Data Driven Fundraising
How to use data to guide strategy
There is a delicate balance between analysis paralysis & valuable insight. The main reason you want to look at your data is to answer very important questions:
- Are you getting the most out of your investments?
- Where can you be more efficient?
- Where are the hidden opportunities?
The benefits of data analysis
There are many benefits to analyzing your data. Especially if you do it before building your annual fundraising plan. The key to analysis is to keep it simple and effective. Here are a few compelling reasons why you should look deeper into your data:
- Look at patterns to solve problems
- Create clarity and understanding
- Reach consensus and validate knowledge
- Ask meaningful questions
- Discover opportunities & efficiencies
- Prioritize and focus on best returns
- Continues learning & growth
Data Comes First In Data Driven Fundraising....
Developing a fundraising plan prior to conducting a data audit is risky as it involves a lot of assumptions without the ability to set the right benchmarks and fundraising goals.
The truth is that a data audit doesn’t need to be too extensive. However a data audit can lead to pin-pointed accuracy about the deficiencies and the opportunities that exist for your organization.
It means you have the necessary information to guide your investments towards the best opportunities.
Data helps to validate assumptions and also inspire curiosity and continuous learning. Fundraising organizations that start with data perform with greater confidence and focus because they let the data lead them to solutions.
The steps to building a solid data driven fundraising plan
If you truly want to be data-driven, you want to implement the following steps into your work flow:
Step 1: Clean the data
Your data might have some irregularities that will cause you headaches when you are looking for answers. The first of which is duplicates, deceased donors, and invalid or wrong addresses. An National Change of Address, Address Correction and Deceased lookup with Canada Post is a good place to start. Dedups and data validation (i.e. correcting names, getting rid of invalid characters...) will enable you to do that part very quickly and much cheaper.
Step 2: The Analysis
A thorough analysis means you need to know what you are looking for. When conducting a general analysis these are some of the questions you need to answer:
- 1What is the make up of our donor base?
- 2What programs have led to our growth?
- 3What does our donor pyramid look like?
- 4How many active donors, lapsed or former donors?
- 5What is our retention/attrition rate by program?
- 6What is our donor/revenue growth year over year?
The above is the basic stuff that will give you an understanding of your organization's growth path. Knowing this will illuminate your path for the future.
Step 3: Conduct a SWOT
Now that you have data on your side, you are ready to summarize your findings by putting your findings into a neat SWOT report. Here you need anecdotal and contextual insights, so you may need to go beyond the data itself to talk to the fundraising team who are intimately aware of the issues but not able to articulate or make a case without the data.
Keep your SWOT short. Don't overwhelm the audience with every little fact, but really try to find the key elements that shape the organization's opportunities and strengths.
Step 4: Write the plan
And now the final part - writing the plan.
Contrary to traditional belief, I think strategic plans should be short in length. They should also be data-centric with a lot of specific growth targets for each program.
It is not good enough to say, we are going to increase revenue by 25% - you have to know specifically which donor segments are going to give you that boost and you have to have a strategy in place to do that work.
If you are interested in learning more about best practice in developing data-driven-fundraising plans - then we should connect!
Get on a 30 minute call with me and together, we'll figure out the first steps for you to become ridiculously productive.
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