The Complete Guide to User Research Software & Tools

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Full Feature Analysis of User Research Software

1. Gathering & Amalgamating Customer Research Data

Integrations

No matter the service you provide, data on your customers will come in all shapes and sizes. Your product management and/or user research team is like dealing with reams of customer data, from customer purchase histories to live chat/support ticket logs to NPS scores to survey responses to one-on-one customer interview recordings.

Most user research software we examined offered some third-party data collection features to make your customer data gathering and warehousing easier.

Most teams will use a whole battery of third-party applications to handle various parts of their business, from Dropbox for storage to services like Lever for recruitment. Data integration allows those third-party applications to talk to each other and import data from one application to another.

Seven of the nine solutions we examined at a minimum allow data integration through Zapier, a popular third-party tool that allows users to pass data automatically between other products.

JIRA and EnjoyHQ have the broadest capabilities to gather and amalgamate customer data, including native integrations, which in some instances means a user research or product manager can get the integration working without engineering or IT, which is a huge benefit.

On the opposite end of the spectrum, Optimal Workshop and Aurelius do not support third-party integrations at all, not even through Zapier.

Zapier, while a good solution, isn’t as good as a native integration, the gold standard. At Instratify, we use Zapier a lot, but the set up can sometimes be tricky, and because there are three applications involved (as opposed to just the two applications a native integration involves) there can be more issues.

This feature frees your team from dependence on third-party software, meaning you will not be at the mercy of whatever developer sold you that software. If Zapier decided to drop support for an application your team uses or to raise its price above your range, your team would be stuck.

EnjoyHQ, productboard, JIRA, and Aha! offer native integrations, in addition to integration with Zapier.

Most user research and product teams absolutely need to amalgamate customer data to drive better decisions and effectively understand their customers’ behavior, which means this lacking any third-party integration features is likely a deal-breaker for most teams.  

That said, if your team does not need to share data between applications, this aspect of Optimal Workshop and Aurelius will not matter very much to you.

Video Uploading

All nine of the top user research software allow text and image uploads, but your team may need to upload video as well.

Of the four products that offer native integrations — EnjoyHQ, productboard, JIRA, and Aha! — only JIRA and EnjoyHQ allow video uploads. EnjoyHQ supports most video file types, including .mp4, .mov, and .avi. JIRA allows your team to upload a similar range of file types, although it uses HTML5 to display video, so which file types users can view will depend on what browser they use.

For the cheaper of EnjoyHQ’s two plans, your team is only allowed 20 video uploads per month, while the more expensive plan permits unlimited video uploads. Similarly, the monthly cost of JIRA varies based on the size of your team.

2. Organizing & Analyzing Customer Research Data

Once you have customer data amalgamated in your customer research tool, having the right capabilities to organize and tag data is essential to discover a broad range of insights you might miss with blunter instruments.

In this regard, EnjoyHQ, productboard, and Aha! stand out with superior tagging and segmenting abilities, as the other six user research software have only rudimentary data-organizing features.

“All data in aggregate is crap. Segment or die.” – Avinash Kaushik

Among those three options, EnjoyHQ and Aha! further stand out because they allow your team to tag feedback automatically based on rules, as well as break data into segments and sort feedback by user properties.

User Properties

When your team is dealing with a large base of customer data, the ability to track and segment by user properties is vital. This feature would allow you to segment, compare, and contrast data from certain groups of customers.

You define these groups of customers by a common characteristic (i.e., user property) such as average customer value, customer age, active user, churned customer, etc.  Each customer then can have many user properties associated with them.

Only EnjoyHQ, productboard, and Aha! allow you to assign user properties to customers in this way.

For us and many teams, the ability to be able to segment our customer research based on different customer groups is critical. We think Avinash said it best: unsegmented customer feedback isn’t useless, but it’s much harder to drive effective business decisions on unsegmented customer feedback.

For example, your team might have just rolled out a sweeping update of your user interface and want to know what your users think of it.

Because your users might disagree about what works well and what does not, feedback from different types of users should carry different weight in your analysis. You may want to prioritize feedback from the users with the most expensive plans or have shown the lowest price sensitivity, as they likely have a heftier impact on your business than the others do.

Tagging

Tagging qualitative customer data, whether it’s from a customer interview, open-ended survey response, on-site poll, support ticket, or NPS response is critical. Having the ability to create, customize, and modify your own customer tagging taxonomy is essential for most teams.

Some tags come pre-created, such as sentiment, but the ability to customize your tagging to what’s important to you will be a deal breaker for many teams.

Tags can be used anything to define insights, group bugs, and feature requests, UI issues, and emotions, just to name a few.

At Instratify, we like to use tags on a per-project basis to analyze open-ended feedback from customer interviews, and use tags across all research projects to grow our database of shared customer understanding across all of our user data (e.g. paint point, driver, great copy, bug, feature request, UI issue, etc).

Most of the user research software we examined allow you to create custom tags, except Google Docs and Airtable. However, while there is no specific tagging feature in Airtable, given its nature as a cloud-based spreadsheet database, there are alternative ways to accomplish the job of tagging.

The real difference between the tools comes down to the next category of features we will explore — segmentation.

In other words, how powerful is the slice-and-dice feature of the tool to segment and analyze customer data and feedback, including by your own custom tagging taxonomy? For this, as we detail below, Aha!, EnjoyHQ, and productboard come out on top.

Segmentation

For similar reasons, the ability to break up your data into segments will be a must for most product management or UX research teams. This allows you to isolate the data you need, avoid wading through reams of irrelevant information and compare and contrast customer data.

A segmentation feature allows you to assign certain action(s) to a segment you name, and then the user research software will group all users who fall within the defined segment together.

This defined segment can be saved for future reference and analysis, as well as compare and contrast against one or more segment(s).

EnjoyHQ, Aha!, and productboard allow you to create customer segments based on user properties and tags, but also on your internal team’s actions (e.g. which of your team members have viewed or updated a document).

For example, this could mean separating customers by age or location or separating documents based on which team members have viewed them.

EnjoyHQ, Aha!, and productboard’s segmentation features allow you to layer multiple actions in a single segment, meaning you could spotlight people under 30 who live in the northern United States, or feedback tagged as expressing negative user emotions. More importantly, this segment, once created, will automatically update as new users and new actions are taken.

Automation Abilities

Automation allows your team to establish rules to automatically tag and sort feedback as it comes in

Aha! and EnjoyHQ set themselves apart here by offering automation features. Google Docs also includes automation and rules features, although it does not support user segmentation or allow your team to organize feedback along user properties.

Rules in EnjoyHQ or Aha! can work along with any user property or tag.

With automated tagging features, you can write a rule to delete every document that has been viewed by a team member after two weeks or to label any document that uses certain keywords or phrases expressing negative sentiment.

Further, you might, for instance, want to flag every response you get that mentions a bug or a certain competitor.

Moreover, one of our favorites is to set rules to automatically categorize incoming customer support and live chat tickets based on keywords into the tags of UX Problem, Positioning Problem, Product Problem, or Feature Request.

Automatic tagging can save you hundreds and thousands of researcher hours. Having a team member(s) comb through hundreds or even thousands of responses to tag items like these is a massive waste of time with the technology available today.  

Feedback automatically tagged for you can also help keep things consistent across everyone using and inputting data into your customer research tool. You might, for example, want to highlight any survey response that uses the names of certain competitors, and, over time, you decide to either add new names to the list or take old ones off.

Using the automation features in Aha! or EnjoyHQ, you would not need to worry about manually combing through all of the responses before you found the ones you wanted.

Changing your criteria would be a matter of tweaking a few rules rather than giving your staff new instructions and hoping for the best.

3. Reporting & Sharing Customer Research Data

Reports and Visualizations

For the data savants on your team doing the meatiest bits of analysis, raw numbers might be a convincing way to tell a story about your customers. For everyone else, though, a well-designed chart or graph will almost always be better.

Except for Airtable, all of the top user research software allow your team to create reports and visualizations. Those reports can display the change in conversions over time or the share of customers who are sticking with your product year after year in a way that make the trends apparent to your team.

Collaboration

The ability to collaborate and share insights with your team can multiply the value that your user research software has, especially as teams are increasingly spread around the country and the world.

Collaboration is a big category. To simplify things for now (we might update this post at a later time), we defined collaboration across two dimensions: the ability to share data outside of the tool, and the ability of team members to comment within the tool.

For sharing, we looked at whether the tool can share info directly to Slack (we used Slack as it’s one of the most dominant office messaging tools) as a proxy.

Slack

EnjoyHQ, JIRA, Aha!, Airtable, and Google Docs all enable your team to share information with Slack, but the rest of the pack does not.

Commenting

In one way or another, all the user research software examined allow team members mechanisms to comment in one way or another.

Search

When it comes to your user research needs, having a customer research tool with a robust search engine is something most teams are looking for, so you can easily find exactly what you need within a few minutes, especially when the top brass asks you what you know about X and expects an instantaneous answer.

All the software tools we examined have, at the minimum, a basic search function.

While JIRA and Aha! lack a dedicated search function to deal with user insights, Airtable and Google Docs have neither a dedicated search function nor particularly usable sorting and filter features.

For example, Google Docs only allows your team to search along a few hard-wired options such as phrases included in the filename or date modified.

Both Dovetail and Aurelius offer search function with text querying, decent sorting, and minimal filters. productboard and Optimal Workshop offer dedicated search, but nothing beyond basic filtering and sorting.

EnjoyHQ has the most robust search function, allowing you to search and sort across multiple criteria at once. It uses an “AND/OR” structure to allow your team to combine as many filters as you need in your search and to search any combination of user properties, documents, segments, date, tags, or insights.

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