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Harness AI to streamline UX research and unlock actionable insights with UserTesting AI.

How UserTesting can help you:

Increases team efficiency by automating repetitive tasks.
Accelerates time to insights through AI-powered analysis of user data.
Amplifies business impact by making research accessible and actionable across teams.

Why choose UserTesting: Key features

AI Insight summaries for quick understanding of key findings.
Friction detection to identify and improve user experience issues.
Sentiment analysis to gauge user reactions and emotions.
Domain-specific datasets and machine learning models tailored for UX research.

Who should choose UserTesting:

UX/UI Designers seeking deeper insights into user behavior.
Product Managers aiming for accelerated product development cycles.
Marketing teams looking for customer feedback to drive strategy.
Business Executives focused on leveraging user research for strategic decisions.

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Autonomous AI-powered software testing tool TestSprite announces early access - SiliconANGLE

Autonomous AI-powered software testing tool TestSprite announces early access TestSprite Inc., a platform that offers end-to-end software testing using fully autonomous artificial intelligence, today announced early access to its platform today. The company's platform provides an AI-powered quality assurance solution that fully automates the process of testing back-end and front-end systems with minimal input from the user by using the context of the services, documents and custom instructions. Traditional testing can be tedious and slow, requiring the generation of numerous test cases for both the user interface on the front-end and numerous test cases for code on the back-end. It is often manual and difficult to scale. The addition of AI co-pilots has eased this work considerably but still requires a noticeable degree of human assistance along the way. TestSprite looks to take the next step and have AI learn everything it possibly can from all the context that is available about software up front and do most of the work. It can learn and understand test objects, inspect software and interpret documentation. From there, the AI automatically drafts test plans in natural language and provides them for review prior to test code generation. That means humans remain in the loop if software engineers want to customize any part of test generation. Finally, complete testing scripts are generated based on the approved plans, scheduled and executed. Should any tests fail, the AI interprets the failures and assists with debugging the root causes using learned knowledge from software code and documentation. "We are the first to introduce a fully automated process powered by an AI testing agent," co-founder and Chief Executive Yunhao Jiao told SiliconANGLE. "Unlike other tools, TestSprite's AI can independently generate testing plans, supporting over 10 types of test categories, and implement code for multiple test cases simultaneously -- no manual input needed." TestSprite covers all the bases from user interface elements to application programming interface calls, including authorization, functionality, performance and more. It will even attempt to uncover potential edge cases based on the software code itself and the documentation. It will also auto-patch and self-fix issues in test code, while offering human review of any changes. "One major challenge is that as more developers rely on AI co-pilots to help them write code, they become less familiar with what's actually in their codebase," Yunhou said. "This raises a critical question: Can they truly be confident in code that's primarily generated by AI? Manually testing code that wasn't entirely created by them can be daunting. That's why using AI to validate AI-generated code becomes essential." The company said the software integrates with tools such as GitHub and works with common development processes such as continuous development and integration workflows. It has a wide range of support for development environments using languages such as Python and JavaScript with a focus on major cloud platforms. TestSprite also plans to roll out test case generation for large language models and AI agents in the future. This would allow customers to use the platform to automatically generate test and run test cases for their AI-enabled applications, models and autonomous agents across broad ranges of issues. Looking ahead, Yunhao said the company also plans enhance the AI capabilities to support more programming languages and testing scenarios, including mobile apps. The waitlist for the platform's early access program is available for coders, developers and small businesses interested in AI-driven testing and AQ is open now at the company's website on a first-come, first-served basis. TestSprite said the platform is targeted to launch into general availability in late October.

SiliconANGLE

Thu, 10 Oct, 2:17 PM UTC

15 ChatGPT Prompts to Improve Customer Experience in Digital Banking

Traditional methods of UX design could be significantly empowered by ChatGPT -- a powerful generative AI model. This article unveils the secrets of using ChatGPT prompts to drive innovation in banking UX, providing insights into how this tool can be integrated into the standard design process for transformative results. Incorporating ChatGPT into the standard product design workflow introduces a powerful tool that combines human creativity with AI-generated insights. For financial digital products, this means developing a user experience that is not only innovative but also deeply attuned to the needs and desires of its users, setting a new standard in the financial industry. Using generative AI, such as ChatGPT, prompts in banking UX design can be highly valuable for several reasons, and it can significantly empower product teams. Here's how it can contribute to the digital financial product design process: Generative AI is already actively used in many areas, significantly speeding up the work process and improving the quality of the outcomes. If we take into account the specifics of financial product design, then services like ChatGPT can be incredibly useful here, too. We are thus ready to share some secrets and tricks of using generative AI in financial UX. Try it, and the results will surprise you. Use ChatGPT to generate detailed personas and user journeys that reflect a wide range of demographics, psychographics and behaviors. How It Works: By crafting prompts that ask ChatGPT to create specific user profiles and scenarios, designers can uncover unique needs and pain points. For example: Benefit: This approach enhances empathy and ensures the app addresses the nuanced requirements of different user segments, leading to a more inclusive and effective design. Use ChatGPT to predict potential user reactions to new features or design changes prior to implementation. How It Works: Generate hypothetical reviews and feedback by asking: Benefit: Anticipating feedback allows designers to proactively address concerns, enhancing user satisfaction and reducing the need for post-launch fixes. Load thousands of customer reviews into ChatGPT to analyze, group and prioritize feedback, extracting actionable recommendations for improvement. How It Works: By inputting large datasets of user reviews into ChatGPT, AI can identify common themes, frequent complaints and areas of praise. For example: Benefit: This process provides a data-driven approach to UX enhancement, ensuring that updates directly address the most significant user concerns, thereby improving overall satisfaction. Review customer requests for new features using ChatGPT to identify the most frequently requested enhancements and understand how they could improve the customer experience. How It Works: Compile customer feature requests and input them into ChatGPT with a prompt like: Benefit: Prioritizing feature development based on customer demand ensures resources are invested in areas that will have the most significant impact on user satisfaction and engagement. Leverage ChatGPT to create insightful interview questions that uncover users' financial habits and challenges. How It Works: By designing prompts for tailored interview questions, you can gather deep insights into specific areas of user behavior. For example: Benefit: This approach leads to more targeted user research, helping you uncover nuanced issues and opportunities for improving the user experience in financial products. Employ ChatGPT to brainstorm ways to make the app more accessible to users with disabilities. How It Works: Craft prompts focused on accessibility improvements, such as: Benefit: Prioritizing accessibility not only broadens the user base but also demonstrates a commitment to inclusivity, enhancing the brand's reputation. Utilize ChatGPT to assist in creating detailed storyboards that visualize user interactions with the app, highlighting key touchpoints and user flows. How It Works: By prompting ChatGPT to outline step-by-step narratives of user interactions, designers can develop storyboards that capture the user's journey through the app. For example: Benefit: Storyboards help visualize and communicate complex user flows, making it easier for the design team to identify potential issues and opportunities for improvement in the user experience. Utilize ChatGPT to understand and design for the emotional experiences of users interacting with the app. How It Works: Ask AI to map out emotional stages. For example: Benefit: Addressing emotional needs fosters a deeper connection with users, promoting loyalty and positive word-of-mouth. Use ChatGPT to generate intuitive and user-friendly microcopy for financial services, ensuring customers feel informed and supported. How It Works: By asking ChatGPT to create microcopy for specific use cases, you can ensure the messages are clear, empathetic and concise. For example: Benefit: This enhances user confidence by providing helpful, easily understood communication, reducing frustration during critical moments like transactions or onboarding. Use ChatGPT to create realistic usability testing scenarios that explore how users interact with specific financial app features. How It Works: Generate scenarios that help reveal friction points in critical features of your app. For example: Benefit: Well-crafted scenarios help you assess the app's usability in real-world contexts, ensuring smoother user interactions with key financial tools. Leverage ChatGPT to explore successful UX strategies from unrelated industries and adapt them to banking. How It Works: Prompt AI to analyze features from gaming, social media, or e-commerce platforms that could enhance user engagement in a banking context. For instance: Benefit: This cross-pollination of ideas brings fresh perspectives, fostering innovation that sets the app apart from its competitors. Use ChatGPT to tailor the app's UX to different cultural contexts. How It Works: Generate insights on cultural preferences by prompting. For example: Benefit: Culturally sensitive designs enhance user comfort and acceptance in diverse markets, expanding the app's global reach. Engage ChatGPT to forecast emerging trends that could impact banking UX. How It Works: Prompt AI to predict technological advancements. For example: Benefit: Staying informed about future developments ensures the app remains relevant and competitive over time. Use ChatGPT to analyze reviews of competitors' apps to identify their UX strengths and weaknesses. How It Works: Input competitor app reviews into ChatGPT and prompt: Benefit: Understanding competitors' successes and failures allows designers to learn from them, avoid similar pitfalls and capitalize on opportunities to differentiate the app. Generate a comprehensive UX workflow plan with ChatGPT to guide the development and testing of financial app features. How It Works: ChatGPT can assist in outlining each step of the UX process, ensuring nothing is overlooked. For example: Benefit: This helps streamline the entire design process, ensuring all critical stages of UX -- from research to testing -- are carefully planned and executed. Generative AI is a powerful tool that enhances the capabilities of UX designers but will not replace them -- especially in the financial sector where complexity, ethics and human connection are paramount. UX designers bring indispensable qualities such as human empathy, ethical judgment, creativity and strategic thinking. Experienced designers bridge the gap between technology and human experience, ensuring that financial services are not only functional but also trustworthy, inclusive, delightful and user-centric. While ChatGPT is a powerful tool for generating ideas and hypotheses in UX design, it cannot provide live user data or empirical insights. The simulations and suggestions offered by ChatGPT should serve as a starting point for developing actual user research plans. To obtain valid and actionable insights, it is essential to engage directly with your digital service users through methods such as interviews, surveys and usability testing. By collaborating with AI, UX designers can leverage its strengths -- such as data analysis and rapid idea generation -- to augment their work. This symbiotic relationship enhances the design process, leading to more innovative and effective financial products. Ultimately, the human touch remains irreplaceable in crafting experiences that resonate deeply with users. Here are several reasons why generative AI will not replace UX designers specialized in financial products design in the future: Incorporating ChatGPT prompts into banking UX design processes adds significant value by enhancing creativity, collaboration and efficiency. It empowers product teams to make data-driven decisions, improve user experiences and stay ahead of industry trends. While ChatGPT supports and enhances the work of product teams, it complements rather than replaces the human expertise required for designing intuitive and empathetic user interfaces. In the future, generative AI will significantly assist the UX design process by offering data-driven insights and enhancing creativity. However, it will still lack the human intuition, empathy and strategic thinking that professional UX designers bring to the table. In the context of financial services, where user trust, security and satisfaction are paramount, the human-centered approach of UX designers will remain irreplaceable. AI will serve as a powerful tool to augment the designer's work but will not fully replicate the nuanced expertise required to create truly effective and empathetic financial interfaces. However, embracing this approach positions financial product designers at the forefront of digital innovation, ready to meet the challenges of the future with confidence and creativity. Incorporating Generative AI like ChatGPT into the digital financial services design and development process can lead to significant improvements and innovations in the user experience. By integrating AI prompts into the design process, financial companies can create more intuitive, engaging and user-centered apps that meet the evolving needs of their customers. The addition of customer and competitor review analysis, along with feature request insights, empowers designers with actionable information. Here are some final best practices for using ChatGPT prompts:

Finextra Research

Mon, 14 Oct, 10:13 AM UTC

Impacts of AI revealed in TestRail report

Artificial Intelligence Impacts of AI revealed in TestRail report Tuesday, October 15, 2024 Richard Harris TestRail's latest report, "Exploring the Impact of AI in QA," analyzes insights from over 1,000 QA professionals to provide a realistic view of AI's role in quality assurance. It highlights AI-driven efficiency, adoption barriers, and future optimism for AI's transformative potential. TestRail announced its latest report, "Exploring the Impact of AI in QA." Based on the QA industry's first AI-focused research survey, this comprehensive report draws on insights from over 1,000 QA professionals and aims to cut through the hype surrounding artificial intelligence, offering a clear and accurate picture of how QA teams are adopting, planning for, and responding to AI technology. The research explores AI's applications in areas such as regression testing, test automation, and performance testing, revealing how AI is helping teams increase efficiency, improve test coverage, and enhance overall quality. Key impacts of AI, according to TestRail's latest report AI Adoption and Success: A significant 65% of survey respondents reported using AI in their QA processes, with AI being applied uniformly across various testing types. However, certain use cases show more potential than others. AI-Driven Productivity Gains: Over 50% of respondents reported increased productivity and improved test coverage, underscoring AI's potential to enhance testing efficiency. AI's Versatility: AI is proving effective across various testing types, including regression, smoke, and performance testing. It is being used to generate test cases, execute tests, and analyze results, allowing human testers to focus on strategic tasks. Barriers to Adoption: Despite high adoption rates, challenges like AI's complexity, concerns about data privacy and security, and uncertainty about its benefits continue to hinder broader implementation. Actionable Tips: The report also offers practical tips, strategies, and prompt ideas from industry experts and survey respondents, empowering QA managers to start leveraging AI in their own processes today. Most importantly, the report also details the QA community's overwhelmingly optimistic outlook on the future of AI, despite adoption challenges -- a perspective that TestRail fully supports. Exploring the Impact of AI in QA "Although it's still early to gauge AI's full impact on QA, we think the future looks bright. Like test automation before it, we're optimistic that AI will not only speed up release cycles and improve software quality but also empower testers to spend more time on tasks that require human insight and intuition. As long as software is made for people, the human element in testing will remain essential," said Judy Bossi, VP of Product at Idera. AI can assist with various stages of the QA process, making life easier for QA professionals. From crafting test cases to analyzing results, QA teams are seeing success leveraging AI for a wide assortment of quality tasks. Here's a look at a few ways it's being used: Creating and managing test cases: AI helps design test cases more quickly and efficiently and even prioritizes them based on risk. Automating tests: With AI, writing and refining test scripts is faster and easier. It also helps to debug and keep test cases up to date. Handling test data: AI generates realistic synthetic data, masks sensitive information, and speeds up data preparation. Analyzing results: AI enhances how we analyze performance, predict defects, and review test outcomes, providing deeper insights into application health. Debugging code: AI offers valuable assistance in analyzing code, suggesting fixes, and spotting anomalies, which speeds up the debugging process. These examples show just how integrated AI is becoming in the QA process, helping to make testing more efficient and effective. The survey found that 54% of respondents experienced a modest boost in productivity and coverage, and 43% saw a significant improvement. These results confirm that AI is quickly proving its usefulness l in QA, delivering real benefits and setting the stage for even greater advancements as the technology evolves. The survey results revealed that AI in QA is still finding its footing. Early indications are positive, but QA professionals are still figuring out the best ways to integrate AI into their testing processes. Even though AI is relatively new and often discussed with a focus on its risks and uncertainties, those who are already using it are genuinely optimistic. This optimism is a clear sign that, despite the hurdles, AI is making a real impact and people are excited about what's to come. Become a subscriber of App Developer Magazine for just $5.99 a month and take advantage of all these perks. MEMBERS GET ACCESS TO- Exclusive content from leaders in the industry - Q&A articles from industry leaders - Tips and tricks from the most successful developers weekly - Monthly issues, including all 90+ back-issues since 2012 - Event discounts and early-bird signups - Gain insight from top achievers in the app store - Learn what tools to use, what SDK's to use, and more Subscribe here Impacts of AI revealed in TestRail report, AI adoption, QA processes, Test automation, Regression testing, Productivity gains, Data privacy, Testrail, AI Technology share

App Developer Magazine

Tue, 15 Oct, 8:28 PM UTC

Automatically Research Anybody with ChatGPT and Perplexity

Imagine being able to gather detailed insights about anyone, anywhere, without spending countless hours sifting through endless streams of information. In our hyper-connected world, where time is a precious commodity, the ability to efficiently research individuals can be a fantastic option. Whether you're a recruiter seeking the perfect candidate, a salesperson looking to understand potential clients, or simply someone preparing for a crucial meeting, having a comprehensive profile at your fingertips can make all the difference. This article explores how AI tools like ChatGPT and Perplexity, paired with automation software Make, can transform the way you conduct research, offering a seamless, time-saving solution that might just transform your professional life. But how exactly does this work, and what makes it so effective? By setting up a smart workflow that taps into platforms like LinkedIn, you can automate the process of gathering and organizing information, making sure you have the most relevant data at your disposal whenever you need it. This isn't just about saving time; it's about enhancing accuracy and gaining deeper insights that empower you to make informed decisions. As we provide more insight into the specifics, you'll discover how easy it is to integrate these tools into your daily routine, potentially unlocking a new level of productivity and strategic advantage. In today's fast-paced digital landscape, efficient research has become a cornerstone of success for professionals across diverse industries. The integration of AI tools like ChatGPT and Perplexity, combined with powerful automation software such as Make, is transforming the way we gather and process information. AI tools are at the forefront of this research revolution, offering unprecedented capabilities in data collection and analysis. ChatGPT and Perplexity, two leading AI platforms, excel at: By using these AI capabilities, you can automate complex research tasks that would typically require hours of manual effort. The AI's ability to understand context and extract relevant information ensures that the data gathered is not just voluminous, but also highly pertinent to your specific research needs. The key to maximizing the potential of AI and automation lies in creating a well-structured workflow. Here's how you can build an efficient system: 1. Set up a Notion database as your central information hub. This serves as the backbone of your research organization, allowing you to: 2. Integrate LinkedIn profile scanning into your workflow. This can be achieved by: 3. Use Make (formerly Integromat) to connect your various tools and automate the flow of information. This automation software acts as the glue binding your research ecosystem together. By implementing this workflow, you shift your focus from tedious data collection to high-value analysis and decision-making based on the gathered information. Find more information on AI tools by browsing our extensive range of articles, guides and tutorials. Setting up your AI-powered research system involves several key steps: 1. Configure Make to connect with Notion, making sure smooth data transfer between platforms. 2. Integrate the OpenAI API (for ChatGPT) and Perplexity API into your Make workflow. This allows you to harness the full potential of these AI tools for data processing and analysis. 3. Set up LinkedIn profile scanning within Make, defining the parameters for data extraction. 4. Create blueprints in Make to streamline the setup process, making it easier to replicate and modify your workflow as needed. 5. Establish error handling and notification systems to ensure smooth operation and alert you to any issues that may arise. This technical foundation ensures that your research process operates efficiently, providing you with accurate, up-to-date information without manual intervention. One of the most powerful aspects of this AI-driven research system is its adaptability. You can tailor the workflow to suit a wide range of professional needs: Furthermore, you can expand the system by incorporating additional data sources, such as: This flexibility allows you to create a truly customized research tool that evolves with your professional requirements. Implementing an AI-powered research system is not only efficient but also cost-effective. Many of the tools involved offer: This accessibility ensures that professionals from various sectors and organizations of different sizes can benefit from advanced research automation without significant upfront costs. The implementation of an AI and automation-driven research system yields substantial benefits: 1. Time savings: Automate hours of manual research, freeing up valuable time for strategic tasks. 2. Enhanced accuracy: Reduce human error in data collection and processing. 3. Comprehensive insights: Gather more detailed and diverse information than manual methods allow. 4. Scalability: Easily increase research capacity without proportional increases in time or resources. 5. Consistency: Ensure uniform data collection and processing across all research subjects. By using AI tools like ChatGPT and Perplexity alongside automation software, you transform your research capabilities. This approach not only streamlines the process but also provides deeper, more actionable insights. As a result, you're better equipped to make informed decisions, identify opportunities, and stay ahead in your professional field. The future of research is here, and it's powered by AI and automation.

Geeky Gadgets

Thu, 31 Oct, 2:10 PM UTC

Slideteam AI review: An honest look

Creating presentations can be a time-consuming task, especially when dealing with complex topics. Slideteam AI claims to simplify this process by using AI to generate professional presentations in just a few clicks. We took this tool for a spin to see how well it delivers on its promises. Slideteam AI is an AI-powered presentation creation tool designed to streamline the process of building informative and engaging slideshows. The tool aims to assist users in creating well-structured, visually appealing presentations without spending hours on content generation and design. Below are some of the main features that make Slideteam AI stand out: We tested Slideteam AI by creating a presentation on greenwashing. The process was straightforward, and we were able to generate a comprehensive set of slides in a relatively short amount of time. Below, we provide a detailed breakdown of the steps we followed: Using Slideteam AI can significantly speed up the process of creating a presentation, but there are some best practices to ensure you get the most out of the tool. The more detail you provide in the initial form, the better the AI can tailor the presentation to your needs. Make sure to include clear objectives, intended audience, and a well-organized document if you decide to upload additional content. This will help the AI generate slides that are more focused and relevant. While the AI-generated outline is a great starting point, it's important to spend some time refining it. Adding specific points or reorganizing sections can improve the presentation's flow and ensure that all important aspects of the topic are covered. Tailoring the outline to your audience can make a significant difference in the effectiveness of your presentation. Choosing an appropriate theme is crucial for the overall tone of the presentation. Slideteam AI provides a range of visual templates, each suited to different presentation styles. Select a theme that aligns with your audience and the nature of your topic -- a professional theme for a business presentation or a more colorful one for creative content. Once the presentation is generated, it's always a good idea to review the slides carefully. Although the AI does a good job at generating content, there may be some slides that require slight modifications to better align with your message or to add personal touches. Reviewing also ensures that the content is accurate and appropriately reflects your key points. AI-generated presentations can sometimes lack the personal touch that makes content truly engaging. Consider adding anecdotes, real-world examples, or your own insights to make the presentation more relatable to your audience. This will help bridge the gap between AI-generated content and your personal expertise. Slideteam AI offers various pricing plans that cater to both individual and team needs. Below is a breakdown of the available options: Well, Slideteam AI delivers on its promise of simplifying the presentation creation process. It works well, generating structured, visually appealing content in a short time. The AI can save significant effort, especially for users needing a quick draft to build on. It's not perfect -- some manual edits are still necessary -- but overall, it works fine for creating informative slides without the usual hassle. For users who need to produce presentations quickly and efficiently, Slideteam AI can be a useful tool, but it's always best to add your own final touches to ensure the content resonates with your audience. Even though Slideteam AI worked out fine for our needs, there are other tools that you might consider exploring. Below are some alternative AI-powered presentation tools that we've reviewed. Each of these options offers unique features, and you can visit the provided links for more detailed information. Gamma.app offers an innovative way to create presentations by focusing on content first and design second. This tool uses AI to adapt the presentation layout to suit the content provided, making it an excellent choice for users who want flexibility in their presentations. Tome AI is an AI-driven presentation tool designed to help users create dynamic and visually appealing slideshows. It focuses on making storytelling easy, with AI assisting users in generating content that flows naturally. Beautiful AI is a presentation tool that emphasizes design simplicity and automation. It helps users create clean, professional-looking slides without needing design expertise. This tool is especially useful for creating visually consistent slideshows. Decktopus is another AI-powered presentation tool that aims to simplify the creation of presentations with its easy-to-use interface and customizable templates. Decktopus provides a quick way to build informative slides without spending too much time on design.

Dataconomy

Thu, 24 Oct, 4:52 PM UTC

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