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Link repositories to a software project

Keep track of your team’s work by linking code repositories from connected development tools to your software project .

Before you begin

Before you can link repositories to your software project , you must complete the following steps:

Enable the code feature in your project. How to enable Code

Connect Jira to Bitbucket, GitHub or another supported source code management tool. Read more about integrating Jira with your development tools

Make sure your tool is configured properly so it can send development information to Jira .

Link your team’s repositories

The Code feature displays a list of the repositories that are linked with your project, helping you keep track of where your team is working. It can display up to 100 linked code repositories.

Link repositories using issue keys

You can link a repository to a project by including issue keys in your branch names, commit messages, and pull requests. Here’s how:

Find the key for the Jira issue you want to link to, for example “JRA-123”.

Checkout a new branch in your repository, using the issue key in the branch name. For example, git checkout -b JRA-123-<branch-name> .

When committing changes to your branch, use the issue key in your commit message. For example, git commit -m "JRA-123 <summary of commit>" . You can also include the issue key in the pull request title.

After you commit your changes or push your branch, go to Code in the project menu to see the connected repository. It can take a few minutes for the connection to finish.

How to reference issues in your development work

Link repositories using the toolchain feature

Project admins can link repositories to a software project using the toolchain feature. You can connect multiple code repositories from Bitbucket, GitHub, GitLab, or any other supported tool, and these will display on the code page in your project.

Select Project settings from your project menu, then select Toolchain .

From the top right, select Add , then select Add code repository .

Select your preferred code tool. You may need to install or authenticate the tool.

Select your team’s repository from the list.

If the tool is already listed in your toolchain, you can connect work from the tool’s card.

Select the add ( ) icon.

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Using Jira as a research repository, part one: pros & cons

I built a research repository in Jira and wanted to get my process down in writing for those in the same boat I was in: weighing the pros and cons of Jira without a guide.

UX repositories are critical, but selecting the right platform for your organization is not easy. Since I created our repository I have heard from many people wondering specifically about using Jira and whether it can work despite not being designed as a research repository.

I wanted to get my process down in writing for those in the same boat I was in: weighing the pros and cons of Jira without a guide.

This article is two parts: in Part One I share our selection process, in Part Two our steps for creating the actual Jira project. I hope you find something useful here and it saves you some time.

Why a research repo?

When I joined my current organization I found there was really valuable research data already coming in from our user base through multiple feedback channels. But if it didn’t find its way into a current project it was just getting lost. We were not only losing opportunities to know our products and users better, but we were also wasting time (and frustrating stakeholders) by asking them the same questions again and again times.

A repository for our research data was clearly needed. We set out to research and build a solution.

Without a repository we were losing opportunities to know our products and users better, and wasting time asking the same questions over and over again.

Our goal was to support continuous user research, build a repository of “timeless” data that would increase in value and usefulness over time, and make it easily searchable and available to all members of the team.

Part One: Why we selected Jira for our research repository

It’s an exciting time to do User Research. There is so much innovation happening right now and new tools coming on the market. At the same time the field is still rather new and there is no established user research taxonomy (though it’s one of the topics the wonderful Research Ops project is trying to address). Every organization that goes down this road is in some ways forging their own new path.

Selecting the right platform for a repository, one that will serve your organization over the long term, is not easy. Kate Towsey curates this great list of tools , and it’s a wonderful place to get started thinking about your software needs, but even this list has limited options for research repositories.

In the end, it’s just a database

One important point to keep in mind is that a research repository is a database, pure and simple. It might be bedazzled with features and options, but at it’s heart its a big ol’ table. There are a lot of software options for creating a database table (an excel document or custom sql among them), the question is simply how to make sure you have the fields you need, that it’s manageable for your team, and you can create the views that give you insight into the data.

Our decision table

There is a lot to weigh when selecting the software for your organization’s research repository. How much data will you eventually store, and how quickly will it be coming in? What is the technical expertise — and size — of the team who will be managing the repo? What custom needs does your organization have? And what is your budget?

We asked all those questions and more, as well as considering the deliverables we would need to extract from the data. Who will be reading it, what kinds of questions will they want to answer, and how quickly can they glean that information?

We explored many software options in our quest for the right fit. Below is our decision table with the “Final 7” software options that made the cut for more testing:

Jira: the imperfect best choice

Ultimately Jira emerged as the best — if imperfect — fit for our research repository. The strongest draw for our team was distributed access to the data: the entire organization is already heavily invested in Jira for handling software tickets. We all use the platform on a daily basis, reducing barriers to shared entry.

Here is how Jira held up against our most important criteria:

Cost: Jira was a good fit for our organization on cost because we were already using it for software development tracking. No additional cost.

Data security: Jira cloud encrypts all their data and uses industry-standard accounts management.

Will it be sustainable by a small UX team? We felt we would be able to harness our existing experience using Jira — and it’s integrations with other software — to get more out of this tool with a small team.

Will it integrate well into our workflow? Because of our existing Jira use for software development this was a yes.

Distributed access to data: This was the strongest point for us, and ultimately the reason why we chose Jira. Our entire team is already invested in, and interacts daily with, the Jira interface. Switching to a different project to view relevant research data is a fairly easy step, even for a busy designer or developer.

If the data isnt seen when it’s needed — by the people that need it — then it’s useless, no matter how great the software or how well the data is organized. Using Jira would bring the data closer to the teams that need it.

Creating actionable items: Another important benefit was the ability to turn insights from the UX repo into actionable backlog items right within Jira. They would immediately be seen by our development team in a language native to their workflow, no further translation necessary.

Stability: Similar to data security, we felt secure in Atlassian’s size and category dominance.

Export/Import data: Especially at this early stage in the development of Research Ops, import/export functions will help you preserve your data beyond any one software solution. Its also a huge timesaver when working with large data sets.

Directly contact users: Jira does not have this capability, even with marketplace addons. I havn’t yet found a good solution that offers both research repo and CRM functions at a high level, it’s the unicorn of UX repos I suppose. We opted for separate solutions.

AI-assisted insights: We also ended up not meeting this criteria. Nice, but not a dealbreaker)

Is the software UX focused? Jira is not UX focused, we had to bend it to our will, but it ultimately did what we needed. I share our tips in detail in the second part of this article; They might save you time.

Data types: Jira met our primary need for storing atomized and qualitative feedback. We found our quantitative data had a shorter lifespan than descriptive feedback so that was not our primary focus.

Data source fidelity: We can use Jira’s linking function to link back to original observations in bug and feature tickets. Linking back to the original research right within the ticket provides further context for developers, as well as validation. Jira’s linking function is a simple way to chip away at the discovery-knowledge gap.

If you think Jira is a good fit for your team’s research repository but arent familiar with customizing a Jira project, Part two of this article shares a step-by-step of how we created our user research repository.

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The complete UX research repository guide for 2024

After you finish a research project, your hard-earned insights shouldn’t be left to fend for themselves. That’s how they get lost in inboxes, folders, or worse — the trash.

You need a home for your findings, one that's as easy to organize today as it is to search at a moment’s notice years later.

You need a UX research repository.

Without a central repository, your research efforts can become inefficient and even wasteful. Research lives scattered across multiple tools without a consistent format for collecting, synthesizing, and analyzing data. This makes it difficult to share what you learn to inform your organization’s key product decisions.

In this guide, we’ll cover all things research repositories – from definitions, benefits, and tools, to tips for building a healthy repository that enables your company to successfully conduct, organize, store, and access research.

Let’s get started.

What is a UX research repository?

A UX research repository — "repo" for short — is a central place to store, organize, and share an organization’s research artifacts and insights.

Think of it as a digital library dedicated to your company’s research knowledge and data.

Today, most research repositories are cloud-based. Content found in a repository typically falls into one of two broad categories:

• Input used in conducting UX research — information for planning and undertaking research.
• Output derived from conducting UX research, which may include the study’s findings and reports.

At the organizational level, the ideal repository should promote and advance UX research awareness by welcoming participation from leadership, product owners, and other cross-functional stakeholders. It should also encourage operationally-sound habits and practices for greater productivity at every stage of the research process, from planning through synthesis .

Benefits of UX research repositories

In recent years, research repositories have grown in popularity due to the variety of benefits they offer to researchers and their organizations. These benefits include:

Centralizing research data

One of the main benefits of having a UX research repository is that it provides a secure, centralized location to store and organize research data. This makes it easy for information to be quickly accessed and retrieved as needed, saving time and resources.

By storing all user research data in a single place, teams can avoid the costs of redundant work and even use existing insights to augment new research.

Additionally, a centralized UX research repository can help teams identify research gaps and areas to study in the future based on the needs of their organizations. For easy retrieval and use, it’s important to develop a repeatable system for tagging research artifacts and logging metadata. This ensures information is discoverable for everyone with access.

Ensuring consistency

Back to the two content types of research repositories. 

Input should include UX research methods and methodologies , protocols, and other standard approaches that help guarantee the consistency and accuracy of findings and insights gained from the research you conduct.

Consistency is vital. It ensures that your research isn’t arbitrary or subjective, and can be independently replicated by other people in the organization or elsewhere using the same or similar methods.

The same goes for output. Whether it’s a written insight report or a collection of clipped video highlights from a user interview recording, each should have its own standard format and conventions.

Enhancing decision-making

The importance of data-driven (or data-informed, as some prefer to say) decision-making can’t be overstated. After all, that’s really what having a healthy repository is all about. 

A centralized UX research repository is a valuable asset for product, design, and development teams because it allows them to store and access powerful data and insights. This enables product managers, designers, and development teams to better understand user behavior, challenges, preferences, and expectations — and ultimately, make user-centric decisions to build better products.

Streamlining the research process

Planning for future research. Taking notes during research. Transcribing interviews. Analyzing raw data. Identifying key highlights. Generating actionable insights. Preparing rich, engaging presentations and reports. 

Depending on how you work, each of these research activities may involve several tools. That’s a lot of jumping around and context switching, which isn’t great for productivity.

If you’re not careful, your research toolstack can grow too fast and too big, making it difficult to manage.

But, finding the right repository for your situation will help you streamline your research processes. This can significantly reduce the need for juggling multiple tools, save valuable time, and improve the quality of results. It also sets you up with the systems you need to scale as your organization — and its demand for research — grows.

Using a repository to streamline processes ensures insights can easily be traced back to the raw data they came from. It’s your organization’s source of truth for UX research.

Read: Scaling research that rocks 🤟(or at least isn’t rubbish) with Kate Towsey

Keeping all feedback in a single location

Conducting research isn’t the only way to uncover insights. Incoming user feedback is also incredibly valuable. That’s why researchers often include various feedback sources in their research repositories.

Feedback can originate from diverse channels such as public reviews on sites like G2 and TrustPilot, sales conversations, and customer support tickets.

Leveraging information from various sources helps keep a healthy mix of positive and negative feedback always coming in. Not only does this widen research perspectives for better decision-making, but it also strengthens the quality of research by using all available data and potentially minimizes the need or scope for new studies.

Greater collaboration

Having a repository makes research a team sport by facilitating collaboration across the entire organization, both in person and remotely. With a central repository, research findings can be shared and discussed collectively, which encourages cross-functional collaboration. 

This democratization of research insights boosts transparency while ensuring that teams are aligned and working towards achieving common goals. It helps prevent the duplication of research efforts since team members can easily see what others have and haven’t done.

A repository can also provide a framework that empowers non-researchers (e.g., product managers) to independently carry out safe, effective user research without having to depend exclusively on research staff.

Build & maintain a participant panel

All this talk about storing research. But what about your participants and their data?

While a participant database may not be the first thing that comes to mind when thinking about establishing a UX research repository, it should factor into your decision-making process.

A healthy participant panel helps researchers keep a pulse on participant interest, activity, and engagement. You can use it to filter and find candidates with the right attributes for your study. You can see who has participated in past research and provide insight into the recruitment of participants for upcoming research. It can also help prevent over-contacting anyone (because the last thing you want to do is annoy your panel).

These are all reasons why it makes sense to integrate your panel with your repository if possible. Keeping participant data and research data close makes for tighter execution at every step.

Read: The complete guide to panel management for 2023

Democratize research access

A research repository makes democratizing research in your organization possible. Access may not necessarily be reserved for only those in the research department (or R&D) but may also be granted to other teams, stakeholders, or everyone in the organization.

From product managers and designers to marketers and sales reps, access to an organization’s repository lowers the barrier to entry for getting involved in research, simply by exploring what others are working on.

That said, adequate access monitoring and control measures must be put in place, and training should be offered to those who are new to using a research repository.

How to build an effective UX research repository for your team

Before you pick your repository tool, it’s important to evaluate the other tools and processes your organization currently uses. The road to launching an effective research repository can be roughly broken down into the following five steps:

1. Set strategic goals

A common error when trying to find the best UX research repository for your needs is to dive straight into the search for tools and try to compare them. (It’s why we haven’t so much as mentioned a single option so far in this guide.) Like any type of software, comparing repositories is a difficult task if you don’t have a clear understanding of what to look for. 

First things first: seek support and input from your team and stakeholders early on.

It might help to conduct stakeholder interviews at this stage to ensure the collaboration and engagement with your future repository. Involving stakeholders can help you see things you might have missed and increase the likelihood of smooth operations once the repository is adopted.

Now, it’s time to define your goals for the ideal UX research repository in your organization. What do you intend to achieve (describe the best-case scenario in detail)? How will building a repository impact you as a researcher, as well as your stakeholders and the business as a whole? Does this decision to build a repository align with larger business objectives?

Consider developing a mind map of what research looks like for your team, or even a want a journey map for the entire research process, outlining what it looks from start to finish.Setting strategic goals for your repository will help your team to better understand its functions and benefits and help you maximize its adoption and impact.

2. Identify your team's requirements

Once you’ve set strategic goals for your UX research repository, the next step is establish your research team's requirements. This may require you to conduct a gap analysis.

The first thing to consider will be the repository tool itself and how its features align with your strategic goals. In most situations, it makes sense to place an emphasis on data security, accessibility settings for team members and stakeholders, user-friendliness, and ease of sharing research findings. Be as thorough as possible.

You’ll also need to consider potential workflow changes given the habits of the employees involved. The bigger your company is, the more sensitive this will be. What changes will have to be made to your current processes? What new tasks will need to be planned for? Which procedures will need modification, and which ones will be scrapped? In particular, think through challenges faced by the product managers as they hold a great deal of operational responsibility.

With these considerations in mind, draw up a rough list of potential repository tool candidates that match your goals.

3. Do your due diligence on repository tools

In a sea of tools, where do you even start? 

Likely with a Google search — but analyzing the top results one by one can get confusing fast. Using a software review comparison site like Capterra or G2 will likely be more effective in making your shortlist of tools that meet your requirements.

Better yet, ask fellow researchers you know for recommendations directly or post online where your peers hang out, such as the ResearchOps Slack Community .

Once you’ve developed your shortlist of tools, drill deeper. Depending on the size of your team and budget, pricing may be the first thing you check or the last. Either way, get a ballpark idea of how much you can expect to spend (and perhaps be wary if a company doesn’t make their pricing publicly available). Take a look at help centers to see how easy it is to find answers to problems and get in touch with support. Check out the blog – does this company put out educational content you might actually read? Do you have a library of helpful how-to videos or templates? And what about their social presence — do they seem to have an engaged community of evangelists or are their accounts littered with complaints from frustrated customers.

During your due diligence, you and your team will hopefully be able to weed out the pretenders and narrow your list down to the true contenders. From there, it’s time to take your new tool(s) for a spin.

4. Demo & trial your best tooling options

Most UX research repository tools offer two ways to get started: immediately with a trial (often free) in just a few clicks or in the next few days by scheduling a demo with the sales team. (If you’re shopping for an enterprise plan for a larger team, it’ll be the demo.)

Then, it’s time for more due diligence. If possible, work with your team to trial and/or demo multiple tools at once. You’ll want to evaluate everything from ease of setup and onboarding to actually organizing and storing your research. It’s also important to get a feel for the company representative(s) who will be managing your account. Do they inspire confidence or concern? Are they invested in achieving your team’s goals or just here to check the boxes?

Not all trial and demo processes will look the same. Make sure to take copious notes throughout, as these will come in handy later if you need to build a business case to present to your procurement team.

5. Create an onboarding plan

Your due diligence is done. Your team has collectively determined a winner (after duking it out in a spirited debate over two final options, of course). You’ve even made your way through procurement and legal with any major issues. Now, it’s time to onboard your new UX research repository.

By now, you should already have a solid idea of what to expect from your trial run and product demos. Next, you need to delegate implementation to one or more capable individuals. Key roles here include purchasing the the repository product and managing billing, defining the repository’s data structures, and granting access to users. If you're leaving an old tool for your new tool, that also means gearing up for a repository migration of all existing research artifacts . 

You’ll also want put together an onboarding plan for all involved stakeholders and a presentation to share with the company as a whole.

Adopting a research repository can be a gradual process that takes time and requires an effective implementation plan to ensure success. It won’t happen overnight.

Consider ranking such goals and focusing on those you intend to achieve earlier to avoid exerting too much pressure on yourself and your team.

Read: The 5 Cs of a successful research repository with Julian Della Mattia

8 of the best UX research repository tools

I know what you’re thinking.

Finally, the millionth edition of the the “# Best [ Software ] Tools in 2023” I’ve been waiting for! Surely there won’t be any bias and the company writing this guide won’t rank itself #1 above all its competitors.

You’ve made it this far and we’ve covered a lot. It’s only right we mix in a joke.

On a serious note, there’s no one-size-fits-all repository tool. (And if anyone tells you that, run.) So in the interest of transparency, we’ve compiled 8 of the top research repository tools on the market. They’re in no particular order, but Great Question is first because, well, it’s our website.

Great Question

At Great Question, we’re building the home of research user-centric teams, like Canva , Drift , and Brex to name a few. A cornerstone of this is our repository. Think of the Great Question Research Repository as an insights hub where you can:

• Capture, store, and tag all of your research. Never forget to hit record again with automatic interview recordings. Get free transcriptions that you can easily search. Organize everything with AI-suggested tags specific to your study or used globally across your team’s whole account. Upload or import external recordings in bulk for free transcription any time. Integrations include Zoom, Google Met, and Microsoft Teams.
• Analyze research data and create artifacts. Select interview transcript text to create instant video highlights of your key moments, then combine multiple highlights into a single highlight reel for maximum impact. You can also embed highlights and reels in your written insight reports.
• Share and collaborate with your team. Copy and paste a link to share any highlight, reel, or insight with your team wherever they work — even if they don’t have a Great Question account. Integrations include Figma, Zapier, and Slack, which allows you to send automatic notifications to your team’s channel when an interview is scheduled, survey is completed, and other research events occur.
• Discover and learn from past research. Search the repository using keywords or custom filters, and view research artifacts in grid, table, or kanban layouts. Quickly find what you’re looking for to prevent duplicate work or augment new research.
• Protect data with enterprise-grade security. Great Question is SOC-2, GDPR, and HIPAA compliant , and meets enterprise security requirements through regular penetration testing. Your data is safe with us.

We’re also hard at work building smart, ethical ways to leverage AI for UX research . This means helping researches save time on tedious tasks so they can focus more on more important, impactful work. Think AI-suggested interview summaries, survey questions, highlights, titles, and tags. 

What makes Great Question different from other tools is that it’s much more than just a repository. With our all-in-one platform, you can:

• Manage a panel of your own users via CRM integration or list upload, or build a panel of non-users through our third-party integrations with Respondent and Prolific .
• Sync your work calendar with your research calendar to prevent conflicts and streamline scheduling with continuous invites and availability .
• Personalize participant recruitment with branded emails and landing pages, send automatic reminders, and prevent over contacting by setting guardrails.
• Run your favorite research methods, like user interviews , focus groups , surveys , unmoderated studies, and more. (Coming soon: prototype testing , tree testing, and card sorting .)
• Set global incentives for research participants with 1,000+ options in 200+ countries and automatically distribute upon study completion.

If you’re ready to take our repository for a spin (or interested in learning more about some of the features listed above), book a demo here to get started.

Founded in 2017, Dovetail is a popular research repository that enables users to generate research reports in a matter of minutes. This cloud-based customer knowledge software assists product, design, and development teams with user research and collaboration. Notable features include full-text search, usability testing, pattern recognition, file sharing, tagging, analytics, and graphical reporting.

Through the Dovetail platform, administrators can store user research data in a unified location, develop procedures for customer interviews, embed videos, images, and recordings in notes, as well as capture demographic and qualitative data. Dovetail also allows teams to analyze data, including survey responses, transcripts, and notes; create a standard set of tags for different projects; leverage natural language processing (NLP) for sentiment analysis; and explore metrics on graphs and charts.

Dovetail helps managers boost collaboration between user experience designers, product teams, and other stakeholders, in addition to providing role-based permissions to users, maintaining project data, and storing billing information for a multiplicity of customers. Team members can search for tags, notes, or insights across various projects as well as export data in CSV format.

Grain is a UX research repository that helps researchers collect and organize user interviews as well as create and share research insights and findings with visually appealing stories. During these user interviews, Grain can record, tag, transcribe, and organize your qualitative data. It also allows users to import their pre-recorded interviews from Zoom Cloud or manually upload them.

You can add your team members, stakeholders, and collaborators to your workspace so that they can access all your research data at any time. As soon as you’ve recorded your interview in Grain, you can slice and dice your data in a variety of ways to make sharing insights easy. Selecting the text in the transcript will enable you to clip and share important moments in a user interview. You can also create an engaging story by combining insights obtained from multiple interviews.

Copy and share the Grain AI summary with one click. Also, share insights and key moments with other teams by copying and pasting to embed Grain videos in communication software such as Slack and collaboration tools such as Notion or Miro. Grain is equipped with a native integration capability that makes it possible for you to send research insights directly to your product board.

Userbit is a tool that not only enables you to collect and store data from user interviews (with highlights, transcripts, and tags) but also includes a suite of features to help you transform data into meaningful insights.

Easily convert your transcripts to visual word clouds or affinity diagrams with Userbit's visualizations. Userbit offers a great way to quickly spot patterns and relationships in your data in order to start generating insights. Another valuable Userbit feature is the capacity to develop user personas directly from research data, allowing you to save a lot of time since it eliminates the need to manually create personas from scratch. With Userbit, you’ll have a mental picture of your users based on how they think and behave. This can be very helpful when attempting to design an intuitive user experience.

Userbit ensures easy sharing of findings with your team members and stakeholders, thus enabling the whole team to collaborate effectively so as to develop the ideal design process and user path.

Condens is a tool that can help you structure and organize your user research data effectively. With Condens, you can create a UX research repository that's both easy to use and well-organized. Condens is designed for anyone: researchers, product managers, designers, and those with little or no technical background.

One distinguishing feature of Condens is its pleasant visual interface, which allows you to view all your data at a glance. You can quickly filter and search for particular items, making it easy to locate what you're looking for, even when faced with a huge amount of data. The AI-assisted transcription feature can speedily transcribe user interviews to ensure prompt data analysis.

Condens boasts a broad range of integrations that include the capacity to easily import data from Google Sheets, Excel, and other research repositories. One advantage of this is that you can start using Condens without having to worry about transferring your data manually. So if easy onboarding and an appealing visual interface are your top priorities, Condens checks all the boxes.

Acquired by UserZoom in 2021 which later merged with UserTesting in 2022, EnjoyHQ is a cloud-based repository that helps UX and product teams learn faster from customers by streamlining the customer research process. EnjoyHQ facilitates the easy centralization, organization, and sharing of all customer insights and data in one location. It has the components needed to build an effective research system that scales.

EnjoyHQ integrates with popular communication and collaboration tools, providing the ability to gather all your data together in seconds. Third-party platforms that seamlessly integrate with EnjoyHQ include Google Docs, Zendesk, Jira Service Desk, Drift, AskNicely, Dropbox, Trello, Trustpilot, and more. Organize all your data in one place, accelerate your analysis process, and easily share insights with team members and stakeholders through EnjoyHQ.

Key features include a collaborative workspace, user management, customer segmentation, sentiment analysis, and app review translations. You can categorize data through tags, metadata, and highlights and also develop a taxonomy to classify research findings for analysis. Managers can prepare summaries and reports as well as monitor audience engagement with respect to the displayed insights. Additionally, presenters can save reports in graphical formats and use links to share them with team members.

Aurelius is a repository that was built by UX researchers for UX researchers. It’s a balanced blend between cost-effectiveness and a suite of features to collect, organize, and synthesize research data. Aurelius helps you analyze data and quickly turn it into valuable insights. Its lean features ensure that you pay for only what you need and nothing else. The Aurelius magic uploader enables you to easily upload your data into the program. Use the Aurelius-Zapier integration or the Aurelius-Zoom integration to import spreadsheets, audio, video, notes, and other file types.

The powerful global tagging feature can be used to tag notes, key insights, and recommendations. AI-powered intelligent keyword analysis helps you identify patterns even in large datasets. The universal search feature will help you quickly locate old research reports, notes, and other data. Add recommendations to each key insight, and Aurelius will automatically generate an editable report you can share with other users.

Aurelius can serve as an extension of your daily workflow in terms of promoting collaboration, encouraging independent research, and helping you obtain research insights that can drive stakeholder action.

Looppanel is a newer repository founded in 2021 with the goal of enabling product and design teams around the world to build products their users love. This AI-powered research assistant streamlines user research by managing everything from initiating calls to creating the perfect user interview templates, recording and transcribing sessions, and assisting teams in discovering and sharing insights faster

Some of its most popular features include taking time-stamped notes during a user conversation and sharing video clippings from a call with a single click. With Looppanel, teams can analyze and share their findings from Zoom-based user interviews in minutes and centralize research data in one place. It offers highly accurate transcripts across multiple languages, allows users to collaborate with team members for free, and lets them share reports and summaries via a link.

Other general tools that can be used as research repositories

Aside from these core UX research repositories, there are other general tools that can be adapted to get the job of a repository done. Here are a few of them:

Notion is a powerful, versatile tool you can do a lot with, from research documentation to project management. It's easy to use, incredibly flexible, and has a tidy interface, making it great software for housing user research data. Notion enables you to create custom databases, which is great for organizing your data. You can also attach rich media such as video, audio recordings, and images to your databases.

Like most modern apps, Notion provides a wide range of integrations. For instance, you can easily import data from other programs such as Google Sheets and Excel. This can be useful if you wish to consolidate all your user research data in a single location. Furthermore, extensions such as Repo can help you transform Notion into a dedicated UX research repository with features like highlighting and tagging. Enrich your research data in Notion by adding videos and key moments from your interviews. 

Notion is a potential option for researchers, product managers, and designers looking for a versatile tool that can serve a variety of purposes.

Though Jira is mainly a project management tool popular for software development teams, it can also serve as a storage medium for UX research data and projects. Jira boasts a variety of features that make it suitable for user research. For instance, it can be used to track interviews, facilitate user testing sessions, undertake other user research tasks, and create custom reports. Jira also allows you to create a dedicated research project, making it easy for your team to keep all research data in one place. You can use it to follow the progress of user research and identify areas where improvements are required.

The ability to add attachments to Jira tickets makes storing and sharing user research data, such as screenshots and interview recordings, easy. Jira can be somewhat overwhelming if you are new to project management tools, but it is nonetheless a good tool to store your user research data.

Airtable is another database tool capable of serving diverse purposes, including UX research. It comes with a user research template that helps you avoid the stress involved in having to set up a database. A combination of that user research template and another feature — the user feedback template — can help you organize your user research data and feedback in one location.

Easily add attachments such as images, audio files, and videos to enrich your user research data. Organize and find your user research data using the views feature to filter and sort your data or create custom formulas to calculate things like the net promoter score . You can also visualize your data through bar graphs and other means.

Confluence is a shared workspace developed by Atlassian to create and manage all your work. Confluence makes it easy to organize and find the information you need. This is one of the main reasons it can be adapted into an effective repository. You can group related pages in a dedicated space for your work, team, or cross-functional projects. Depending on permissions, access to a Confluence workspace can be reserved for only you or other members of your company. Page trees create a hierarchical list of pages within a workspace, highlight topics on parent pages, and help ensure you and your team work tidily.

To find something, just do a quick search of existing pages. You can even locate comments posted to a page by others. Visual improvements for UX concept documentation not only make sense but are simple in Confluence. It facilitates the easy integration of a variety of add-ons through which you can quickly attach visual information such as image maps, flow charts, and other diagrams via your editor.

Concept visualization, prototypes, and spec files are all integral components of UX design and should form part of your UX documentation as well. Confluence provides you with the opportunity to visually preview a wide range of file types that you can utilize to bolster your written research documents.

Final thoughts

To build a healthy, mature UX research practice in any organization, you need a repository. But a research repository without a clear strategy won't last long.

That’s why it’s essential to align with your team on strategic goals for your repository, perform due diligence on your tooling options, and run collaborative onboarding to maximize adoption and impact.

With this guide in your back pocket, you’re well on your way to building an effective repository that makes research vital to your organization.

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Jack Wolstenholm

Jack is the Content Marketing Lead at Great Question, the end-to-end UX research platform for customer-centric teams. Previously, he led content marketing and strategy as the first hire at two insurtech startups, Breeze and LeverageRx. He lives in Omaha, Nebraska.

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Research repository: solving your organization’s research problems

User research is siloed within departments

The same research is repeated over and over

Research reports go unread by stakeholders

Cumulatively scaling datasets don't lead to cumulatively scaling knowledge

Throughout this blog post, we’ll dive into these problems and discuss how a research repository can help and the principles that make for a great research repository solution .

.css-1nrevy2{position:relative;display:inline-block;} User research is siloed within departments

Along with the user research team, almost all teams within an organization conduct some form of customer research, even if they don’t explicitly call it that. Product managers interview users, designers test prototypes, salespeople talk to leads, support tracks topics, marketing facilitates focus groups, HR run feedback surveys, and customer success run  Net Promoter Score  surveys.

These functions and teams all do user research differently, analyzing their data with different tools, and publish mountains of data, reports, and updates across a variety of formats and products. Stakeholders and consumers struggle to find what’s relevant to them—the signal in the noise; the needle in the haystack.

Often, when a new researcher joins a product team, they go off, do some research, and come back with the same insights and findings that are already known. It takes months (years, even!) of experience to build the necessary context and to get to tangibly meaningful insights that have the power to effect change and be force multipliers in an organization.

Tenured employees already know this and grow skeptical of a research team that tells them things they already know. Over time, thanks to the same research being repeated, and the same conclusions echoed, the effectiveness and credibility of the research discipline within your organization is slowly eroded.

Sherif Mansour  is a distinguished product manager at  Atlassian  with over 10 years of experience working on products like  Jira  and  Confluence . He reflects that:

One of the key challenges we’ve seen is how to help new team members build a shared understanding of the key insights that existing team members have already realized. The cost of re-learning is expensive, especially in growing organizations.

Because research is stored in a variety of formats, tools, and silos throughout the organization, there’s no way for anyone to quickly get up to speed on what is already known. Searching through years of unorganized archives of reports, documents, and presentations to build context is an impossible task.

Lastly, when that researcher leaves the company, they take a lot of undocumented knowledge of your customers with them—hopefully not to a competitor.

Reports go unread by stakeholders

Written reports and presentations are the ‘go-to’ format for sharing user research insights, but unfortunately, there’s no standard for how they’re produced or what content they should contain, and every researcher structures them differently.

These kinds of reports are usually inaccessible to everyone in the organization: they’re shared spontaneously over email and chat or lost in Google Drive or Dropbox. There isn’t a clear place for people to go to learn about your customers. You’re lucky if these reports are read, and you’re even luckier if any action is actually taken as a consequence of them.

Back in 2005,  Jakob Nielsen  from  Nielsen Norman Group  highlighted the pain of finding usability testing reports in his article  Archiving Usability Reports :

When people have to search for usability reports, they’ll often fail—or they won’t even know what to look for because there’s no single place that lists all available usability results. Even worse, if past project owners are the only source of results, you risk losing valuable institutional memory when these individuals leave the company or get reassigned.

Another detriment of traditional research reports is that they’re usually disconnected from the raw data and evidence that led to the formulation of the report in the first place. It’s difficult for stakeholders to understand how a researcher came to a particular insight, because there’s often no way to dive into the details of a specific usability test, interview, or survey response. This lack of traceability leaves stakeholders spending time poking holes in the research or methodology, instead of taking action on them.

Standard research reports also often lack any features that allow you to track engagement. PDFs don’t have read-receipts, and there are no easy ways to measure the impact research is having in your organization.

Worst of all, of the researchers we spoke to, none of them actually enjoy creating these reports. They find themselves spending more time designing and formatting internal reports for stakeholders, rather than actually talking to customers and users. The best workaround we’ve seen is reusable templates for research reports.

Research data and customer feedback comes in many shapes and sizes, including surveys, quotes, interview notes, video recordings, industry trend reports, social media posts, app reviews, and more. Researchers rely on all this information to synthesize research findings, usually in the form of a research report. Typically, this research lives in a file storage system like Google Drive or Dropbox or a wiki like Confluence or Notion.

Organizing and curating this ever-growing collection of data is relatively simple for a small organization. However as companies grow, the systems used to store customer research don’t scale and end up requiring significant administration to maintain. Someone has to ensure all the files are searchable, appropriately restricted, and tidy.

Inevitably, the repository becomes unwieldy and difficult to use. This creates the opposite of the intended effect—people stop using stored research and the total sum of an organization’s customer research leads to less customer knowledge.

Why a research repository?

Most organizations with a user research function acutely feel the pain of the problems above. If you don’t yet, it’s likely you will in the future as you scale design and research. Much of the pain can be eased through a thoughtful approach for how research data and insights are captured, analyzed, standardized, archived, and shared.

Imagine a ‘Wikipedia’ for your organization’s customer knowledge: a centralized, searchable database of research and insights that the entire company leverages to make better decisions. A single source of truth that empowers stakeholders to engage with research and fosters a culture of research across your organization. Designers, product managers, and developers effortlessly pull up insights that answer common questions and, in one click, can explore the evidence—and understand the context—that led to those insights.

A  research repository  is just that—one central place, or source of truth, where people in your organization can go to find the latest insights from your research team.

Learn how they did it

The characteristics of a successful research repository

We’ve talked to user researchers, designers, and product managers across a variety of organizations, and we’ve settled on five key characteristics that lead to the successful adoption of a research repository. We believe all successful repositories are  retrievable ,  approachable ,  traceable ,  accessible , and  secure .

Retrievable

Searching and finding research insights should be effortless. Members of the product team should be able to easily find answers to their questions, self-serve, without needing to write complex queries or spreadsheet formulas. Insights should be easily filtered and segmented by attributes important to your organization, like segment, country, market, demographic, or even  NPS . Researchers need to be able to conduct secondary research by easily retrieving prior research and insights and feed that into current research projects.

Approachable

A research repository should be approachable not only for user researchers, but also for other members of the product team like designers, product managers, developers, and stakeholders like founders or executives.

Creating insights needs to be simple and delightful—your team needs to be bought in and want to use your repository, and they won’t if the experience is complicated, clunky, or slow. Stakeholders want to consume research insights in a lightweight, quick, and beautiful way, without needing to read multi-page reports or presentations. Anyone should be able to easily “remix” previous research and leverage an organization’s cumulative customer knowledge to make informed product decisions.

Successful research repositories aren’t just a collection of disconnected insights or recommendations. They also need to provide a path back to the raw research data which led to the insights in the first place. Research findings should be connected to the source material that the researcher interpreted to inform a particular insight. References to raw research data or ‘evidence’ enable stakeholders to see where an insight came from and understand the original context of the research method.

Someone should be able to look back on a user research insight from years ago, review the evidence, and determine if it’s still relevant or has been interpreted correctly based on what is now known. Researchers should be able to look back to see if new insights could be developed from research data that was collected previously.

A repository needs to empower your organization to leverage customer research data and insights, and for this to happen your entire team needs access. New people who join your organization should be given access on day one.

You shouldn’t have to worry about managing access permissions for folders in Drive or Dropbox – the ideal research repository should be ‘open by default’. Team members should deep-link to your living repository over email and chat as the source of truth, rather than send around presentations or reports as static attachments.

As a research repository will act as the single source of truth for your organization’s customer knowledge, it’s likely it will include personal information and potentially sensitive data from a range of industries.

For your research repository to be approved by your security, legal, and information technology teams, you’ll need to consider where customer data will be stored, what the processes are for retention and deletion, if data is encrypted or anonymized, and what security practices and policies are in place.

If your organization has customers in the European Union, you’ll need to ensure that your research repository is compliant with the  General Data Protection Regulation (GDPR) .

Starting a research repository

So you’re convinced and want to start building a research repository in your organization. How do you get started? Aside from working out the  governance and operations  that will support how people use and interact with your repository internally, the most critical decision is selecting a tool or platform for your research repository.

Flexible and generic tools

Most organizations start their research repository journey by assembling existing tools that are already used internally, typically because they’re accessible and inexpensive to set up. Teams cobble together faux research repositories with wikis like  Confluence  or  Sharepoint , spreadsheets and databases like  Excel  or  Airtable , issue-tracking tools like  Jira  and  Trello , and storage tools like  Google Drive  or  Dropbox .

As an example of using a flexible tool as a research repository solution, the folks at  GitLab  have used their own product as a repository for their UX research insights.  Sarah Jones , UX Research Manager at GitLab  describes their repository :

Instead of reports and slide decks, we use  issues to document key findings  from research studies. Each insight is supported with evidence, typically in the form of a video clip or statistical data. We use GitLab’s related issues functionality to connect insights which were revealed during the same research study.

As everyone at GitLab has access and knows how to use the product, this approach has been successful for them. However, most research organizations don’t have the luxury of working on a product that can be manipulated in this way, and flexible solutions almost always inevitably fail in the long term for a variety of reasons:

Searching and retrieving insights from these tools is cumbersome – search functionality is complex, limited, and unintuitive. In the case of file storage tools like Dropbox and Google Drive, searching within files is usually not possible.

Insights are static and disconnected from the original research data. Recordings, transcripts, notes, and participant information has to be stored across many different tools and the evidence that supports an isolated insight is lost.

They’re not fit for purpose. Flexible, horizontal tools aren’t designed for research and use unopinionated terminology like cells, sheets, rows, and records instead of concepts that are research-friendly like insights.

We often see people come to  Dovetail  as a purpose-built research repository solution after trying to build a repository using tools that aren’t built for that specific purpose.

Building a custom repository in-house

Unsatisfied with flexible, generic tools that aren’t fit for purpose, organizations with well-resourced research teams often look to design and build their own research repository in-house. Large enterprises like  Microsoft ,  WeWork , and  Nasdaq  have all shared details of their own purpose-built research repository solution.

Microsoft’s research team have built their own repository called the  Human Insights System (HITS) . As  Matt Duignan , Principal User Research Manager at Microsoft explains, to help scale HITS across the entire Microsoft organization without losing the integrity of their data, they designed for letting people find insights while retraining context:

If a user were to take an insight out of context, say to make an argument in favor of a new product feature, HITS makes it possible for everyone involved to look at the supporting evidence and come to a fuller understanding of what the context implies.

The design of HITS enables research to be brought into conversations and make product decisions informed by customer data and evidence.

Q&A with Matt Duignan from Microsoft’s Human Insight System

Similarly, WeWork built their own research repository solution internally, and  Tomer Sharon , then the Head of User Experience at WeWork, announced the Polaris research repository in his article  Democratising UX .

Following the article, an ‘open-source’ version of Polaris was  released as a template on Airtable . Unfortunately, the researchers we’ve spoken to who have tried to create a research repository with this template have not had success, for the same reasons why tools like Confluence, Airtable, and Dropbox don’t make good research repositories.

Creating WeWork’s Polaris research repository in Dovetail

With enough resources, building your own research repository can work since it can be tailored to specific needs and processes. However, given the complexity in building a bespoke research repository solution and the ongoing maintenance commitment, even large organizations rarely opt to invest in an internal solution.

Why we built Dovetail

We built Dovetail to be the platform for your organization’s user research, considering principles of  retrievability ,  approachability ,  traceability ,  accessibility, and  security  from the ground up. With our platform, researchers, analysts, designers, and product managers can store user research data in one place, analyze qualitative data to discover patterns and insights, and share research findings with the rest of their organization.

Our  team  has decades of combined experience working in product teams at  Atlassian ,  Canva ,  Intercom , and  Microsoft . We’ve all seen first-hand the challenges that come with managing customer knowledge and insights, and we’re passionate about helping teams understand their customers, make better decisions, and do great work.

Search, segment, and retrieve data

We’ve built an appreciation of how important it is to enable stakeholders to self-serve customer data and research insights. Researchers are usually stretched thin relative to their counterparts in engineering, product management, and design, and insights need to be scaled across the entire organization.

We’ve built powerful, intuitive filter and segmentation controls that enable people to easily  retrieve  research data and customer insights. Research data can also be enriched with contextual information: demographic data like name, age, location; contact details like email address and phone number; properties like persona, company, or license; and even someone’s  Net Promoter Score .

Approachable and enjoyable

A focus for us is making sure Dovetail is  approachable  and enjoyable to use. We know a lot of research software isn’t particularly intuitive, especially academic qualitative data analysis suites like  MAXQDA ,  NVivo , and  Dedoose . While very powerful, these QDA tools are complex and beyond the reach of most commercial researchers and stakeholders.

We try to make it easy for people to analyze unstructured data, create insights and embed references to raw data, and making insight reports look good by default.

Embed evidence to your raw data

In his article on  Microsoft’s Human Insights Library , Matt Duignan talks about “real-time curation” as a way to encourage participation in the research library / repository, to avoid the problem of reports being deferred to the end of the process:

Someone needs to synthesize insights in a way that optimizes for durability and reuse across time. But for researchers under pressure, it can be tempting to defer this work.

Rather than running out of time to turn insights into durable, standardized reports, an insights repository should instead organically evolve over time, with  traceability  back to the original source material and context.

Because Dovetail has features to help with analyzing common research methods like interviews, usability testing, and surveys, it allows you to maintain traceability through embedded references to notes, quotes, tags, photos, videos, recordings, and more.

Access for your entire organization

We don’t want  our pricing  to inhibit the effectiveness of research teams within organizations. To make Dovetail  accessible  to everyone, we’ve been intentional about offering unlimited, free viewer accounts for people in the organization to view research data, read insights, and comment. This means that our customers only pay for researchers that actively contribute data, analysis, and insights.

This pricing model has accelerated the consumption of research in our customer’s organizations. Gemma Sherwood,  Intrepid Group ’s UX Manager has  shared with us  that their UX team has now turned their attention to other departments like Marketing and Insights to get them involved in their research repository:

Our broader goal is for the Insights and Marketing departments to utilize Dovetail as a searchable research library to improve their decisions and ground them in customer experience.

We’ve also invested in features that  allow anyone with an email address  at your organization to join your Dovetail workspace without needing to be invited and the ability to  share your projects and insights  with others who don’t yet have an account.

Secure, and private by design

We make  security  and data privacy foundational principles of everything we do, and we recognize the importance of adhering to regulations to advance information security and data privacy, including the  GDPR .

We’ve chosen proven third party cloud providers, take regular data backups and test recovery, run penetration testing, encrypt all data at rest and in transit, conduct static code analysis and third-party vulnerability scanning, sanitize our logs, secure individual customers at the database level, and  many other cloud security techniques .

The future of research repositories

We think more and more organizations that talk to customers and leverage customer data to improve their products and services are increasingly frustrated with the pains of storing, retrieving, and sharing insights from user research. We believe that a thoughtfully considered user research repository is critical to mitigating this pain and unlocking the potential of customer research in organizations worldwide.

In Dovetail, we think we’ve built a solid foundation on our principles of  retrievability , approachability , traceability , accessibility , and security . Our team is motivated to make Dovetail the obvious platform for your user research and insights.

We’re at the beginning of this journey. We’ve got more to learn from our customers, and  many exciting features planned  for the future. If you’re interested trying a research repository in your organization, we’d encourage you to give Dovetail a go and  sign up for a free trial —we’d love to hear your feedback!

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How to build a research repository: a step-by-step guide to getting started

Research repositories have the potential to be incredibly powerful assets for any research-driven organisation. But when it comes to building one, it can be difficult to know where to start. In this post, we provide some practical tips to define a clear vision and strategy for your repository.

Done right, research repositories have the potential to be incredibly powerful assets for any research-driven organisation. But when it comes to building one, it can be difficult to know where to start.

As a result, we see tons of teams jumping in without clearly defining upfront what they actually hope to achieve with the repository, and ending up disappointed when it doesn't deliver the results.

Aside from being frustrating and demoralising for everyone involved, building an unused repository is a waste of money, time, and opportunity.

So how can you avoid this?

In this post, we provide some practical tips to define a clear vision and strategy for your repository in order to help you maximise your chances of success.

🚀 This post is also available as a free, interactive Miro template that you can use to work through each exercise outlined below - available for download here .

Defining the end goal for your repository

To start, you need to define your vision.

Only by setting a clear vision, can you start to map out the road towards realising it.

Your vision provides something you can hold yourself accountable to - acting as a north star. As you move forward with the development and roll out of your repository, this will help guide you through important decisions like what tool to use, and who to engage with along the way.

The reality is that building a research repository should be approached like any other product - aiming for progress, over perfection with each iteration of the solution.

Starting with a very simple question like "what do we hope to accomplish with our research repository within the first 12 months?" is a great starting point.

You need to be clear on the problems that you’re looking to solve - and the desired outcomes from building your repository - before deciding on the best approach.

Building a repository is an investment, so it’s important to consider not just what you want to achieve in the next few weeks or months, but also in the longer term to ensure your repository is scalable.

Whatever the ultimate goal (or goals), capturing the answer to this question will help you to focus on outcomes over output .

🔎 How to do this in practice…

1. complete some upfront discovery.

In a previous post we discussed how to conduct some upfront discovery to help with understanding today’s biggest challenges when it comes to accessing and leveraging research insights.

⏰ You should aim to complete your upfront discovery within a couple of hours, spending 20-30 mins interviewing each stakeholder (we recommend talking with at least 5 people, both researchers and non-researchers).

2. Prioritise the problems you want to solve

Start by spending some time reviewing the current challenges your team and organisation are facing when it comes to leveraging research and insights.

You can run a simple affinity mapping exercise to highlight the common themes from your discovery and prioritise the top 1-3 problems that you’d like to solve using your repository.

💡 Example challenges might include:

Struggling to understand what research has already been conducted to-date, leading to teams repeating previous research

Looking for better ways to capture and analyse raw data e.g. user interviews

Spending lots of time packaging up research findings for wider stakeholders

Drowning in research reports and artefacts, and in need of a better way to access and leverage existing insights

Lacking engagement in research from key decision makers across the organisation

⏰ You should aim to confirm what you want to focus on solving with your repository within 45-60 mins (based on a group of up to 6 people).

3. Consider what future success looks like

Next you want to take some time to think about what success looks like one year from now, casting your mind to the future and capturing what you’d like to achieve with your repository in this time.

A helpful exercise is to imagine the headline quotes for an internal company-wide newsletter talking about the impact that your new research repository has had across the business.

The ‘ Jobs to be done ’ framework provides a helpful way to format the outputs for this activity, helping you to empathise with what the end users of your repository might expect to experience by way of outcomes.

💡 Example headlines might include:

“When starting a new research project, people are clear on the research that’s already been conducted, so that we’re not repeating previous research” Research Manager

“During a study, we’re able to quickly identify and share the key insights from our user interviews to help increase confidence around what our customers are currently struggling with” Researcher

“Our designers are able to leverage key insights when designing the solution for a new user journey or product feature, helping us to derisk our most critical design decisions” Product Design Director

“Our product roadmap is driven by customer insights, and building new features based on opinion is now a thing of the past” Head of Product

“We’ve been able to use the key research findings from our research team to help us better articulate the benefits of our product and increase the number of new deals” Sales Lead

“Our research is being referenced regularly by C-level leadership at our quarterly townhall meetings, which has helped to raise the profile of our team and the research we’re conducting” Head of Research

Ask yourself what these headlines might read and add these to the front page of a newspaper image.

You then want to discuss each of these headlines across the group and fold these into a concise vision statement for your research repository - something memorable and inspirational that you can work towards achieving.

💡Example vision statements:

‘Our research repository makes it easy for anyone at our company to access the key learnings from our research, so that key decisions across the organisation are driven by insight’

‘Our research repository acts as a single source of truth for all of our research findings, so that we’re able to query all of our existing insights from one central place’

‘Our research repository helps researchers to analyse and synthesise the data captured from user interviews, so that we’re able to accelerate the discovery of actionable insights’

‘Our research repository is used to drive collaborative research across researchers and teams, helping to eliminate data silos, foster innovation and advance knowledge across disciplines’

‘Our research repository empowers people to make a meaningful impact with their research by providing a platform that enables the translation of research findings into remarkable products for our customers’

⏰ You should aim to agree the vision for your repository within 45-60 mins (based on a group of up to 6 people).

Creating a plan to realise your vision

Having a vision alone isn't going to make your repository a success. You also need to establish a set of short-term objectives, which you can use to plan a series of activities to help you make progress towards this.

Focus your thinking around the more immediate future, and what you want to achieve within the first 3 months of building your repository.

Alongside the short-term objectives you’re going to work towards, it’s also important to consider how you’ll measure your progress, so that you can understand what’s working well, and what might require further attention. 

Agreeing a set of success metrics is key to holding yourself accountable to making a positive impact with each new iteration. This also helps you to demonstrate progress to others from as early on in the process as possible.

1. Establish 1-3 short term objectives

Take your vision statement and consider the first 1-3 results that you want to achieve within the first 3 months of working towards this.

These objectives need to be realistic and achievable given the 3 month timeframe, so that you’re able to build some momentum and set yourself up for success from the very start of the process.

💡Example objectives:

Improve how insights are defined and captured by the research team

Revisit our existing research to identify what data we want to add to our new research repository

Improve how our research findings are organised, considering how our repository might be utilised by researchers and wider teams

Initial group of champions bought-in and actively using our research repository

Improve the level of engagement with our research from wider teams and stakeholders

Capture your 3 month objectives underneath your vision, leaving space to consider the activities that you need to complete in order to realise each of these.

2. Identify how to achieve each objective

Each activity that you commit to should be something that an individual or small group of people can comfortably achieve within the first 3 months of building your repository.

Come up with some ideas for each objective and then prioritise completing the activities that will result in the biggest impact, with the least effort first.

💡Example activities:

Agree a definition for strategic and tactical insights to help with identifying the previous data that we want to add to our new research repository

Revisit the past 6 months of research and capture the data we want to add to our repository as an initial body of knowledge

Create the first draft taxonomy for our research repository, testing this with a small group of wider stakeholders

Launch the repository with an initial body of knowledge to a group of wider repository champions

Start distributing a regular round up of key insights stored in the repository

You can add your activities to a simple kanban board , ordering your ‘To do’ column with the most impactful tasks up top, and using this to track your progress and make visible who’s working on which tasks throughout the initial build of your repository.

This is something you can come back to a revisit as you move throughout the wider roll out of your repository - adding any new activities into the board and moving these through to ‘Done’ as they’re completed.

⚠️ At this stage it’s also important to call out any risks or dependencies that could derail your progress towards completing each activity, such as capacity, or requiring support from other individuals or teams.

3. Agree how you’ll measure success

Lastly, you’ll need a way to measure success as you work on the activities you’ve associated with each of your short term objectives.

We recommend choosing 1-3 metrics that you can measure and track as you move forward with everything, considering ways to capture and review the data for each of these.

⚠️ Instead of thinking of these metrics as targets, we recommend using them to measure your progress - helping you to identify any activities that aren’t going so well and might require further attention.

💡Example success metrics:

Usage metrics - Number of insights captured, Active users of the repository, Number of searches performed, Number of insights viewed and shared

User feedback - Usability feedback for your repository, User satisfaction ( CSAT ), NPS aka how likely someone is to recommend using your repository

Research impact - Number of stakeholder requests for research, Time spent responding to requests, Level of confidence, Repeatable value of research, Amount of duplicated research, Time spent onboarding new joiners

Wider impact - Mentions of your research (and repository) internally, Links to your research findings from other initiatives e.g. discovery projects, product roadmaps, Customers praising solutions that were fuelled by your research

Think about how often you want to capture and communicate this information to the rest of the team, to help motivate everyone to keep making progress.

By establishing key metrics, you can track your progress and determine whether your repository is achieving its intended goals.

⏰ You should aim to create a measurable action plan for your repository within 60-90 mins (based on a group of up to 6 people). ‍ ‍

🚀 Why not use our free, downloadable Miro template to start putting all of this into action today - available for download here .

To summarise

As with the development of any product, the cost of investing time upfront to ensure you’re building the right thing for your end users, is far lower than the cost of building the wrong thing - repositories are no different!

A well-executed research repository can be an extremely valuable asset for your organisation, but building one requires consideration and planning - and defining a clear vision and strategy upfront will help to maximise your chances of success.

It’s important to not feel pressured to nail every objective that you set in the first few weeks or months. Like any product, the further you progress, the more your strategy will evolve and shift. The most important thing is getting started with the right foundations in place, and starting to drive some real impact.

We hope this practical guide will help you to get started on building an effective research repository for your organisation. Thanks and happy researching!

‍ Work with our team of experts

At Dualo we help teams to define a clear vision and strategy for their research repository as part of the ‘Discover, plan and set goals’ module facilitated by our Dualo Academy team.  If you’re interested in learning more about how we work with teams, book a short call with us to discuss how we can support you with the development of your research repository and knowledge management process.

Nick Russell

I'm one of the Co-Founders of Dualo, passionate about research, design, product, and AI. Always open to chatting with others about these topics.

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Creating the Best User Research Repository for Your Team

February 28, 2023.

Rasheed Ahamed

Every UX team needs a user research repository.

It helps you democratize research findings, get stakeholders to engage with insights, and influence the product roadmap. Having a repository also accelerates the research process and enables you to find and share relevant highlights from your user interviews whenever needed.

Is a user research repository only useful for companies with dedicated researchers? Not at all!

As long as someone in your company is talking to customers to understand their needs and get product feedback, setting up a repository is necessary. Rob Fitzpatrick , the author of The Mom Test, explains why:

Though we refer to it as a “user research repository”, it can help any team in understanding customers. And, if you’re looking to set up a repository, you are in the right place. Let’s go!

User Research Repository

User research repository is a shared hub for different teams, especially UX—to store, analyze, and collaborate on user research, enabling everyone in your company to develop a shared understanding of customers and how they use your product.

A repository isn’t just to gather and organize your user interviews. It’s a meeting point where your company can learn the jobs-to-be-done, receive feature requests, and collect product feedback—directly from the end-users and customers.

What Makes an Effective User Research Repository?

Research teams with no budget sometimes try to set up a repository using existing internal wikis like Notion or Confluence, project management tools like Trello or Jira, and databases like Sheets or Airtable.

Truth be told. It doesn’t work for most teams.

But it works for a few. For instance, GitLab built their repository using GitLab itself to make things easier for everyone involved.

“Open issues and epics indicate that the research study is still in progress and the UX researcher and/or UX/product designer is still adding insights to the repository. Closed issues and epics indicate that the research study is finished.”

On the other hand, leveraging specialized tools that are built intentionally to serve as a repository can work for you—out of the box.

But that doesn’t mean you can pick any tool for the job. You need to pay attention to a few characteristics to ensure the repository will help you accomplish what you set out to do!

Creating & Sharing Insights

One of the primary reasons to set up a research repository is to create & share insights . If the process isn’t straightforward and takes a lot of time, then it turns your team away from using it.

Your team would end up creating standard reports that aren’t easy to digest and other teams interested in contributing to the repository wouldn’t create any insights at all — as it forces them to spend hours on the process.

The easier it is for users to create and share insights, the more value you can get out of the repository. We’ll talk more about this later below.  

Discovering Insights

It should be as easy as a Google Search to find what you’re looking for in the repository. Tomer Sharon, former Head of User Experience at WeWork, argued that “reports” shouldn’t be the atomic unit of research insight. Because if that’s the case, you have to read through multiple reports to find what you are looking for.

“Whenever anybody asked me if I had witnessed users experiencing a particular problem, I’d rack my brain trying to work out which research report might contain the answer. I’d sift through multiple reports, scanning everything I had previously written."

- Sarah O'Donnell, UX Researcher, GitLab.

If finding an insight or a specific moment from user interviews involves a handful of steps, then your repository prevents others from consuming the insights. You need to have a solution that makes sharing out as simple and quick as possible.

Democratizing Research Data and Insights

Your UX repository should break down the silos and democratize insights curated by different teams. A sales team should be able to access the user interviews and highlights from UX research studies and vice versa.

And, to truly democratize insights, your repository should be approachable. If it’s complex and has a steep learning curve, then everyone except researchers will avoid using it.

It should allow stakeholders to consume insights in a quick, visually-appealing way without having to scroll through pages of reports. Anyone should be able to search and find the relevant nuggets from previous research interviews and create a new “insight” to share with their team and make informed decisions.

“Everyone is sharing their reports, results, and updates. Nobody is making sense of ALL of the piles of data being collected.”

- Tomer Sharon, former Head of User Experience at WeWork .

Connecting the Insights

With a repository, you can find the patterns from your research to come up with themes. The themes eventually lead to actionable insight.

If you find insight, it should also let you trace it back to its source—for instance, a user interview recording or transcript to understand the context and learn what led to the insight in the first place. In other words, it should connect the insight back to its source material .

Creating a User Research Repository using Grain

Now that we know what makes an ideal repository, let's create one using Grain!

Grain helps you store, organize, and collaborate on user research interviews and makes it easier to discover, create, and share insights—all from one workspace. We’ll talk about how to set up an effective repository for your company using Grain in three steps.

• Setting up a repository
• Creating and Organizing Insights
• Democratizing User Research

‍ Sidenote : We are creating a repository to house qualitative research interviews, not quantitative studies.

Step 1: Setting Up a Repository

The first step is to create and set up your Grain Workspace. Your Workspace will act as the repository, helping you search, create, and share insights from your user interviews.

To populate your Workspace with research data, you can either upload your interviews (video or audio files) or import them from your Zoom Cloud account. ‍ ‍

Grain will automatically transcribe all your interviews in a few minutes and split the conversation based on speakers, ready for you to analyze and clip out key moments.

And, for the upcoming user interviews, you can ask Grain to automatically join and record and transcribe the calls in real-time.

But before we get into creating highlights and insights, we’ll quickly look into customizing your Grain Workspace. Without adding the necessary context, it wouldn’t be possible for your team to understand and use the raw data. ‍

Tag all your recordings to help others understand the purpose behind the interview.

For instance, if a user interview is a part of ‘Product usability research’, then adding tags like #usability-study #user-interview makes it easier for everyone to find the recording and get the context. You can also tag your highlights, but we'll talk more about it later. ‍

Edit the title of the meeting. When we interviewed users to learn more about how they organize Grain Workspace, we titled the interviews clearly to help others in the team find and review a specific recording.   

Having the right title and tag helps you find what you’re looking for instantly!

Step 2: Creating and Organizing Insights

Once you set up the repository, you can get to creating insights. As we mentioned earlier, “reports” don’t have to be the atomic unit of research insight.

With Grain as your repository, the atomic unit of your research insight is a "Highlight" , a short video clip that captures the important moment that led you to the insight. Just select the text in the transcript from your user interviews to capture the key moments and turn it into a shareable video clip.  

As we hinted, you can add #tags to your highlights, making it easier to discover and share them with your stakeholders. Just type # to create your own or select an existing tag.  

All your highlights can be viewed via the Highlights page. You don't have to open a recording every time to view or share a highlight clip. Switch to personal view to see the highlights created by you or filter by tags to instantly find the insight you're looking for.

Grain Stories are a powerful way to make your case. Put simply, Stories helps you to stitch together the highlights you created into a video reel.

For instance, if you'd like to propose a different UI, then a reel of highlights capturing how customers struggle to use the product would help product managers and other stakeholders realize the gravity of the problem and make the necessary changes.

You can share the story by copying the URL or embedding it in your key presentation. In other words, every story can be a standalone insight or you can embed it in your documentation to put together a report in a preferred format.  

“The majority of my presentation is letting these video clips run, watching the reactions on stakeholders' faces and then briefly explaining some context—with any recommendations moving forward.”

- Nikki Anderson, User Research Academy.

Here’s how to use stories to share your research insight and maximize the impact of your work.

Step 3: Democratizing Your User Research Findings

The last step is to let everyone in your company collaborate, contribute, and leverage research data and insights to build a customer-first product.

1. The best way is to invite everyone to Grain Workspace.

With Grain, you're essentially building a shared video library —recording, annotating, and organizing every user interview and insight from you and your team in one place.

Once you add your collaborators and stakeholders, they can search, discover, and access every insight and user interview from the entire research team whenever they need—without any hand-holding.

2. Start sharing highlights and stories through preferred communication channels. For instance, Parabol uses #GOLD, a public Slack channel to share interesting nuggets from their customer conversations with the rest of the team.

We share interesting clips on Slack using #voice-of-the-customer channel as well.

3. Embed Grain highlights and stories on Notion, Miro, or any other documentation tools you use. More importantly, make your key presentations and reports 10x powerful by bringing in the actual voice of the customer.

4. Send your insights directly to Productboard automatically. With our Productboard integration , you can capture and push user feedback directly into your product roadmap. This way, you can ensure your research findings and insights are factored in before prioritizing the roadmap and product features.

Organize Your User Research

A user research repository, unlike what the name implies, isn’t just a repository. It helps different teams to leverage the research insights and make informed decisions. It helps your company develop a shared understanding of customers that researchers have already realized. It helps you build a ‘customer-centric’ culture.

Whatever research tool you decide to use to build the repository, ensure it’s easier to search, discover, create, and share insights! The goal is to make it a “home base” for your customer knowledge.

Related Articles

Best ux research repository tools in 2023 [reviewed], how to conduct user interviews effectively, get started with grain.

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A knowledge base is a repository for how-to and troubleshooting information. Knowledge Bases are commonly used by IT Support teams, but can be useful for procedural and troubleshooting information in any organization or team.

Learn more about how a knowledge base helps your team work smarter

What do people want out of a knowledge base? Using an IT Support team as an example:

• Customers want fast access to a solution, and relevant search results.
• Help desk staff want to be able to create new articles quickly.
• Help Desk team leads wants the space to be self curating, and do not want to spend a lot of time manually organizing content.
• Everyone wants a way to be notified when articles they are interested in have been updated or important notices are added.

Create a knowledge base space

To create your knowledge base space:

• Choose Spaces > Create space > Knowledge base space
• Choose  Space Tools  >  Permissions to set permissions for the space, including anonymous access
• Choose  Create  >  How-to  or  Troubleshooting  and follow the prompts to create your first knowledge base article

The knowledge base space blueprint includes everything you need to get started, including article templates, and a pre-configured homepage with Livesearch and Content By Label macros.

Page labels are essential in knowledge base spaces. These are used to add topics to your articles, and allows your knowledge base to become self-organizing over time.

Users will generally find articles by searching, and using the topic navigation on the homepage and end of each article, rather than navigating through a tree-like page hierarchy.

When starting off your knowledge base space, it's a good idea to brainstorm a few topics to get started.

Customize your knowledge base space

You'll need Space Admin permissions to do this.

To make it easy for your users to create knowledge base articles, such as your help desk or support team, we recommend customizing the how-to and troubleshooting article templates to make them relevant for your organization. The more guidance and structure you can put in your template, the faster it will be for your team to create great articles.

To edit the article templates:

• Go to Space Admin > Content Tools > Templates .
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You can also add additional templates, such as a policy or procedure page templates.

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To change the look and feel:

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• RSS - create an RSS feed and add the link to your knowledge base homepage (choose Help > Feed Builder ). Alternatively encourage users to create their own feed - useful if they want to keep up with particular topics (labels), rather than receive notifications for the whole space. 

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If your Confluence site is connected to another Atlassian product (via an application link ), you can make use of these great integration features:

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When you sign up to the Atlassian Research Group, we’ll ask a few questions about you. Your answers will help make sure you get invited to research that’s relevant to you.

We’ll invite you to research via email and include all the details so you can decide if you’d like to take part. You can always say no to an invite and you can unsubscribe at any time.

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We’re not just looking for people who love Atlassian or even who use Atlassian products. Anyone can sign up, and once we find a project you can help with, we’ll reach out. Be honest when answering questions so we can invite you to the right projects.

What do I receive for taking part?

After taking part in a research project we may send you a thank you gift, e.g. an e-gift card, swag, charity donation, or something else. The thank-you gift varies session by session, but we'll include its exact details in the email invitation, so you know what you'll receive before each session.

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The information you provide will only be used to match you with suitable research studies and won't be shared or sold to external parties. See our  Privacy Policy  for more detail.

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An open-source framework for machine learning and other computations on decentralized data.

google-parfait/tensorflow-federated

Folders and files, repository files navigation, tensorflow federated.

TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data. TFF has been developed to facilitate open research and experimentation with Federated Learning (FL) , an approach to machine learning where a shared global model is trained across many participating clients that keep their training data locally. For example, FL has been used to train prediction models for mobile keyboards without uploading sensitive typing data to servers.

TFF enables developers to use the included federated learning algorithms with their models and data, as well as to experiment with novel algorithms. The building blocks provided by TFF can also be used to implement non-learning computations, such as aggregated analytics over decentralized data.

TFF's interfaces are organized in two layers:

Federated Learning (FL) API The tff.learning layer offers a set of high-level interfaces that allow developers to apply the included implementations of federated training and evaluation to their existing TensorFlow models.

Federated Core (FC) API At the core of the system is a set of lower-level interfaces for concisely expressing novel federated algorithms by combining TensorFlow with distributed communication operators within a strongly-typed functional programming environment. This layer also serves as the foundation upon which we've built tff.learning .

TFF enables developers to declaratively express federated computations, so they could be deployed to diverse runtime environments. Included with TFF is a single-machine simulation runtime for experiments. Please visit the tutorials and try it out yourself!

Installation

See the install documentation for instructions on how to install TensorFlow Federated as a package or build TensorFlow Federated from source.

Getting Started

See the get started documentation for instructions on how to use TensorFlow Federated.

Contributing

There are a number of ways to contribute depending on what you're interested in:

If you are interested in developing new federated learning algorithms, the best way to start would be to study the implementations of federated averaging and evaluation in tff.learning , and to think of extensions to the existing implementation (or alternative approaches). If you have a proposal for a new algorithm, we recommend starting by staging your project in the research directory and including a colab notebook to showcase the new features.

You may want to also develop new algorithms in your own repository. We are happy to feature pointers to academic publications and/or repos using TFF on tensorflow.org/federated .

If you are interested in applying federated learning, consider contributing a tutorial, a new federated dataset, or an example model that others could use for experiments and testing, or writing helper classes that others can use in setting up simulations.

If you are interested in helping us improve the developer experience, the best way to start would be to study the implementations behind the tff.learning API, and to reflect on how we could make the code more streamlined. You could contribute helper classes that build upon the FC API or suggest extensions to the FC API itself.

If you are interested in helping us develop runtime infrastructure for simulations and beyond, please wait for a future release in which we will introduce interfaces and guidelines for contributing to a simulation infrastructure.

Please be sure to review the contribution guidelines on how to contribute.

Use GitHub issues for tracking requests and bugs.

Please direct questions to Stack Overflow using the tensorflow-federated tag.

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Microsoft Loop Adds GitHub, Jira, and Trello for Enhanced Collaboration

Microsoft's Loop app now integrates with GitHub, Jira, and Trello. This lets developers and project managers manage tasks directly in Loop.

Microsoft has announced new integrations for its Loop app with GitHub , Jira, and Trello, aimed at improving workflow efficiency for developers and project managers. These updates allow Microsoft 365 work and school account users to manage projects and track issues directly within the Loop interface, enhancing productivity and collaboration.

The integration with GitHub enables users to embed GitHub issues and pull requests into Loop pages. By using a simple “/” command, users can access a menu to select GitHub and follow in-app instructions to start integrating. This feature allows users to view and modify GitHub milestones, change assignees, or update PR reviewers directly from Loop. However, utilizing these GitHub features requires user permissions for the respective GitHub repository.

Enhancing Project Management with Jira and Trello

Loop's integration with Jira facilitates the viewing and managing of Jira issues. Users can alter the status, due date, or assignee of a Jira issue from within Loop, although this functionality is currently limited to Jira Cloud projects, excluding Jira Server and Jira Data Center.

The Trello integration operates on the same principle, allowing users to manage Trello cards by dragging and dropping them across swim lanes, adjusting members, and setting due dates. Additionally, users can access Trello's detailed card view directly from Loop.

Microsoft Loop   became widely available in November . Initially  introduced at Ignite 2021 , Loop has now launched for  Microsoft 365 E3 , E5, Business Standard, and Business Premium users. Compatible across web, iOS, and  Android  platforms, the app is also accessible to  Microsoft 365 consumer customers via mobile apps. While the availability of these features for Microsoft 365 personal subscribers has not been specified, the introduction of these integrations represents an enhancement in Microsoft's suite of productivity software.

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