Solution view counter and changing solution likes/dislikes
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Introduction
How do you know if the effort invested in creating a solution (knowledge base article) is worth it? Which solutions are valuable and which are not?
These are typical questions that almost every CIO, IT manager, or content creator wonders about.
Solution's View Counter
SolarWinds Service Desk (SWSD) has a metric that can help you answer these questions using real data.
The metric is called Solution’s View Counter, which measures every time a solution/article is viewed by someone. Each time this happens, either in the Portal or via email, the solution’s counter increases by one.
A person, no matter what their role in SWSD, is counted only once per solution and per month. If someone reads parts of the solution every day of the week in the same month, it will still be counted as a single view. However, if they read the solution once in March and then revisit it in May, it will be counted as two views.
The Solution’s View Counter is shown both in the portal, for requesters, and in the platform, for agents and administrators.
Portal view
Platform view
Important notes about the view counter
- The view count began on December 19, 2019.
- You can download the view count data as part of the export to a CSV feature.
- The Solutions Over Time report captures the solutions view trends (use Scope = Views].
Use this metric together with other powerful SWSD metrics:
- Number of thumbs up/thumbs down each solution received
- Number of times each solution was attached to an incident
Other solutions module features
- User can change their minds regarding the likes/dislikes they previously made on a solution.
For example, the user might have initially found a solution unhelpful and gave it a thumbs down. After the solution was updated the user finds solution valuable and then gives it a thumbs up or decides to remove the previous thumbs down rating by clicking thumbs down again, which removes the previous rating. - In the portal, requesters can sort Solutions by Helpful Articles, which are based and calculated according to the Net-Likes (= Number of Likes - Number of Dislikes).
- In the platform, agents can filter based on Helpful Articles.
With these options you can expect high accuracy around the helpfulness of your solutions, a data point that can be used by both agents and requesters.