Tool Information
Hubble is an in-product user research and feedback platform that enables companies to create world-class products by gathering high-quality contextual feedback from targeted users. With Hubble, companies can collect in-product feedback through SDK, prototype concept testing and create qualitative research questions and build study templates through the use of ChatGPT by OpenAI. It also allows companies to segment users based on their attributes and track results in real-time for summary analysis and create beautiful reports. Heat maps and video clips are also available for understanding customer flow. Companies can also create customized, unmoderated studies to collect any type of product feedback from usability testing to feature satisfaction. All this is available in a user-friendly platform that makes product research 10x easier.
F.A.Q (20)
Hubble.team is an in-product user research and feedback platform. It enables companies to gather high-quality contextual feedback from targeted users, facilitating the creation of world-class products. In-product feedback can be collected through SDK, prototype concept testing, and the creation of qualitative research questions through the use of ChatGPT by OpenAI. Hubble's platform includes user segmentation, real-time result tracking, report generation, heat maps, video clips, and customizable unmoderated studies.
Through Hubble's SDK, feedback is collected in-product. This allows companies to highlight product features, components, and user flows to collect detailed user feedback at scale.
Prototype concept testing in Hubble allows for the testing of concepts and prototypes before a real product is built. This involves the creation of click-through interactive tests by simply copying and pasting a Figma working prototype.
Hubble makes use of ChatGPT by OpenAI to create qualitative research questions and build study templates. Through this collaborative conversation-based model, comprehensive insights into user preferences, behaviour, and feedback can be generated.
The Hubble x ChatGPT feature is a qualitative research tool that leverages the capabilities of OpenAI's ChatGPT. It enables the creation of study templates and the formulation of research questions. It's useful in understanding user behaviour, collecting contextually rich feedback, and helping teams make better-informed decisions based on user insights.
Hubble offers a feature that allows companies to segment users based on their attributes. This aids in targeting the right users during product usage, ensuring that insights are gleaned from actual users. Thus, feedback gathered is relevant and authentic.
Yes, Hubble provides a feature for companies to track results in real-time. This provides constant insights into user interactions, helping teams make timely decisions.
Yes, Hubble allows companies to create beautiful, auto-generated reports. These reports can be shared within the team to disseminate insights and facilitate cross-functional collaboration.
Heat maps in Hubble provide actionable insights from individual participants. They show patterns of user interaction with the product, indicating areas that receive the most attention and those that get overlooked. These visual representations allow for an easy understanding of user behaviour towards different product features.
Yes, Hubble provides video clips for understanding customer flow. These recorded clips for live studies assist in understanding your customer's journey and interaction with the product in a better way.
Hubble allows for the customization of unmoderated studies. This feature elevates research capabilities and enables the collection of any type of product feedback, ranging from usability testing to feature satisfaction and concept tests.
Hubble aids in collecting feedback related to feature satisfaction by facilitating the creation of customized unmoderated studies. These studies get contextually rich and precise feedback from the actual users about their satisfaction with different product features.
In terms of usability testing, Hubble gathers feedback related to the functionality and user-friendliness of a product. It collects user reactions to various aspects of the product, including simplicity of use, navigation, design aesthetics, error handling, and overall user satisfaction.
Hubble can be used in a variety of scenarios. This includes prototype concept testing before the actual product is built, in-product surveys for collecting feedback at scale, creation of research questions with Hubble x ChatGPT, and use of customizable, unmoderated studies for collecting any type of product feedback.
Despite its vast features, Hubble is designed to be user-friendly. It simplifies the process of product research, making it up to 10x easier than traditional methods.
Hubble differentiates from traditional user research platforms by offering in-product user research, eliminating the need for survey emails or research calls. It gathers feedback from real users during product usage, synchronizing user research with their interactions, unlike traditional platforms that often miss this contextual richness.
Hubble's platform allows companies to directly engage with their users, negating the need for external panel recruitment. It cuts costs associated with recruiting panels externally, making the whole process more efficient and cost-effective.
Hubble collects high-quality feedback from real users by focusing on in-product user research. By asking users to provide feedback while they're actively using the product, Hubble gathers authentic, contextual, and relevant insights.
Study templates in Hubble can be used to create a wide variety of studies. These include usability tests, feature satisfaction assessments, design preference tests, concept tests, and many others. The templates make the process more streamlined and efficient.
Hubble simplifies product research by providing an all-in-one platform that facilitates gathering in-product feedback directly from users. This method reduces recruitment costs, eliminates research calls and survey emails, and allows for real-time results tracking and auto-generated reports. User segmentation and customizable studies further the efficiency of the process, making product research significantly easier.
Pros and Cons
Pros
- In-product user research
- High-quality contextual feedback
- Feedback collection through SDK
- Prototype concept testing
- Enables qualitative research questions
- User segmentation based on attributes
- Real-time result tracking
- Summary analysis with reports
- Heat maps and video clips
- Customized
- unmoderated studies
- Usability testing capability
- Feature satisfaction feedback
- User-friendly platform
- Efficient product research
- No need for survey emails
- Interactive tests with Figma prototype
- Contextual user feedback at scale
- Aggregated data access
- Collecting and comparing respondent metadata
- Screen recording for live studies
- Design concept validation
- Design preference testing
- Auto-generated reports
- Ability to target users
- Collaboration with cross-functional partners
Cons
- High external panel recruitment costs
- Requires SDK for feedback collection
- No sync with traditional platforms
- Lack of real-time interview support
- Customization limited to studies
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