July 2019 Summaries

The author of the text is trying to find a better way to catch unsatisfiable Auto Layout constraints errors in Xcode, which occur when there are two or more conflicting Auto Layout constraints installed in an app's view hierarchy. To achieve this, they developed a solution that involves running UITests and using LLDB (Low-Level Debugger) to attach to the process and wait for the constraint removal. The author provides step-by-step instructions on how to run LLDB from the terminal locally, including attaching to the debugger, waiting for verification, and executing custom commands. They also discuss how to use this solution in a CI/CD pipeline using CircleCI 2.0.

Detecting unsatisfiable Auto Layout constraints in UIKit can help developers address potential UI issues, even if it doesn't catch all instances of UI breakage. These errors occur when there are conflicting constraints in an app's view hierarchy, which UIKit attempts to resolve by logging the conflicts in the console. To systematically identify these issues during development and continuous integration (CI), the process involves attaching a debugger to UI tests, using LLDB's symbolic breakpoint UIViewAlertForUnsatisfiableConstraints, and running the tests via the command line. By automating LLDB commands through a text file, developers can streamline the process, allowing tests to continue running by terminating and re-adding breakpoints as needed. Integrating this approach with a CI tool like CircleCI ensures that any test failures are flagged for unsatisfiable constraints, running LLDB in the background and triggering checks only when a UI test failure occurs. This method aims to enhance the reliability and maintainability of the app's UI by catching layout issues early in the development cycle.

Surveys are most useful when elegantly deployed, and having a working understanding of survey segmentation and targeting best practices is crucial for getting actionable answers. Segmentation helps to identify specific subgroups of users, allowing businesses to learn more about their customers and better cater to their needs. By dividing users into groups with similarities, businesses can entice the right users into trying their app, increase response rates, and tailor messaging to a specific group of people. Effective segmentation involves researching and analyzing quantitative and qualitative data, including demographic information, purchasing behavior, location, device information, application events, user behavior, occupational details, profile information, and user frequency. Once segments are created, businesses can ask segment-specific survey questions that take into account the goals and needs of each group. Survey targeting considerations include timing, location and time of day, in-app events, user behaviors, persistence, and survey length, with the goal of minimizing interruption and maximizing response rates. By using these strategies, businesses can collect valuable feedback from their users, improve their product roadmap, and create a more personalized user experience.

In-app surveys are an effective tool for gathering specific user data, enabling companies to make informed, data-driven decisions about product development and customer needs. Effective survey segmentation involves grouping users by similar characteristics such as demographics, purchasing behavior, and usage patterns, which allows for more targeted marketing and feedback collection. This approach not only increases response rates but also helps in customizing user experiences, reducing app uninstalls due to irrelevant messaging. Tailored survey questions and strategic deployment, considering factors like timing and user behavior, are crucial for maximizing the benefits of segmentation. Additionally, understanding user segments can aid in persona creation, providing deeper insights into user needs and expectations. Regularly testing and updating segmentation strategies ensures relevance as user behavior and app features evolve over time.

Calculating an NPS score for a mobile app involves understanding how to categorize respondents into promoters, passives, and detractors based on their responses to a survey question. The traditional NPS question asks users to rate their likelihood of recommending the product to a friend or colleague on a scale of 0-10. A positive score indicates more promoters than detractors, while a negative score suggests the opposite. Industry benchmarks for NPS scores vary widely across different industries and contexts, with some companies scoring above 70 indicating exceptional customer experience. To get a better understanding of one's NPS score, it's essential to consider industry averages, perform a holistic competitive analysis, and use in-app surveys that collect valuable feedback through additional questions. Instabug offers customizable survey options, including the ability to route promoters to leave positive reviews, request additional feedback from passives and detractors, and replay app sessions to understand user experiences.

Net Promoter Score (NPS) surveys are a straightforward tool for gauging customer satisfaction, measuring how likely customers are to recommend a product or service on a scale of 0-10, with respondents categorized into promoters, passives, and detractors. The NPS is calculated by subtracting the percentage of detractors from the percentage of promoters, yielding a score between -100 and 100. A positive score is generally considered good, though the definition of "good" varies across industries, with scores above 30 indicating high customer satisfaction and scores over 70 denoting exceptional customer loyalty. Industry benchmarks, such as those from the NICE Satmetrix U.S. Consumer Net Promoter Benchmarks Report, provide context but should be viewed cautiously due to regional and industry-specific differences. The NPS is particularly valuable as it offers a simple, quantitative measure of customer sentiment, but deeper insights can be gained by pairing it with qualitative feedback from follow-up questions. Tools like Luciq enhance the NPS survey process by allowing customization of questions and follow-up actions, helping businesses gather detailed feedback and engage directly with respondents, thereby providing a more comprehensive understanding of customer experience and areas for improvement.

I've been working with the Instabug team for five months and have learned about their core values, particularly "No Bullshit," which emphasizes direct communication, respect, and simplicity. I initially struggled to understand this value during my interviews but set out to learn more after joining the company. I read the 70-page handbook, which answered many of my questions and helped me grasp the importance of being straightforward in conversations and sticking to facts. Through my experiences, I've seen how embracing these values has led to personal growth and a positive work environment, where team members aspire to be their best selves and make decisions based on open communication and respect.

Having spent five months at Luciq, the author reflects on their journey of aligning with the company’s core values, particularly "No Bullshit," which emphasizes direct and respectful communication. Initially overwhelmed by the extensive 70-page Luciq Handbook, the author found clarity in its guidelines, which reinforced the importance of straightforwardness in avoiding unnecessary complexities and fostering efficient teamwork. In a planning meeting, the author witnessed the practical application of these values, where concise communication and focus on key performance indicators led to an impressively brief yet effective session. The author learned that minimizing drama and ego within a supportive work environment accelerates personal and professional growth, as demonstrated by the team's commitment to transparency and efficiency. With these insights, the author invites like-minded individuals to consider joining Luciq, emphasizing the company's consistent adherence to its aspirational values as a catalyst for personal development.