After importing customer data in Harvestr, you can leverage numeric attributes to automatically calculate the business impact of your Discoveries to make the right product decisions.
You will be able to answer questions like:
What is the cumulated MRR/ARR of all customers who are linked to a specific Discovery?
How many Enterprise customers have requested a specific feature?
What is the average user base of all customers who requested a specific improvement?
The fields that will help you answer these questions by computing customer data at the Discovery level are called "Customer attributes aggregation fields".
Creating customer attributes aggregation fields
REQUIREMENT: to create a customer attributes aggregation field, you first need to create customer attributes. You can import customer attributes with our Excel import feature or synchronize them from Salesforce, Hubspot, or Intercom. The field's creation settings will remain inactive if you do not have any customer attribute.
To create such a field, go to the product section, click "edit fields" in the top right corner, "add field", and select the Customer attributes aggregation type.
You will then be able to choose:
which customer attribute will be computed for each Discovery
the unit you want to assign to this new field and its position (to the Left or Right from the value where it will be displayed)
the calculation rule, i.e., how attributes values will be computed for all customers who are linked to a Discovery:
SUM (only for numeric attributes): calculates the sum of all attribute values of all customers who are linked to a Discovery
AVERAGE (only for numeric attributes): calculates the average of all attribute values of all customers who are linked to a Discovery
MEDIAN (only for numeric attributes): calculates the median of all attribute values of all customers who are linked to a Discovery
MINIMUM (only for numeric attributes): calculates the lowest of all attribute values of all customers who are linked to a Discovery
MAXIMUM (only for numeric attributes): calculates the highest of all attribute values of all customers who are linked to a Discovery
COUNT (for all attribute types): counts how many customers linked to a Discovery have a value for the selected attribute that is different from 0 and false.
COUNT filters can also be added to the COUNT rule to count how many customers linked to a Discovery have a specific value for the selected attribute.
Here are some practical examples that you can use for your prioritization.
Cumulated MRR/ARR per Discovery
In the following example, our companies have a Monthly Spend field that is equal to their MRR. We use this attribute to create a "Cumulated MRR" field that will sum all the Monthly Spend values of all companies who are linked to each Discovery.
The volume of feedback from US customers
In the following example, our companies have an HS Country field that is equal to their country location (USA, Canada, France, etc.). We use this attribute to create a "US customers" field that will count how many US customers provided feedback on each Discovery.
Using Customer attributes aggregation fields to prioritize Discoveries
When the field is created, it will be added to all your Discoveries. In the previous example, each Discovery will have a value in $ for the "Cumulated MRR" field we created. This value will be displayed inside of your Discovery in the section dedicated to numeric fields on the right.
When you create a Customer attributes aggregation field, it will also be displayed as a new column in your Discovery table. You will then be able to sort Discoveries by this new parameter and prioritize them based on criteria such as Cumulated MRR.
If you do not see the newly created field in the table, go to your table field settings to ensure it is displayed.
If you have requests or ideas about how we could improve Customer attributes aggregation fields, we'd be happy to hear your thoughts.