Statistics are Like Bikinis

by Ashley Perry

“Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital.” 

--Aaron Levenstein, business professor and economist

Profitable businesses in almost every industry have long relied on data analytics to make strategic decisions about their products, operations, customers and how to best utilize their resources. 90% of nonprofit organizations collect data, but only half try to leverage it.  Why?

“Without big data analytics, companies are blind and deaf, wandering out on the Web like deer on a freeway.”

-- Geoffrey Moore, American management consultant and author

Nonprofit business organizations collect an array of data from their donors, volunteers, and beneficiaries- addresses, emails, donation dates and amounts, things they clicked on or not, etc. This data is an organization's most valuable asset. Most nonprofits don’t have the staff or the skills required to understand how to take that information and turn it into something meaningful. 

This process- called Data Analytics- is the is the #1 most promising IT opportunity, growing as a structural consequence of the digital transformation. Analysts use data-driven insights to help nonprofits maximize efficiency and the effectiveness of their programs and services, as well as target approaches for goals and optimize marketing campaigns. 

The 3 types of data analytics

  • Descriptive. What has happened over a specific period of time? Discover changes that have occurred and compare specific time periods against each other- neutral analysis based on facts. 
  • Diagnostic. Why has this happened? Drawing connections among variables to help answer questions like, “Did our social outreach affect end of year giving?” or “are our programs evolving with current social trends?”
  • Predictive. How do past trends anticipate future outcomes? What is the best course of action to take? Based on trend predictions, organizations may allocate resources differently, adjust the budget, or create new targeted marketing and fundraising strategies. Once you’ve analyzed your past results, it is easier to predict what will drive success in the future, and understand potential risks and benefits.

“We are surrounded by data, but starved for insights.”

- Jay Baer, marketing and customer experience expert

76% of nonprofit businesses who used advanced analytics reported performing their objectives with much greater efficiency. 

Following are a few of the many areas that can be enhanced with analytics:

  • Marketing and Fundraising. Donor relationships are among the most important factors in your outreach efforts. Analytics can identify new prospects as well as  provide ways to improve your current contact and campaign strategies. Understanding your target audience allows you to categorize and send highly relevant messaging, taking relationships to the next level. 
  • Accountability and Reporting. Long term-success requires transparency between organizations and their donors. Accurate reporting of financial statistics from year to year is not only required, but it is only one measure of how your organization is doing.  Using statistics to identify the value that your programs and services bring to the community gives donors assurance and makes them feel important by recognizing that their dollars are making a difference. 
  • Budgeting and Forecasting. Analyzing past trends can help identify areas of strength and weaknesses. If your year end donations are down, was it because of some random event?  If not, what can you do to reverse the trend? When are the best months for major fundraising efforts based on past performance? 

The shortest possible summation of all this? 

Data analytics will help you make sure you’re putting your time, money, and effort into the right channels. 

“Data analytics is the future, and the future is NOW!

Every mouse click, keyboard button press, swipe or tap is used to shape business decisions.

Everything is about data these days.

Data is information, and information is power.”

-- Radi, data analyst