Early this year I started working on a search tool that was being developed for a UK based enterprise. The high-level brief was to build a search tool that would index data stored in the form of millions of documents, images, text, videos, etc. This data is stored in different servers all over the world and we had to make this data easily accessible to the employees while keeping data security in mind.
I joined the team as Lead Experience Designer. My job was to understand what the employees wanted through design research and feed in all those insights into the business. The next part was to build this search tool and test it out with 100s of users in different locations.
Here are few of the learnings I got as an Experience Designer after launching version 1 of the search tool.
The 8-second attention span is real.
With increasing digital mediums our attention span is decreasing. A Microsoft study revealed that we now have an attention span of eight seconds–making our attention span shorter than that of a goldfish (at nine seconds).
I found very similar results in my user testing after launching version 1 of our product. Users would become frustrated and quit using the tool if they did not get the information they were looking for under 10 seconds or within first 15 results.
In one of the interviews, the user expressed his frustration by saying
“10% of the time the tool is successful in finding the right information and 90% of the time, it’s too many results to look through.”
Duplicate and redundant data is a huge problem in large organizations.
While doing my initial research for the project, I came across a problem which is very common in large organizations, redundant data. This impacted our product reliability as the tool would index and display 100s of same files with the same metadata or different versions of the same file sitting in different server locations. This kind of search results confused users and made our tool look unreliable and untrustworthy to the users.
To address this problem, as a first step we embedded a duplicate identifier within our tool which would identify the files with the same data and reports it to the relevant information management team.
Users want relevant information, not more information.
When users search for information, they are not looking to gather as much information as possible, they just want to see the most relevant information. Going to the next level of relevancy, users expect information personally relevant to the work they do in the organization.
To enhance our search tool we started to capture data metrics and derive insights to provide a better user experience. This would enable us to provide results that are personally relevant to each user in the future.
A good search tool should not require extensive filters.
We initially introduced filters in order to provide the user with a capability to narrow down search results. What I found out during the user testing sessions is that going through filters and using them is not a good experience for the users. Users expect a search engine to provide relevant results without using filters extensively.
Old habits die hard!
This one was the most obvious finding from my user testing. When you introduce a new tool within an organization you are altering employee’s existing way of working. The employees who have been in the organization for a long time find it hard to pick up new tools even if they are easy to use. These employees would want to stick to their existing way of working even if takes them more time to complete their tasks. Whereas new employees take less time to adapt to new ways of working.
When you introduce a new tool within an organization you are altering employee’s existing way of working.
Hence to increase the adaptability of the tool we looked at taking a persona based approach that would enable us to deliver a more personalized experience to the user, based on their existing way of working.