What's the difference between reporting and analysis? According to Salesforce, reporting is answering the question, "What is happening?" and analysis is answering the question, "Why is it happening?" (You can read more about it in this blog post. ) While this is a good distinction, I don't think most people are much concerned with this nuance. We all try to answer both of these questions when looking at a report. The natural next step, after figuring out what is happening, is to figure out why.
Take, for example, a Master File Audit - a report that illustrates the state of your fundraising performance. If the report shows that the number of donors is down 1%, but revenue is up 2%, your brain immediately begins trying to rationalize and answer why that is. We instinctively try to fit this into a narrative: "Industry acquisition is down and that's why my donors are down...... We focused on Mid-Level donors this year which is why we're showing a revenue increase...." Essentially, it's inherent in us to try to analyze what's happening while we read reports.
The Salesforce blog suggests that the analysis digs deeper. In the example above, if you think your Mid-Level focus is why your revenue went up, a true analysis (to start) would mean isolating those donors and looking at their giving this year compared to last. The bigger questions that I think we all need to ask is,
How do we use this data to inform our strategy? How do we go from reporting and analysis to data-driven?
Forbes published an interesting article, Five Steps To Build A Data-Driven Marketing And Communications Model, that describes their take on data-driven marketing. The article still focuses primarily on reporting and analytics, rather than connecting data to strategy, but the advice is good and I especially like tip #5 Report Meaningfully. However, the key to becoming data-driven was not included as a step, but rather a highlighted sentiment.
Driving marketing decisions from data should become a habit.
But how to make that a habit? Try by starting simple. When talking about strategy, track it to a number. For example, if you want to improve retention, tie the objective you hope to accomplish from a particular action to a number: If I spend $1 to thank a donor I will improve retention by 0.2%.
This may seem daunting, but the data is readily available. This is at the heart of what we do at DonorTrends. Every report, every analysis, and every action is tied to an objective. We call this our A.I. - Actionable Insight.
A great example of the free A.I. we offer nonprofit fundraisers is in our newly released Donor Contact Strategy Report, found in our growing Budget Solution Center resource. We'll calculate the optimal number of contacts for each segment of your donors, thus connecting your data to one of the most important strategies you employ: How often should I be in front of my donors?
What ways are you using data to guide your strategy?