1. Customer facing utilization reports: trying to represent utilization % in graph format isn't an option out of the box.  We send a stacked column chart of the utilization scorecards in an email.  To compensate we populate use another MDA object and pump the current score in one field and use a calculated field to equal difference in another, when reporting on both you always end up with a sum of 100.  





Cascade this across multiple scorecards, along with a custom palette for the object to match your corporate palette and you get a beautiful chart.  Coupled with some fancy HTML formatting in your template and a well thought out survey (link included) you give the customer a branded visual representation of value(at least with our product) with an included means to provide quick feedback which we close-loop of course.





2. Our individual feature adoption targets (Scorecard) is not linear over the Implementation process; starts slow and increases over time.  Maintaining a separate MDA object to assign a specific percentage target based on a customer's size and Lifecycle In Weeks was required.  





3. We do a lot of reporting based on the customer's Relative Week (since purchase) which is impossible to do as you cannot Group By number fields.  Simply transporting the numeric value into a string doesn't solve our problem due to ordering (0, 1, 10, 11-19, 2, 21, etc).  As above we have a reference object which maps numeric "1" to string "0001".

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Thanks for sharing this. Iam interested in understanding about your adoption targets use case. Do you capture this detail by running rules for your customers in onboarding/implementation stage?





What sort of actions do you drive if the goal you have set does not meet for a customer?

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We have a schedule and associated scorecard for each of our product features, indeed!





Right now the action is very human-driven.  Trusting email automation a bit more is where we would like to be but are wrestling with email compliance, ingesting Marketo opt-in/out info layered with Gainsight's black-hole of unsubscribe data.  Feel free to reach out if you would like to have a discussion on this topic.

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When we did our last NPS Survey, we needed to be able to send emails to customers depending on how they answered a multiple choice question. In the question, there are 5 options, and you can choose any combination of the five.





The question is presented to promoters and asks:

Would you be willing to:

• Allow us to use your logo on our site

• Provide a Testimonial on our behalf

• Be a part of a case study

• Write a story for our blog or publication

• Other

The hard part is this type of question populates each of these answers into it's own row in the database.





To solve for this, we created a bionic rule for a pivot to put a 1 in each column the customer had selected. From there, we wrote the data into an MDA table. This allowed us to pull the information into a Power List to send targeted emails to customers based on how they responded. Through doing this, we were able to follow up on what types of responses a customer gave.





From doing this, we now have a better understanding on how to solve for survey follow up on multiple choice/response questions.

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That's an awesome idea, thanks for sharing!  We're launching our first Gainsight NPS survey and will definitely need this exact use case.

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