Capturing Usage Information in Spark

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4 comments

  • Official comment
    Product Team
    Hi Paul,
     
    Before you begin capturing Usage data it is important to identify the user journeys in your product.
    1) A user logging in is obviously the most basic indication of usage but often insufficient
    2) Identify the pivotal points in your application that a user experiences where they derive value
    3) It is important to partner with Product teams to identify the key steps that may be important to track to distinguish users who are completing those steps versus tracking users who are not performing those steps.
    4) Having this insight lets you target specific users who are not fully adopting via Campaigns to help them complete those other critical journeys that will help them get value from your offerings.
     
    Finally this article should help you do this effectively in Totango - https://support.totango.com/hc/en-us/articles/202877345-Getting-Started-Guide-to-End-User-Data
     
    This article is technical but you can partner with your Product and Engineering teams to accomplish this.
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  • Sean Maguire

    Hi Paul - Just to clarify, are you trying to view usage of your CSMs in Totango, or usage data about how your customers use your products and how that's being brought into Spark? I suspect the latter, but want to confirm

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  • Paul Case

    Hi Sean, thank you for the response.

    I am looking to capture data on how our customers are using our product.  I would like to get more educated on what data other Totango users are capturing so I can work with my development team on our product changes to support this.

      

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  • Sean Maguire

    The below is pretty high-level and likely kind of obvious. I'm curious to hear what others think, and am happy to clarify where possible, but a few approaches I'm aware of are:

    1. Usage Percentage: Number of active licenses divided by number of available licenses
    2. Usage Frequency: Number of logins per month / week / day / hours, etc.
    3. Usage Intensity: Number of users per month / week / day / hour (this is similar to Frequency, but corrects for those times when you have one or two power users logging in all of the time, but the other 98% almost never logging in)
    4. Usage Duration: Time in system... Total time logged in, average time, max active login in 24 hour period, etc.
    5. Usage Scope: How many different things did they do while logged in?
      Did they see the homepage then leave, or did they click around and do multiple different things (I like the example of wikipedia... did you just read one page and then move on with your day, or did you spend 7 hours drilling down topic after topic until you somehow found yourself reading about Napolean's favorite horse color and the name of King Tut's cats at 3am)

    It also tends to vary depending on the nature of your product. Basically, what is the unit of measure?

    Sometimes it makes sense to track users, other times it might be number of transactions or clicks, or even number of dollars moving through a system, or forms created... how many widgets produced, etc., but the overall approach is still similar.

    What percentage of what they're paying for are they using? How often are they using it? How intensely are they using it? How long are they using it? What's the total, average/median, maximum, and minimum of these categories... how are those numbers changing over time, and how does this compare to other similar customers (are they above, below, or right at average)?

    Once that data is there, then the more important and interesting conversations can start: "What exactly do we need to do now that we know these things? How can we make the customer experience better and ensure they're getting the most from their investment in us?" 

    Hopefully this was more helpful than silly. As I said above, I'm curious to hear from others, too. Wishing you luck in your efforts!

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