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Search and filter: 5 best practices for your insights repository
Research excellence

Search and filter: 5 best practices for your insights repository

Few features play such a critical role in the success and overall experience of an insights repository as those surrounding search and filter. In this post we look at 5 best practice considerations to ensure that your repository is set up to scale.

Dan Robins
January 5, 2022
Building an insights repository with a powerful search and filter capability ensures users can quickly and easily access relevant research and insights.

By nature, insight repositories should increase in value as more research is added. However, poor search and filter experiences can often become a hindrance as repositories scale, depleting the overall value of your repository. 

In this post, when we refer to an ‘insights repository’ we mean a structured place to put the information your organisation has gathered through research. This might be focused around a single team or product, or the consolidated findings of many teams, disciplines and tools. 

We’ve seen many different tools used by teams to build insights repositories, and the ability to search and filter is a key job for both the researchers contributing to the system, as well as the stakeholders and wider teams who are predominantly consuming the knowledge.

In this post we look at 5 critical search and filter best practices that will ensure your repository is set up to scale and avoid timely rework later.

Why does the search and filter experience matter?

Having a filterable repository enables users to quickly and effectively narrow a body of information to their personal interests. It also allows users to browse and find relevant content that they may have not otherwise known about. If fellow researchers as well as wider teams and stakeholders are engaged with your insights repository, it’s more likely to encourage a network effect - meaning the more your insights repository is used, the more valuable and powerful it becomes. 

To demonstrate the importance of building an insights repository with a powerful search and filter capability, let’s look at 2 specific use cases:

1. As a stakeholder, I want to find all the research and insights associated with our current project, so that I can make an informed decision on what steps to take next

2. As a researcher, I want to find all the research associated with a particular topic, so that I'm able to inform my new study and ensure I’m not repeating previous work by other researchers

In both instances, I want to quickly access existing and relevant knowledge that we might hold as an organisation.

Whilst an insights repository is in its earliest stages, a basic keyword search function will add value in allowing both user types to find relevant research reasonably quickly. But what happens when this repository scales to 10s of insights, or 100s, if not 1000s?  This is where advanced search and filter capabilities really become paramount - when repositories begin to scale.

Having large bodies of knowledge at hand is unquestionably a powerful thing for any organisation. However, if it's difficult to filter that knowledge to a specific interest, you lose the benefits of it being consolidated altogether. It’s therefore important to build your repository with the right foundations - ensuring that when you add your first insights, it has the capabilities to scale with you. This makes life easier in the long run and allows you to quickly and effectively onboard new contributors and consumers when the time is right.

5 search and filter best practices for your insights repository

Let’s look at 5 best practices that you should consider when building your own insights repository to ensure that it’s usable and scalable:

1. You should be able to tag every piece of research added to your repo

Tags make information accessible. Without tags, filtering your repository is extremely difficult. In order to scale your repo effectively, the first (and arguably most critical) function is to ensure that you can tag data and create themes of tags. This is usually referred to as ‘managing a taxonomy’. Taxonomies evolve and should be regularly reviewed and updated as your repository scales. It’s therefore important that the solution you build your repository in allows for the easy management of tags.

The ability to index your data through tags and themes is one of the most critical jobs that an insights repository should enable in order for effective filtering. A strong taxonomy solution will enable you to manage both tags and themes across your repository quickly and easily.

2. Tags should be used to help people filter the data

A comprehensive set of filters helps users find knowledge faster. Filters can be of varying levels of granularity, yet should be intuitive and differentiable so that all different types of users (including wider stakeholders) can understand them and know what to expect in the event of selecting an option. 

In Dualo, filters are bespoke to your organisation’s repository, as they are organised in accordance to the tags and themes in your taxonomy. Meaning that the way in which research is added and tagged is intrinsically linked to how it is searched for and found. This allows users to select filters that are relevant to the knowledge that is in the system, and ensures that as your taxonomy evolves over time, so does the filter experience.

In Dualo, the tags and themes in your taxonomy automatically translate to filter options. As your repository and the way that you structure your data evolves, so does the filter experience.

3. The number of search results should be presented dynamically

When displaying unselected filters, the best filter experiences show the counts for each option if they were to be applied to the current search query. This is particularly common in ecommerce experiences, but can (and should) be appropriated for your insights repository too.

The ASOS filter experience indicates to users that by selecting specific filters, they are narrowing their search.

For example, in the graphic below, hovering on a count tells the user that by selecting ‘Laptop’, they can narrow their search to the 8 insights and 11 studies that have this tag.

Further, by dynamically updating the total number of results every time a new filter is applied, you can hint to the user which is the shortest search path. They can then decide whether to add more filters and narrow their search further, or remove filters to include a broader range of results.

The Airbnb and Dualo filter call-to-actions display the total number of results which dynamically update as filters are applied and removed.

4. It should be easy to edit or remove filters

Drilling down and narrowing your repository with filters should be an easy and intuitive process for all users. The trade-off is that users may accidentally select an incorrect filter, or simply find that they would like to broaden the parameters of their search after it has taken place. It’s therefore important that users can easily remove filters without having to refresh the page or begin their search and filter process again. Once again, the objective is to ensure the user experience is as seamless and fast as possible to improve the chances of finding relevant research and insights.

Users should be able to easily unselect filters, without needing to perform a new search.

5. You should be able to perform search and apply filters simultaneously

There may be instances where users have a specific search term or keyword in mind that is more focused than a tag or filter option available. Best practice search and filter experiences allow users to search and filter separately, as well as simultaneously. 

For example, a user may have a search term such as ‘buttons’, which doesn’t have its own dedicated tag or filter in the repository - the results of a search using ‘buttons’ as a keyword therefore might be quite broad. In this scenario, the user may wish to also apply filters to the search term in order to focus the results. For example, adding the filter ‘mobile’ alongside the original keyword ‘buttons’ will display results that include both the search term and the applied filter.

Users should be able to perform a search and apply filters either separately or simultaneously.

In summary

Intelligent search and advanced filter capabilities help to provide a delightful user experience for the users of your repository. By helping users drill down to specific research and insights based on their personal needs with ease, they eliminate the need for numerous searches and allow for unintended discoveries in niche areas of your knowledge base. 

Whilst the end result of a powerful search and filter capability in the context of an insights repository seems simple from the end users’ perspective, there are a number of considerations to ensure that it delivers the best experience, particularly as it scales. 

Well-designed search and filter capabilities improve the user experience for both the contributor of research and the consumer of it. They enable researchers to efficiently see what research has been conducted before them, and stakeholders to self-serve critical knowledge without having to pull researchers away from what they’re currently doing to help them find this information. 

Different tools have different ways of maximising the value and impact of research and insights. And whilst there are certainly other significant factors and features to consider when building your own repository, few feature areas play such a critical role in its success as the search and filter experience.

Further reading

Search and filter UX best practices

How to build an Ops-first Research Practice

Taxonomies - the make or break of a research repository 

How to structure product insights to maximise value and impact

The tools being used today to build cross-team insight repositories

You can learn more about the process today’s best product organisations are following to level up their research operations by downloading a free copy of our User research is broken: A guide on how to level up your research operations playbook, available here.

About Dualo

Dualo is an insights hub used by digital product teams to get more repeatable value from their user research and insights, so that stakeholders can make informed and timely decisions across the organisation. If you're interested in learning more, please request a demo and a member of our team will be in touch.

Dan Robins

I’m a design, UX & strategy lead with a passion for storytelling. Proud member of Dualo’s founding product trio. Always seeking new inspiration.

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