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Thanks for your input: October 2017 community feedback results

wordcloud of comments form q1 2017 feedback

Part of improving as a useful service for everyone is listening to our community. Finding out what’s working, what’s not and what we can do next to help solve problems or meet user needs around making data easier to find and use.

To help this we’re establishing a regular user feedback survey every 3 to 6 months. Since this is our first one, it’s helped to give us a benchmark to start from and some useful insights for our product team.

As the analyst in the team, my happy place is in collating and interpreting data and recommending product improvements to based on this evidence. I thought I would share my findings in the first customer survey along with the data collected as an open dataset.

Who’s using, how often and why?

41.4% of responders classified themselves as Data Enthusiasts, 34.5% as Data Analysts and 41.4% of responders classified themselves in more than one user type.

This last insight what we call ourselves with respect to data is often quite subjective and not easily put into one bucket. We also tend to wear many hats in teams.

To improve the next survey we may look to use a more defined list of roles, however for our benchmark this gives us a good overall idea of who’s who on

As far as how often people are making use of, from our sample, 65.5% of responders visit every few months. 10% of responders visit weekly, another 10% visit annually. 6.9% visit fortnightly and the remainder of the responders visit infrequently or hardly ever.  

Chart showing what users did the last time they visited

The top reasons responders said they visited was to browse or look for a dataset (48.3% of responders). 13.8% said they were looking for guidance on how to supply open data and another 13.8% said they were browsing the dataset requests.

Column chart showing how often users visit

What do they think about using

We asked users to rate their last experience with as well as how easy they found it to locate the data they were looking for. For both users rated an average of 6.6 out of 10.

Alongside their rating we also received some insightful comments.

Some responders could use the search function just fine but the dataset(s) they were looking for were not relevant or not available.

Some users experienced completely different search results depending if they searched for file names, topics or abbreviations. This is something we can look to improve in two ways.

  1. Provide better guidance to releasing agencies about how to name data files and describe their data with quality metadata. We have a useful help guide on this however we’ll look to review and provide some further examples.

  2. Search could be improved if we increase the richness of content held in our search tool including indexing the data file (where they are machine readable) as well as the metadata. The hypothesis here is that it would improve the relevance of a user’s search query. The CKAN open source community has such a feature available that we’ll assess and if useful, we’ll consider installing this to help enhance the search on

Do our users talk about to others?

At the end of the survey we asked users whether they would recommend to others. Word of mouth (in person or digitally) is important in sharing knowledge and growing a community.

Getting an idea of how many of our users pass on positive stories to others about helps us understand how we can better support the community.

We calculated a score of minus 14 on this, not as high as we might have liked but good to get honest feedback to help drive improvements. If you’d like to know more about how this standard measure is scored you can read up on this here

The accompanying comments to the score provide some useful interpretation (maybe not so bad after all!)

Those that gave low scores tended to be data suppliers who used very rarely or just once a year. Comments were not overly negative, they just don’t use the site frequently so it could be a new learning process for them each time they supply a dataset.

Another comment mentioned wanting datasets grouped by topics to help make searching easier. As this functionality exists, we need to look into why they weren’t able to find this more easily.

A big thanks

Thanks to everyone that took part in our first survey, your input has been well received. We’ll look to run another again in 3-6 months as a check in. Meanwhile, you’re always welcome to submit your feedback or get in touch with the team on



Bronwyn Beagle is the Performance Analyst for Government Information Services, and she enjoys turning raw data about anything from anywhere into something interesting and actionable.




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