Qualitative insights: Reimagined and supercharged 🚀
We're thrilled to announce the re-launch of our Qualitative Insights tool, formerly known as Reframer. This powerful upgrade brings new features designed to revolutionize your qualitative data analysis process, making it faster, easier, and more insightful than ever before.
Introducing the new Qualitative Insights 🔍
Qualitative Insights has always been your go-to tool to help you plan and organize interviews, take notes, tag, and analyze rich, unstructured data. Now, we've taken it to the next level with two game-changing additions:
Insights feature: A dedicated space to capture, organize, and communicate your key takeaways.
AI capabilities: Optional AI-powered assistance to accelerate your analysis process.
Discover insights effortlessly 💡
The new Insights feature transforms how you work with qualitative data:
Centralized hub: All your analytical discoveries in one place.
Structured insights: Each insight includes a title, detailed description, and associated observations.
Flexible viewing: Toggle between overview and deep-dive modes.
Efficient organization: Tag and categorize insights for easy retrieval.
Collaboration tools: Share and discuss findings with your team.
How it works 🛠️
Manual insight creation
Filter your data using keywords, tags, affinity map groupings, tasks, segments, and sessions.
Select relevant observations.
Craft your insight with a custom title and description.
AI-Powered Insight Generation (Optional)
Click "Generate" to activate our AI assistant.
AI analyzes existing observations to produce new insights.
Automatically generates insight titles, summaries, and attaches relevant observations.
AI-generated insights are marked with an AI star symbol for easy identification.
All AI insights remain fully editable.
AI: Your analysis assistant 🤖
Our AI capabilities are designed to enhance your abilities, not replace them. Use AI to:
Speed up insight discovery
Reveal hidden patterns in your data
Jumpstart the analysis process
Remember, your expertise is crucial. Always review and refine AI-generated insights to ensure accuracy and capture nuances that only human understanding can provide.
Your data, your choice 🔒
We prioritize your privacy and data control:
Your data stays within your organization
We don't use it to train other AI models
You control when to use AI for insights
AI features can be turned on or off anytime
Get started today 🌟
Ready to experience the power of the new Qualitative Insights? Learn more and dive in. Upgrade your qualitative analysis workflow and uncover deeper insights faster than ever before with Qualitative Insights!
We're thrilled to announce the re-launch of our Qualitative Insights tool, formerly known as Reframer. This powerful upgrade brings new features designed to revolutionize your qualitative data analysis process, making it faster, easier, and more insightful than ever before.
Introducing the new Qualitative Insights 🔍
Qualitative Insights has always been your go-to tool to help you plan and organize interviews, take notes, tag, and analyze rich, unstructured data. Now, we've taken it to the next level with two game-changing additions:
Insights feature: A dedicated space to capture, organize, and communicate your key takeaways.
AI capabilities: Optional AI-powered assistance to accelerate your analysis process.
Discover insights effortlessly 💡
The new Insights feature transforms how you work with qualitative data:
Centralized hub: All your analytical discoveries in one place.
Structured insights: Each insight includes a title, detailed description, and associated observations.
Flexible viewing: Toggle between overview and deep-dive modes.
Efficient organization: Tag and categorize insights for easy retrieval.
Collaboration tools: Share and discuss findings with your team.
How it works 🛠️
Manual insight creation
Filter your data using keywords, tags, affinity map groupings, tasks, segments, and sessions.
Select relevant observations.
Craft your insight with a custom title and description.
AI-Powered Insight Generation (Optional)
Click "Generate" to activate our AI assistant.
AI analyzes existing observations to produce new insights.
Automatically generates insight titles, summaries, and attaches relevant observations.
AI-generated insights are marked with an AI star symbol for easy identification.
All AI insights remain fully editable.
AI: Your analysis assistant 🤖
Our AI capabilities are designed to enhance your abilities, not replace them. Use AI to:
Speed up insight discovery
Reveal hidden patterns in your data
Jumpstart the analysis process
Remember, your expertise is crucial. Always review and refine AI-generated insights to ensure accuracy and capture nuances that only human understanding can provide.
Your data, your choice 🔒
We prioritize your privacy and data control:
Your data stays within your organization
We don't use it to train other AI models
You control when to use AI for insights
AI features can be turned on or off anytime
Get started today 🌟
Ready to experience the power of the new Qualitative Insights? Learn more and dive in. Upgrade your qualitative analysis workflow and uncover deeper insights faster than ever before with Qualitative Insights!
Investing in prototype testing and user-focused design isn't just about creating better products—it's a proven strategy to save costs, accelerate timelines, and drive customer loyalty. According to Forrester Research, companies that incorporate prototype testing in their design process can reduce development costs by 33% and cut collaboration time by 25%. UX-focused companies also see products hit the market 50% faster and loyalty rise by 240% (Forrester Research, Nielsen Norman Group)!
Whether you're refining user flows, testing new concepts, or optimizing your onboarding experience or conversion flows, prototype testing helps ensure your designs hit the mark—before you invest too heavily in the build.
With those benefits in mind, let's dive into how prototype testing can help you deliver user-centered designs efficiently and effectively.
Common Use Cases for Prototype Testing
Test Onboarding and Sign-Up Flows How intuitive is your onboarding process? Prototype testing can help identify friction points, ensuring users can navigate and complete sign-ups seamlessly. For example, you can simulate different scenarios to determine whether users can easily register, set up accounts, or retrieve forgotten passwords.
A/B Test Email Designs Test different layouts, calls-to-action (CTAs), or visual elements in your email prototypes to discover what resonates best with your audience. Measure metrics like click-through rates or time spent engaging with content to refine your design.
Evaluate User Flows and Wireframes Whether you're testing a new feature, redesigning a user journey, or validating a wireframe, prototype testing gives you real-world insights. Observe how users interact with your design and identify areas for improvement before you move to development.
Test Concepts Before launching a new idea, validate it through prototype testing. Let users interact with your concept to gauge feasibility and potential impact. This can save time and resources by helping you focus on ideas that resonate.
Evaluate Conversion Flows Are users completing purchases or achieving desired outcomes? Use prototype testing to analyze conversion flows and pinpoint where users drop off. From landing pages to payment processes, you can optimize every step for success.
Test User Interfaces (UI) Ensure your UI elements—buttons, navigation menus, or forms—are intuitive and accessible. Prototype testing can help you identify design inconsistencies or usability challenges early in the process.
Conduct Usability Tests Have a new feature in development? Prototype testing lets you see how users interact with it, revealing insights that can guide refinements and improve overall satisfaction.
Real-Life Prototype Testing Scenarios
Airline Imagine your flight has been canceled. Ask how your customers self-service on the airline website to find new flight options.
Bank Have a prospect or customer interact with a prototype to open a business account online. Uncover usability issues and streamline the process.
Insurance Imagine you’re interested in switching car insurance. Explore how intuitive it is for customers to view coverage details in an app, helping insurers improve navigation and accessibility.
Prototype Testing Analysis & Insights
Optimal’s prototype testing gives you a variety of analysis options to help you to evaluate the effectiveness and usability of your prototypes. Use these to see exactly how users navigate, where they face challenges, and what areas are proving to be successful.
Task-based scenarios: Observe how users complete tasks like purchasing a product or updating account settings and set correction paths and destinations.
Clickmaps: See how users navigate and locate information. See hits and misses on designated clickable areas, average task completion times, and heatmaps showing where users believed the next steps to be.
Task results: Gather insights into how long it took to take a task (time taken), misclicks, directness score (considering backtracks or incorrect pathways), and success score.
Participant paths: The Paths tab provides a powerful visualization, including thumbnails, to understand and identify common navigation patterns and potential obstacles participants encounter while completing tasks.
Video, audio, and/or screen recording: See how your users interact with and respond to your prototype. Listen to their thought process and pick up on nonverbal cues, like hesitation, frustration, or confusion to pinpoint areas for improvement or exploration.
Ready to use prototype testing to help your team reduce development costs and get a faster time to market? Get started in your account by creating a new prototype test.
In the last few years, the influence of AI has steadily been expanding into various aspects of design. In early 2023, that expansion exploded. AI tools and features are now everywhere, and there are two ways designers commonly react to it:
With enthusiasm for how they can use it to make their jobs easier
With skepticism over how reliable it is, or even fear that it could replace their jobs
Google UX researcher Clara Kliman-Silver is at the forefront of researching and understanding the potential impact of AI on design into the future. This is a hot topic that’s on the radar of many designers as they grapple with what the new normal is, and how it will change things in the coming years.
Clara’s background
Clara Kliman-Silver spends her time studying design teams and systems, UX tools and designer-developer collaboration. She’s a specialist in participatory design and uses generative methods to investigate workflows, understand designer-developer experiences, and imagine ways to create UIs. In this work, Clara looks at how technology can be leveraged to help people make things, and do it more efficiently than they currently are.
In today’s context, that puts generative AI and machine learning right in her line of sight. The way this technology has boomed in recent times has many people scrambling to catch up - to identify the biggest opportunities and to understand the risks that come with it. Clara is a leader in assessing the implications of AI. She analyzes both the technology itself and the way people feel about it to forecast what it will mean into the future.
What role should artificial intelligence play in UX design process? 🤔
Clara’s expertise in understanding the role of AI in design comes from significant research and analysis of how the technology is being used currently and how industry experts feel about it. AI is everywhere in today’s world, from home devices to tech platforms and specific tools for various industries. In many cases, AI automation is used for productivity, where it can speed up processes with subtle, easy to use applications.
As mentioned above, the transformational capabilities of AI are met with equal parts of enthusiasm and skepticism. The way people use AI, and how they feel about it is important, because users need to be comfortable implementing the technology in order for it to make a difference. The question of what value AI brings to the design process is ongoing. On one hand, AI can help increase efficiency for systems and processes. On the other hand, it can exacerbate problems if the user's intentions are misunderstood.
Access for all 🦾
There’s no doubt that AI tools enable novices to perform tasks that, in years gone by, required a high level of expertise. For example, film editing was previously a manual task, where people would literally cut rolls of film and splice them together on a reel. It was something only a trained editor could do. Now, anyone with a smartphone has access to iMovie or a similar app, and they can edit film in seconds.
For film experts, digital technology allows them to speed up tedious tasks and focus on more sophisticated aspects of their work. Clara hypothesizes that AI is particularly valuable when it automates mundane tasks. AI enables more individuals to leverage digital technologies without requiring specialist training. Thus, AI has shifted the landscape of what it means to be an “expert” in a field. Expertise is about more than being able to simply do something - it includes having the knowledge and experience to do it for an informed reason.
Research and testing 🔬
Clara performs a lot of concept testing, which involves recognizing the perceived value of an approach or method. Concept testing helps in scenarios where a solution may not address a problem or where the real problem is difficult to identify. In a recent survey, Clara describes two predominant benefits designers experienced from AI:
Efficiency. Not only does AI expedite the problem solving process, it can also help efficiently identify problems.
Innovation. Generative AI can innovate on its own, developing ideas that designers themselves may not have thought of.
The design partnership 🤝🏽
Overall, Clara says UX designers tend to see AI as a creative partner. However, most users don’t yet trust AI enough to give it complete agency over the work it’s used for. The level of trust designers have exists on a continuum, where it depends on the nature of the work and the context of what they’re aiming to accomplish. Other factors such as where the tech comes from, who curated it and who’s training the model also influences trust. For now, AI is largely seen as a valued tool, and there is cautious optimism and tentative acceptance for its application.
Why it matters 💡
AI presents as potentially one of the biggest game-changers to how people work in our generation. Although AI has widespread applications across sectors and systems, there are still many questions about it. In the design world, systems like DALL-E allow people to create AI-generated imagery, and auto layout in various tools allows designers to iterate more quickly and efficiently.
Like many other industries, designers are wondering where AI might go in the future and what it might look like. The answer to these questions has very real implications for the future of design jobs and whether they will exist. In practice, Clara describes the current mood towards AI as existing on a continuum between adherence and innovation:
Adherence is about how AI helps designers follow best practice
Innovation is at the other end of the spectrum, and involves using AI to figure out what’s possible
The current environment is extremely subjective, and there’s no agreed best practice. This makes it difficult to recommend a certain approach to adopting AI and creating permanent systems around it. Both the technology and the sentiment around it will evolve through time, and it’s something designers, like all people, will need to maintain good awareness of.
