Question

Tracking top support cases by contact in account

  • 1 April 2016
  • 7 replies
  • 74 views

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Hi team - I have a request from one of our teams to keep tabs by account of those that call in often into our support queues (phone, email, chat).  This is all done in cases so I'm thinking in the least just throwing another report type within the case view but I'm curious if anyone has anything that could be more actionable?  For instance if someone is calling in a lot, then create a CTA for the CSM to take a look.  I haven't been able to wrap my head around how that could be done.

7 replies

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Absolutely Brandon - using a lot of cases/calls as a driver for creating a CTA is key.  Also recommend aligning with your support team on it.  Here are a few documents that support how we handle it (we set CTAs for Urgent tickets-so CSM is aware, customer has over 5 tickets open, or a ticket has been open for over 21 days as an example).  This should help -

https://support.gainsight.com/hc/en-us/articles/211248617-Support-Risk
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Denise - thanks for the reply.  I'm aware of these types of CTAs and this won't help solve the problem.  We tend to have 200+ users that may call into our support line from one account so it's hard to apply rules to the entire account without having CTAs fire all the time for 'high volume of tickets'.  In actuality, it may not be.  What we want to do is spot check problem children utilizing our support a lot that may be really frustrated and have a CSM reach out.  Does that make sense?  
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Is there criteria you could use to identify these potential problem children?  Or would this be something where you would want Support to create a CTA for acting on? What ticketing system are you using?
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The criteria would simply be 'volume of cases submitted within x time period'. We use Salesforce cases.
Userlevel 7
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Hi Brandon - a couple thoughts on this.



When designing rules, we find it usually helpful to start with putting down on paper the workflow and business challenge


  • Imagine that you had to solve it without any automation. 
  • What are the metrics that you'd be taking as inputs, what are the triggers, what are the inclusion/exclusion parameters? 
  • This helps you wrap your head around how it would work in a manual sense - from there it's easier to build the automation once you have the workflow defined.
If you want to spot check a percentage, I'd recommend a couple approaches depending on your business needs:


  1. Best scenario would be to look at secondary or tertiary criteria that would direct your spot check efforts - focus on customers with upcoming renewals, high ARR or congruent risk criteria - this will help you get the most 'bang for the buck' in support review effort
  2. Another option would be to assign all customers that meet the rules criteria to a manager (support or otherwise) and they would hand pick which customers they would investigate deeper. This is only partly automated - and the support manager would likely be using some other criteria other than pure random to choose which CTAs would get attention, so ideally those criteria could be used in Option 1 to drive more automation.
Hope this helps.
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Thanks Dan.  It does help.  The challenge for us is always going to be automation since we have 5000+ customers and each account could have 1-200+ users.  Trying to navigate how to isolate those users who are in a digital haystack is challenging.  



Manually, I would solve this by running reports and seeing specific users with high support cases and manually creating CTAs to address....how to automate it further is where I'm stuck.
Userlevel 7
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If you're able to get access to the data from your support system from Gainsight that shows the specific users, it should be fairly straightforward to build a rule that triggers an automated CTA based on users that pass a given threshold in a certain period of time. 



Another option would be to use a rule to bring that data into the Gainsight MDA and then it would be available for reporting and rules criteria that way. 



You're definitely on the right track of thinking through how it would be done manually first and what the gates/decision matrix is and then building the rules to perform the automation. 

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