When someone submits their email address on the ONE Campaign website, they receive a welcome email with a friendly message and a simple question: ”Do you think we’ll see the end of extreme poverty in our lifetime?” You’re also presented with three run-of-the-mill options. Clicking on any of the three takes you to a different form where you’re asked to take a 2-minute survey so the organization can understand your interests and motivations.
This is data collection at its simplest and most natural.
Instead of making do with the average welcome message, the campaign utilized the initial interest a supporter shows in submitting an email address to learn more about the individual via a low barrier ask: answering a simple question. A heftier initial ask, like donating or pledging, risks putting the supporter off before the nonprofit has had a chance to earn their trust. The information can then be used to segment the supporter into a communication stream based on their interests. A person receiving communication more in tune with their interests is more likely to remain an active supporter of the cause.
The purpose of the above data collection effort was to personalize future communication. The example offers us two good lessons. 1) To start your data collection through low barrier asks and 2) To commence your data collection efforts with a question: why did you need to collect data in the first place?
Start by identifying your overarching goals for supporters and then breaking it up into sub-goals that are achievable through data. For example, improving your donor retention can be an overarching goal while personalizing your supporter engagement can be the subgoal. Personalized communication involves collecting supporter data such as name, home address, interests, history of engagement etc.
The type of data you collect depends on your organizational needs. Some of the common datasets you should be collecting are supporter interests, personal details, how they want to be communicated, event attendance, volunteering history, social media engagement, website visits and more.
Before commencing your data collection there are a few best practices that’ll let you make the best of your efforts.
1. Connect your data sources
Often times your data exists in silos of its own without communicating with each other. Social media data, email data and various other data come in separately, and decisions are made without considering how each communication strategy can affect the other. Using a primary database alleviates most of the issues that come with disconnected data sources. Make sure you use a CRM solution that comes with robust integrations. That way, you avoid multiple points of data entry by having data flow seamlessly from one tool to another.
2. Treat every interaction as a data collection opportunity
Website signup forms, events, webinars and door to door canvases are some obvious sources of supporter data. Some not so obvious places are your emails, text messages and phone calls. Treat every touchpoint with the supporter as an opportunity to learn more about them. Go for outreach tools that incorporate data collection into their feature set.
3. Segment your data
Your supporters are not all cut from the same cloth. Your data collection tools should facilitate the building of segmented lists. It should be easy to filter supporters based on datasets to create targeted lists.
4. Add to and update your data
Data can grow stale pretty fast. Make sure your staff has the ability to update datasets on every time they communicate with a supporter.
5. Start small
People who work in the nonprofit sector are more attuned to individuals than numbers. Avoid overwhelming them with statistics and start off small. Scale up your efforts once the returns on a certain strategy become evident.
As a nonprofit, supporters tend to be more open about sharing their data with you. But give your supporters low barrier asks to start with and depending on their responses increase the strength of your ask. If you present a strong ask outright, supporters might feel threatened about sharing their information.
