Prospect Research: Understanding database management

publication date: Oct 10, 2017
author/source: Brian Dowling, Tamara Wojdylo and Shelly Steenhorst-Baker

The world has become more data-driven and we’re more reliant on data to assist with analysis, reporting and decision-making. Prospect researchers are in a unique position to help guide their organizations to use data more effectively. Here are a number of recommendations for you to consider as you enhance your expertise with data. .

Automate, Automate, Automate Good database management begins with the discipline of automation. If you find yourself running a query in your fundraising system, exporting the data to a spreadsheet and then having to manually manipulate the data further, you will appreciate how inefficient and error prone this can be - especially if you have to repeat the exercise with the same data sets. .

Here is a simple example of how automation can enhance workflow: many shops track the number of prospect research requests in order to measure the effectiveness of the research team and to let their manager know what they’ve been working on. If you’re using a spreadsheet, think: how can this be coded in your database so you can create a report?

• Attach codes (and date stamps) to the prospect's record showing when the research request was made and completed.

• Record another code in your database showing when the prospect was assigned to a fundraiser.

• Create a report to track all research requests, which were, and which were not, assigned. It may also be helpful to add a column for total giving.

A simple strategy like this saves you time, gives a fuller picture for you and your manager, and stores that information attached to the prospect’s record, so it’s clear to everyone who reviews that record, what work has already been done. It shows the results of your effort, and you can use the report to follow-up with fundraisers and assign prospects.

Effective automation occurs when policies plus process, plus people equals better data management. Automation saves you time, provides information at your fingertips, reinforces coding in your database, encourages employees to follow specific business processes and enhances the accuracy and value of the information you are capturing.

Manage your prospect research with metrics There’s an old adage that “if it doesn’t get measured, it won’t get done.” Prospect research professionals should have a clear understanding of the metrics required to manage research, prospect portfolios, and relationships with prospects and donors to help drive one’s activities. Here are a few things to keep in mind when making database storage and reporting decisions:

1. Who assigns research priorities and how are these determined? Do you use cumulative giving metrics? Are you able to be automatically notified when a constituent moves over a cumulative giving threshold?

2. Do you keep track of how many days your prospects should be in certain stages, such as cultivation, before an ask should be made? This helps fundraisers move towards an ask.

3. How large are the prospect portfolios assigned to individual fundraisers and how are they changing over time? If you code prospect assignments, you can advise on how to balance prospect portfolios between fundraisers so they each have portfolios they can actively manage.

4. Are you using metrics to measure individual fundraiser performance? These can include activity based on action/contact/meeting targets, proposals delivered to a prospect, and a data quality analysis so the fundraiser knows what data to collect when they are meeting prospects.

Metrics-driven organizations are more successful and prospect research is in a great position to use and report on them. Metrics also reinforce coding. For example, when measuring prospect visits, fundraisers are quick to notice if their visits are not showing up and will be the first ones to ensure their meetings are entered in the database. Be the best you can be at understanding key metrics that drive your organization’s performance.

Lead the charge for data standards and quality Data standards are particularly important for everyone in the database, and even more important for major prospects. We all have stories about the spousal relationship that was not recorded properly or about the wrong people who were invited to an event. Prospect researchers need to educate staff on the data integrity standards of the organization and prioritize which data elements should be collected and managed. Here are a few examples of data standards:

Biographical: First and last names, middle name preferred over middle initial as it gives you more detail for identifying constituents.

Addresses: Are you using Canada Post standards for addresses? Former address is a valuable piece of information and should be coded as "former" with an end date instead of deleting it outright. Past addresses are valuable when evaluating individual's real estate portfolio, and how it has changed over time.

Relationships: If known, do not skip a marital status, nor family members. These can be indicators of wealth and life changes. When a prospect's marital status changes, any former relationships are best not overwritten, instead, the relationship type should be changed to reflect a "former" status.

Every time a fundraiser visits a prospect there is an opportunity to find out more. If we are not getting this critical intelligence back into the database, it is a gap. Keep an eye out for shadow databases and other clusters of rogue data living outside the database.

This article is excerpted from the chapter on "Database Management: Bringing it all together for effective reporting" in Prospect Research in Canada: An Essential Guide for Researchers and Fundraisers, edited by Tracey Church and Liz Rejman.

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