Frazer Mawson emphasizes the significance of Mixed Methods Experimentation in optimizing user experience and conversion rates. He outlines four primary use cases for this approach, which combines qualitative and quantitative research methods to enhance the effectiveness of experiments. The first use case is diagnosis and prioritization, where user experience (UX) research identifies factors that hinder or enhance conversion rates. This foundational understanding allows teams to create and prioritize hypotheses for testing, leading to more informed experimentation. Mawson notes that tests grounded in research tend to have higher success rates compared to those without such backing. The second use case involves understanding test results. While A/B testing is a standard method for determining the causal relationship between variables, it often lacks insight into the reasons behind the outcomes. By integrating UX research after testing, teams can uncover the underlying motivations for user behavior, as illustrated by a case where lifestyle imagery failed to perform as expected. The third use case focuses on informing key decisions. A/B tests reveal how features impact user behavior, but they do not explain why. Incorporating UX research fills this gap, providing the necessary context for making strategic decisions based on experimental data. The fourth use case is execution sharpening, where the design concept undergoes UX research before being tested. This ensures that the execution of the hypothesis is robust, minimizing the risk of inconclusive or misleading results. Mawson invites readers to share their experiences with Mixed Methods, suggesting that there may be additional applications not covered in his post. He highlights the importance of experimentation in driving business value and encourages a collaborative discussion on the topic. In a broader context, Mawson discusses the challenges and limitations of various research methods, advocating for a Mixed Methods approach to overcome these obstacles. He emphasizes that while A/B testing provides valuable data on user behavior, it does not capture the full picture, particularly regarding user motivations and preferences. By combining different methodologies, teams can triangulate insights and make more informed decisions. Mawson also shares insights from his experience with specific experiments, illustrating the practical application of these concepts. He recounts instances where initial hypotheses were challenged by user feedback, leading to unexpected results. This highlights the iterative nature of experimentation and the necessity of adapting strategies based on real-world data. Overall, the discussion underscores the value of Mixed Methods Experimentation in enhancing user experience and driving conversion rates, while also acknowledging the complexities and nuances involved in the process.

User testing is by far the fastest and most effective way to find the issues that limit website conversion rates and revenue. There are five levels of user testing to consider: testing on yourself, testing on someone with fresh eyes, testing with qualified users, testing with prospects who are on your website right now, and testing competitor websites alongside your own. Common issues found from these methods include users making “stupid” mistakes, users not trusting you (or believing your claims), or users hitting a sticking point and stalling (or leaving).

In user experience (UX) research, the practice of asking users "Why?" serves as a fundamental method for uncovering the motivations behind their behaviors and preferences. This approach, while seemingly straightforward, reveals a complex interplay of psychological factors that can both enhance and hinder the effectiveness of UX research. The article delves into the strengths and weaknesses of this inquiry method, offering insights into how to maximize its benefits while addressing its limitations. The strength of "Why?" questions lies in their ability to probe deeper into user motivations. From an early age, individuals naturally adopt a scientific approach to understanding their environment, often asking "Why?" to make sense of their experiences. In UX research, this technique aims to uncover core motivations and mental models that drive user behavior. The "Five Whys" technique, originally developed at Toyota, exemplifies this approach by encouraging researchers to ask "Why?" repeatedly to identify root causes of user issues. Additionally, the Theory of Planned Behavior suggests that understanding user intentions through "Why?" questions can lead to better predictions of future behaviors, allowing designers to create products that align more closely with user needs. However, the effectiveness of "Why?" questions is not without challenges. Research in cognitive psychology indicates that individuals often lack introspective access to their true motivations. Studies have shown that people may provide post-hoc rationalizations for their choices, leading to inaccurate or misleading explanations. For instance, participants in experiments have confidently justified choices they did not actually make, highlighting the tendency for individuals to fabricate reasons for their actions. This phenomenon raises concerns about the reliability of user responses in UX research, as users may attribute their preferences to superficial factors rather than the underlying influences that truly guide their decisions. Cognitive dissonance also plays a role in how users respond to "Why?" questions. Users may rationalize their behaviors to align with their self-perception, leading to justifications that do not accurately reflect their true motivations. Cultural and contextual factors further complicate this dynamic, as different cultural backgrounds can influence how users interpret and respond to inquiries. For example, individuals from cultures that prioritize social harmony may avoid providing negative feedback, skewing the data collected during UX research. To effectively leverage the power of "Why?" questions while mitigating their pitfalls, researchers can adopt several strategies. Triangulation, or the use of multiple data sources, can enhance the credibility of findings by cross-verifying insights. Behavioral observation allows researchers to gather information on user actions rather than relying solely on self-reported data. Implicit measures can uncover attitudes that users may not consciously recognize or be willing to disclose. Additionally, being aware of cognitive biases can help researchers design inquiries that minimize their impact on user responses. In conclusion, while "Why?" questions remain a valuable tool in UX research, their application requires careful consideration of their limitations. A balanced approach involves using these questions judiciously, complemented by other research techniques, and maintaining a critical perspective on the explanations provided by users. By understanding the complexities of human cognition and decision-making, researchers can develop more effective strategies for uncovering user motivations and behaviors, ultimately leading to better design outcomes.

Combining Marketing and Design enhances end-to-end user experience and should be unified under one leader for efficient decision-making. Companies should focus on customer experiences from awareness to product championing, fostering collaboration, and "Yes, and..." thinking across departments.

Exploring the nuances of conversion optimization, this article highlights 13 factors that may hinder website traffic from converting and offers actionable tactics. From establishing trust to simplifying navigation and enhancing value perception, marketers can implement these solutions to optimize their conversion funnels.

The demand for user research is growing as brands face uncertain times and aim to mitigate risk in their strategies. Non-researchers, such as marketers and product designers, are increasingly conducting user research. This research democratization results in a greater impact on decision-making. New AI tools are allowing teams to scale their user research by automating analysis, transcription, and other tasks.

A new A/B testing model leverages the variation in consumer responses to dynamically allocate test subjects, reducing the number of observations needed by 50%.

The mise en mode approach allows creativity and expression while maintaining a structured system for user experience design. Its premise is to think of elements like rounded corners, purple gradients, and typography as modes on top of an underlying familiar structure. A system like this provides user expectation guardrails, while tokens provide a style-by-name interface to convey a form of expression.

This article shares how to create interactive content that resonates with audiences on a deeper level than traditional social media posts. From quizzes and polls to user-generated content campaigns and giveaways, these innovative approaches not only boost visibility, but also foster a sense of community and brand loyalty.

Simulate user behavior and pinpoint potential usability problems more efficiently.

Iterative design enhances website development by incorporating continuous user feedback to refine and improve the user experience. This approach involves four key stages: research and ideation, prototyping, testing and evaluation, and refinement. By focusing on user-centered design, iterative methods reduce costly errors, ensure more effective websites, and foster better collaboration among development teams, leading to successful outcomes.

This post shares 8 strategies to experiment with to optimize paywall conversion. These include adding a Free vs. Premium comparison chart, sharing stats on premium user success rates, offering discounts for annual subscriptions over monthly ones, and incorporating dynamic images and copy that match with what users tapped to reach the paywall.

This article presents CRO case studies that offer insights for marketers. From enhancing in-store sales through digital marketing to maximizing ad spend with creative landing pages, each case study highlights innovative approaches and techniques to improve conversion rates and drive business growth.

Based on UserZoom capabilities, UserTesting has created a new Feedback Engine, which combines AI with generative capabilities to help better understand feedback from user surveys. The company is also expanding its AI-powered insights capability to provide a deeper analysis of trends from user testing operations by enabling AI-powered surveys. AI-powered theme generation will allow researchers to understand test results better.

Designers keep pushing for design research because they think that is how it should be done in all projects. However, for most projects, regular research is sufficient. Intensive research should only be conducted when a new product is being developed, when a crucial decision needs to be made, or when no knowledge source is available.

Netflix researchers developed methods to analyze historical A/B test data to understand the relationship between proxy metrics and long-term business outcomes. They propose three estimators that offer more robust solutions for understanding the true relationship between proxy metrics and north star metrics: Total Covariance (TC), Jackknife Instrumental Variables Estimation (JIVE), and Limited Information Maximum Likelihood (LIML).

Exploring the extremes is an excellent way to find ideas that transform the status quo and improve user experience. It can also unlock innovation and creativity, resulting in breakthroughs. The best way to embrace extremes is to let go of what's familiar and comfortable, embrace constraints, and be open to vulnerability.

With how quickly things are changing in tech, marketing playbooks are quickly becoming relics. This article covers an alternative: the RINse and Repeat framework. The first critical step is building a rich understanding of your customers and market with a narrow-to-broad-to-narrow approach. Next, generate novel ideas for campaigns that capture attention in new ways, including new channels you haven’t tried yet. Lastly, narrate the impact and avoid over-indexing on conversion metrics that often under or overstate campaign success.

Optimizing your cancellation flow can reduce user churn. Brands should first collect the various reasons why users cancel, either through user interviews or by using an open-ended question in the cancellation flow. Next, insert a multiple-choice survey into the cancellation flow based on the initial research. Finally, set up the flow to provide a win-back offer back on the multiple-choice selection.

The “Plus 20% Content Strategy” advises marketers to improve social media engagement by analyzing content performance and adjusting strategies incrementally. By focusing on content that exceeds the median by 20% and doubling down on its production while cutting underperforming content, marketers can enhance engagement gradually.

To increase a website's conversion rate, survey customers who just bought your product or service. These users can help uncover obstacles that result in other visitors leaving without buying. Ask them where exactly they first found out about you, what persuaded them to purchase from you, which options they considered before choosing your product, and the one thing that nearly stopped them buying from you. Incentivize survey participation with a small reward and send a thank you email to respondents.

Properly establishing null and alternative hypotheses before conducting A/B tests is essential. The null hypothesis suggests sample observations occur randomly, while alternative hypotheses propose that the control and variant groups are not comparable. This article shares best practices and discusses in detail the different types of alternative hypotheses and how to use them to interpret results based on statistical significance.

To optimize Facebook ad performance, use “ugly” ads that resemble organic content. Incorporate real people into your ads, rather than focusing solely on product images. Use Facebook's dynamic ad features, such as Dynamic Creative Optimization and Advantage+, to automatically test and optimize creative elements. Implement the “engagement; purchase; scale” method by warming up audiences, retargeting for conversions, and scaling successful campaigns. Allow Facebook's algorithms to manage targeting while you focus on A/B testing. Lastly, switch to the Conversion setting for Lead Ads to drive users to your website forms for better tracking.

Recent changes to Google's user interface have affected the volume and quality of organic website traffic, particularly for top- and bottom-of-funnel keywords. Mid-funnel content can help transition searchers from being problem-aware to solution-aware and improve brand awareness. Examples of mid-funnel content include feature round-ups, solution hijacking, quizzes, niche calculators, scorecards, and alternative assets.