You can use the filters in MemberView to mine your MemberView data on-the-fly. By applying filters on reports you can view the credit union experience metrics by member demographics, member experience, member relationship, delivery channels, account types, and KPIs.
Apply one or more filters to any MemberView report by accessing the Filters drop-down menu underneath the Report Generator as shown below.
Expand the data filters by clicking on the down arrows to make choices from the following filters:
Event Experience
By default, MemberView lists all experiences your credit union measures when you generate a report. You can limit the experiences you want to show by using the Experience filter. This filter is useful for aggregating experiences. For example, if you want to find out the Promoter score for lending by combining the mortgage experience and the consumer loan experiences only, choose those two experiences from the Experience filter and apply them to the entire report.
Delivery Channel
Choose one or more filters from the delivery channel list to filter by delivery channel. This filter is available if your credit union has provided delivery channel information with its member email list for email invitations to online surveys or if your credit union is asking members which delivery channel they used in its surveys.
With this channel you can discover things such as how easy it is for members to do transact business via drive-thru versus phone or branch. Discover how easy it is for members to apply online for a loan versus applying by phone or face-to-face.
Account Type
If your credit union supplies specific account type in your experience files or asks members which account they transacted on or opened, you can filter on account types such as checking accounts, savings accounts, IRAs, credit cards, vehicle loans, home equity loans, and more.
An example would be determining the difference on your team’s score on an upselling question such as “Did we offer you an additional product or service that would meet your financial needs?” based on whether the member transacted on a checking account or a savings account.
Another example would be generating a member effort score for credit card acquisition versus the member effort score for vehicle loan acquisition in a consumer lending experience survey.
Member Demographics
MemberView includes four demographics filters:
- Member Age
- Member Gender
- Member Household Income
- Member Zip Code
Member age and zip code are typically populated when your credit union sends them with member data in the email invitation file. Age can be automatically populated based on the member’s date of birth. Alternately, your credit union can ask members to supply their age and zip code in a survey question.
Most credit unions do not have household income or gender in the member data file, but your credit union can ask these questions in the surveys. MemberView can identify gender by voice recognition for live, outbound call surveys.
Member Relationship
MemberView includes several member relationship filters:
- Member Accounts Per Household
- Primary Financial Institution (PFI)
- Length of Membership
- Deposit Balance Category
- Loan Balance Category
- Credit Score Category
- Profitability Rating
Accounts per member household can be populated if your credit union appends MCIF data to your core processor member records.
Many credit union populate the PFI filter by determining whether or not the member has a checking account with the credit union and sending that information in the member data file. It is generally accepted that consumers consider the financial institution where they have their checking account to be their PFI although some contend that the place where they maintain their first mortgage is their PFI. Another tactic for populating the filter is simply to ask, in your surveys, whether the member considers your credit union to be their PFI.
Length of membership can easily be populated when your credit union sends the membership origination date along with its member data files.
KPI Pivots: Promoter Score and Member Effort Score
Most MemberView users consider the Promoter Score and the Member Effort Score to be Key Performance Indicators (KPIs) of the member experience. MemberView allows you to pivot on both scores.
One good way to pivot on the Promoter Score is to filter your results three ways:
- Scores for all questions for Promoters. Generate this score by choosing “9” and “10” (considered to be Promoter scores) in the Promoter Score filter.
- Scores for all questions for Passives. Generate this score by choosing “7” and “8” (considered to be Passive scores) in the Promoter Score filter.
- Scores for all questions for Detractors. Generate this score by choosing “0,” “1,” “2,” “3,” “4,” “5,” and “6” (considered to be Detractor scores) in the Promoter Score filter.
Likewise you can filter on the Member Effort Score. A rule of thumb for the Member Effort Score is that anyone giving your credit union a “6” or a “7” for the experience considered the experience to be easy. Anyone giving your credit union a score of “1,” “2,” “3,” “4,” or “5” for an experience considered the experience to be fairly or very difficult.
Beyond Built-in Filters: Custom Variables
If you’d like to pivot on your MemberView results using other variables, you can supply those variables in your member data files. They’ll appear as separate columns in the “Surveys and Comments” report in MemberView which you can download as a spreadsheet. You can then use your spreadsheet to create a pivot.
If you’d like assistance in creating your own custom pivot table, please contact [email protected]. We’re happy to help!
