In this article we provide an overview of the most popular tools being used today to manage and distribute insights across product organisations. We then consider the core requirements that a solution dedicated to tackling this challenge head-on would need to address in order to add real value to insight-driven teams.
The drive to be recognised as a truly customer-centric business remains top of the agenda for most organisations today. With many product teams committed to improving the access to insights from user research as one of their current objectives.
Given the lack of dedicated tooling currently available for this, people have started to build centralised libraries of the research and insights that exist across the tools and teams within their organisation - typically repurposing products designed for a different set of use cases to get the job done.
We’ve observed a number of different solutions being used by organisations. Here are the most popular ones we’re seeing time and time again, including a summary of the pros and cons of using each one as a shared insights repository.
We then highlight the core needs that a dedicated cross-team insights solution needs to fulfil in order to provide real value to today’s insight-driven organisations.
Most teams default to using a shared drive such as Google Workspace or Microsoft 365 to store and share the key outputs from their user research.
These tools make it really easy to upload research materials to a central place but start to fall down when attempting to pool research and insights together across teams. They typically require the use of another tool to act as the ‘front end’ for the drive itself, something which researchers can use to start properly indexing the information stored across the drive.
What works particularly well?
- Most people are familiar with using a shared drive to make documentation available to others or to look for information previously shared across the organisation
- Quick and easy to upload multiple documents
What doesn't work so well?
- Limited to keyword search when attempting to discover new and existing research and insights, as you’re unable to create a proper taxonomy across the findings uploaded to your shared drive without leaning on another tool
- Hard to keep track of the research findings being shared across teams due to inconsistencies in how teams structure their own data on the drive
Many teams have started to use collaborative tools such as docs, sheets, and slides to create a shareable index of all of the user research and insights being generated across their organisation.
Sheets being by far the most popular choice here, particularly smart sheet tools like Airtable that allow you to more easily classify your research using tags. However, sheets were never designed to engage and inspire stakeholders which massively limits their effectiveness as a tool for storytelling to the wider audiences across your organisation.
What works particularly well?
- The collaborative nature of these tools helps you develop towards a fully democratised library of knowledge across teams
- The ability to tag your research allows you to start highlighting broader patterns in the data being contributed across teams
- You’re able to encourage people to start linking to any raw data in other tools which underpins their research findings
What doesn't work so well?
- These solutions become difficult to maintain as a company scales its research efforts (it’s for this reason that spreadsheets are typically used only as an ‘MVP insights repository’ to test initially the appetite for consolidating research across teams)
- It’s near impossible to turn your research findings into presentable insights that inspire action using a spreadsheet solution
- Wider stakeholders are unlikely to end up self-serving research findings from a spreadsheet repository, especially your more senior sponsors
Wikis, like Confluence and Notion, are another popular tool being used by researchers to share their research findings with others across the business.
The benefit of using wikis to distribute research and insights is that, like shared drives, they’re usually already being used to upload and share other organisational information across teams. However the difficulty comes in knowing exactly where to look for your research findings amongst the other documentation that exists within your company. Something which becomes more and more of a problem as the organisation scales.
What works particularly well?
- People will be familiar with how to contribute to and navigate the wiki if one is already being used at your company
- The collaborative nature of these tools helps you develop towards a fully democratised library of knowledge across teams
- You’re able to link fairly easily to any raw data in other tools that underpins your research findings
What doesn't work so well?
- It’s difficult to maintain a consistency in the way that research and insights are presented by researchers; people can develop their own templates for sharing research findings but tend not to share these across teams
- It’s hard to signpost to wider stakeholders how to navigate the research specific pages that have been created across teams, making it difficult for people to self-serve this information without first coming to a researcher for guidance
- Limited to keyword search and basic tagging when attempting to discover new and existing research and insights
Some of today’s more sophisticated research analysis tools, either qualitative analysis tools such as Dovetail or quantitative analysis tools like Hotjar, offer their users the opportunity to turn the analysis of research or user behaviour into shareable insights. You can also apply a taxonomy to your research findings.
The main challenge with using a tool designed for research analysis as your insights library is that these tools tend to focus on the processing of either qualitative or quantitative data. Researchers conducting mixed method research are still using shared drives, sheets, and wikis in an attempt to create one truly central repository for research and insights across tools and teams.
What works particularly well?
- Able to create and apply a taxonomy to help structure your research materials
- Can build atomic research libraries with the ability to link directly back to the raw data
- Able to translate your research findings into shareable insights
- These tools are designed to scale in line with your research efforts
What doesn't work so well?
- These tools tend to be dedicated to the analysis of either qualitative or quantitative research, making it hard to create a mixed methods insights repository where the findings of both types of research are available side by side
- Many of the product teams we’ve been speaking with mention that their wider stakeholders are highly unlikely to end up self-serving research findings from their research tool repository
- These tools also don’t seem to resonate well with senior stakeholders, who find the way they are structured overwhelming and want to cut to the chase without having to deep dive into the data
- These systems can be expensive for teams looking for a place just to store and present the key findings from their user research
The majority of organisations we’ve spoken with are using some form of chat tool, like Slack, alongside their repository to help with the distribution of insights across teams. With some companies going as far as building their own Slack bots in an attempt to move their organisation towards more of a self-serve knowledge repository.
What works particularly well?
- People are familiar with using chat tools to receive key information being shared across an organisation
- Stakeholders can self-serve insights asynchronously from when they were shared
- Tools like Slack are well integrated with other apps, making it easy to automate distribution from the tools you’re using to conduct your research
What doesn't work so well?
- Previously shared insights are hard to rediscover as they quickly get lost by ‘travelling up the feed’ as more and more messages are posted to a channel
- These tools were designed for sharing and not creating, restricting their value as a tool for research to only the distribution and socialising of research and insights; they need to be integrated with other tools to really come to life as an insights solution
The main problem with the tools being used as shared insights repositories today is that they weren’t designed specifically to help teams with achieving user research excellence - they don't help with consolidating, discovering, and distributing the key insights from research across teams.
Shared drives, sheets, wikis, and research tools may help you get so far with the consolidation of research and insights but make it difficult to neatly thread together the insights from different teams and disciplines, especially at scale.
Most of today’s tools provide limited discovery and distribution options. They weren’t designed to help make insights actionable and accessible for wider product stakeholders.
Researchers end up becoming frustrated with these solutions, typically conducting their work as a new silo, and end up creating yet another study that gets filed away on the shared drive after just one use - losing all repeatable value.
Stakeholders give up searching for the key insights in lengthy research reports and data sets and continue to request specific insights and recommendations, pulling researchers away from actually doing research.
None of today’s most popular choices provide the functionality required to complete the consolidation, discovery, and distribution of research and insights all in one place.
It’s difficult to answer this question head on as a publicly available solution for this hasn’t yet been developed in its entirety (and we’re yet to see a full view of the dedicated tools that Uber and Microsoft have developed for their own teams).
However, through conducting our own research and observing how people are using today’s tools to manage and distribute insights across the teams within their organisation, we're confident of what the core requirements for a tool like this include:
- Quick and easy for anyone to upload research and create insights
- Encourages consistency in how research findings are structured across teams
- Collaborative in its nature, allowing researchers to work together on creating a repository of shareable research and insights, regardless of team or discipline
- Able to link insights to the raw data that underpins them (ideally well integrated with other apps and tools to make this process even easier)
- Engages non-researcher and senior stakeholders with user research (ideally something that these stakeholders understand how to navigate themselves)
- Scales successfully as a platform in line with your organisation’s research efforts
We haven’t seen a tool that meets all of these needs, it’s why we’re building Dualo.
If you enjoyed this article be sure to grab a free copy of our User research is broken: A guide on how to level up your research operations playbook to learn more about the big shift to shared insight repositories, available for download here.
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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