iterations. This is a fair representation of many design processes.

Overall Evaluation: The statement contains both fair and potentially unfair assessments. It fairly underscores the importance of qualitative data in UX and its typical use in the early stages of the design process. However, the portrayal of Google's approach to product design and UX might be seen as an oversimplification or potentially biased perspective. Without comprehensive data or a nuanced discussion, such a characterization could be deemed unfair.Please list the Google B2C applications that were invented at Google and not aquired through purchasing a startupCertainly! Google has developed many products and services in-house, although it's worth noting that they have also expanded and enhanced many of these products through acquisitions. Here's a list of some of the notable B2C (Business-to-Consumer) applications that were originally invented at Google:

1. Google Search: The product that started it all. Larry Page and Sergey Brin developed the search engine while they were Ph.D. students at Stanford University.

2. Gmail: Launched in 2004, Gmail was a game-changer with its 1GB storage offering at a time when most other free email services offered much less.

3. Google Maps: While the initial foundation of Google Maps was based on the acquisition of a company called Where 2 Technologies, the product was significantly developed and expanded by Google, especially after the acquisition of Keyhole (which led to Google Earth).

4. Google Drive: This cloud storage service was launched in 2012 and integrated with Google Docs, Sheets, and Slides, which were also developed in-house.

5. Google Calendar: Launched in 2006, this web-based calendar service integrated seamlessly with other Google services.

6. Google News: Launched in 2002, it's an automated news aggregation service.

7. Google Translate: Started in 2006, this service began with the translation between Arabic and English and has since expanded to support over 100 languages.

8. Google Photos: While some aspects of Google Photos may have roots in Picasa (an acquired company), the Google Photos service as we know it was largely an in-house development and was launched in 2015.

9. Google Assistant: Launched in 2016, it's Google's virtual assistant that operates on mobile devices and smart home equipment.

10. Google Chrome: Launched in 2008, it's a web browser that quickly gained popularity due to its speed and simplicity.

11. Android OS: Though the original Android company was acquired by Google, the development and evolution of the Android operating system into the world's most popular mobile OS was predominantly Google's effort.

12. Google Play: The digital distribution service, including the app store for Android, music, movies, and books.

13. Google Classroom: An in-house developed service for classroom management and assignment distribution.

This is not an exhaustive list, but it gives a good idea of the range of products Google has developed in-house. However, as mentioned, many of these services have seen enhancements or integrations from technologies and talent brought in through acquisitions.Can you re-write this to better illustrate my point and to have a kinder tone with my team? When the candidate talked about quantitative data such as user interviews with 6 people or testing a flow with 8 people, the team would push back looking for reassurances of quantitative data. It seems like the team hasn’t worked with UX before. This is a classic problem and source of misunderstanding and weaker product. For example: One caricature of this problem is Google A/B testing for the perfect shade of blue on a button.Certainly! Here's a re-written version with a more collaborative tone:

"When the candidate mentioned utilizing quantitative data from user interviews with 6 individuals or testing a flow with 8 participants, the team understandably sought further clarity on the breadth of quantitative data. It's quite common, especially for teams less familiar with the nuances of UX, to lean more towards large-scale data sets. A well-known example in the industry is Google's extensive A/B testing to determine the ideal shade of blue for a button. It's all about finding the right balance between qualitative insights and quantitative data to create the best user experience."

Quantitative vs. Qualitative in UX created at Tue Jan 20 1970 15:41:39 GMT+0000 (Coordinated Universal Time)