Everything You Need to Know About Nonprofit Data Analytics

Data is at the heart of every successful nonprofit’s decision-making processes. In today's mission-driven landscape, the ability to effectively measure, manage, and communicate social impact is not just an advantage—it's a necessity.

Nonprofit data analytics moves organizations beyond good intentions toward demonstrable, evidence-based results. This guide covers everything you need to know about the analytics process, including:

• Nonprofit Data Analytics FAQs
• How to Analyze Your Nonprofit’s Data
• Essential Metrics to Track for Nonprofit Data Analytics

Nonprofit Data Analytics FAQs

What Is Nonprofit Data Analytics?

Nonprofit data analytics is the systematic process of collecting, managing, and analyzing a mission-driven organization’s data. Analytics allows nonprofits to measure their mission effectiveness and organizational efficiency, highlighting strengths and opportunities for improvement. The end goal is to make data-driven decisions that support your nonprofit’s mission and the communities it serves. 

Why Is Data Analytics Important for Nonprofits?

The insights your nonprofit can derive from data analytics offer several proven benefits:

• Informed donor engagement: Analyzing donor data helps nonprofit teams understand their supporters’ unique giving motivations and preferences. This insight fuels personalized outreach, which has been proven to boost donor response rates by as much as 40%. 
• Increased impact transparency: Organizations raise 53% more from donors on average when they share impact data. Nonprofit data analytics helps organizations measure their impact and determine which data is most useful for demonstrating their overall effectiveness. 
• Stronger collaboration with funders: Impact transparency helps grantmakers allocate resources in the ways that align most with their values and make the greatest possible difference. In fact, 43% of foundation leaders report that information about impact or outcomes is the most useful type of information grantees provide. 
• Enhanced program efficiency: Data has been proven to directly improve efficiency, with nonprofits reporting a 25% increase in program effectiveness when they use analytics for decision-making. 

If you’re still not convinced, look at your nonprofit’s own processes. Do statistics and research findings offer valuable insights into your community’s needs? Are your outreach campaigns more effective when you segment donors and personalize your messages? 

What Are the Major Types of Data Analytics?

Data analytics in any industry encompasses four specific types of analytics that apply to different data points and offer different results as follows:

• Descriptive analytics focuses on historical data covering a specific time period and surfaces patterns and trends from past performance.
• Predictive analytics looks toward the future, anticipating potential outcomes using patterns from historical data.
• Prescriptive analytics helps organizations plan their next steps by evaluating the risks and benefits of certain actions.
• Diagnostic analytics identifies contributing factors and connects them to specific events to address why something happened.

For example, let’s say your nonprofit wants to assess the effectiveness of its youth literacy program. Here are some ways each category of analytics can contribute to this goal:

• Descriptive analytics helps you measure success with insights such as the number of students who completed the program or their average reading level before and after.
• Predictive analytics forecasts the likelihood of future participants reaching a certain reading proficiency based on their initial assessments and the program's historical success rates.
• Prescriptive analytics recommends strategies to improve the program, such as adjusting resource allocation based on an analysis of what approach to spending has been most effective in the past.
• Diagnostic analytics helps your nonprofit understand why some students made significant progress while others struggled by examining factors like attendance, individual learning styles, or external challenges they faced.

Your decision-making will be best informed if you use a combination of all four types of analytics rather than just focusing on one. 

How to Analyze Your Nonprofit’s Data

It’s clear that nonprofit data analytics is a valuable process for understanding and applying your data. But how do you get started?

At UpMetrics, we have a methodology for impact measurement and management, which also applies to the overarching data analytics process. We call it the DeCAL methodology, and it includes the following steps:

• Define: Clarify your objectives and identify the metrics you want to track. In impact measurement, this step lays the groundwork for your Impact Framework.
• Collect: Gather data and clean and format it for analysis.
• Analyze: Examine the data for patterns and trends that reflect your organization’s impact.
• Leverage: Put your insights into action by creating an impact report and planning out operational improvements.

Let’s look at how these steps apply to the nonprofit data analytics process.

Choose Your Metrics

Analytics starts with deciding what data you should focus on. We’ll go over the metrics that most nonprofits track later, but no two organizations need to analyze the exact same data or conduct analytics in the same way.

At a base level, there are two primary types of data your nonprofit should collect for analytics:

• Quantitative data refers to metrics with a numerical value, such as donor retention rates or email click-through rates.
• Qualitative data refers to descriptive information that details characteristics, experiences, and other intangible attributes. 

While the word “metric” tends to make most people think of numerical figures, qualitative data is just as important. Balancing both is critical to gain a well-rounded view of your nonprofit’s effectiveness. 

Collect and Manage Data

Establish a process for organizing existing data, gathering new information, and maintaining a clean database along the way. This process, also called data hygiene, involves:

• Standardizing data entry so that all information is input consistently
• Correcting any errors in your data
• Removing duplicate records
• Updating outdated information
• Filling in missing information through data enrichment

Having the right technology is paramount to collecting and managing data for analytics. The analytics process covers a lot of information, so using basic spreadsheets or disconnected systems will leave data disorganized.

To make sure your technology supports organized, useful data analytics, try these tips to assess your existing solutions and consider whether new ones would be valuable:

• For existing technology, integrate any systems generating data for your nonprofit. This could include your constituent relationship management (CRM) system, marketing and fundraising tools, and other platforms that gather or track data.
• For new technology, determine whether your existing solutions focus on the data you need. For example, your bookkeeping software houses all of the financial transactions you have to report on annually for compliance purposes, but it can’t measure your organization’s social impact.

Visualize Key Metrics and Compare Benchmarks

With an arsenal of data and the right technology at your disposal, you can start looking for patterns in your data and comparing them to industry-wide benchmarks. Apply the different types of analytics (descriptive, predictive, prescriptive, and diagnostic) to your data and see what insights surface.

Impact reporting tools are especially useful at this stage because they automate many of the analytics workflows and allow you to turn static numbers into visual dashboards for easier analysis.

Act on Your Insights

It’s tempting to think that analytics ends once you’ve gathered a list of insights from your metrics. However, acting on the insights you derive from data analytics is arguably the most important step of the process.

Data analytics surfaces both what’s working and what isn’t, allowing your team to capitalize on its successes and plan improvement initiatives.

Essential Metrics to Track for Nonprofit Data Analytics

Data is the raw, unorganized information your nonprofit collects in the analytics process. Within this data, you can look for specific metrics, which are calculated values derived from the data to help you derive insights from the information. 

If you’ve got a full database and are wondering what you should be looking for in it, here is a list of commonly-tracked metrics that can serve as a helpful starting point:

Fundraising and Donor Data

Data surrounding your fundraising activities and donor base vary greatly depending on the campaigns you host and types of support donors give. Here are a few of the most commonly tracked metrics for understanding fundraising effectiveness:

Donor Retention Rate

Definition: Donor retention rate refers to the percentage of donors who give period-after-period. This metric helps nonprofits identify donors with a strong sense of loyalty to the organization and understand the effectiveness of their stewardship efforts.

How to measure it: Calculate donor retention rate with the following formula:

• (Number of repeat donors in a period / Number of total donors in the previous period) x 100

According to the Fundraising Effectiveness Project, average year-over-year donor retention rates hover around 45%. However, industry leaders often cite 50-70% as a strong retention rate to aim for.

Donor Lifetime Value (LTV)

Definition: Donor lifetime value (LTV) is the total net revenue you expect a donor to contribute over the course of their relationship with your nonprofit. This metric helps nonprofits understand the long-term value of donors and informs their fundraising strategies.

How to measure it: Calculate donor LTV using the following formula:

• Average donor lifespan x Average donation x Average donor frequency

Donor LTV varies significantly depending on your organization’s size and mission, but it’s best understood in the context of your cost per dollar raised. A higher LTV and lower cost per dollar raised indicate you’re acquiring donors at a low cost and receiving significant support in return.

Average Gift Size

Definition: Average gift size, or amount, is the dollar amount that donors typically contribute to your organization. This metric provides insight into the general giving capacity and patterns of your donor base.

How to measure it: Calculate your donors’ average gift size with the following formula:

• Total revenue from donations / Total number of donations

The average gift amount also varies greatly. Statistics show that the average one-time gift is $121, while the average monthly donation is $25. You might calculate separate averages for donors at different giving levels (small, mid-level, major, and planned) or for specific campaigns to dive deeper into this metric.

Affinity Indicators

Definition: Affinity indicators are the characteristics or qualities that signal a donor’s connection to your cause. For example, an individual who has adopted three dogs is more likely to donate to your animal shelter than someone with no pets, because the first person has demonstrated indirect interest in your cause.

These markers help nonprofits identify potential donors and tailor outreach for greater relevance.

How to measure it: Look for indicators such as demographic data, hobbies and interests, and other information to identify affinity markers. While there isn’t a universal benchmark for affinity, your organization will know its unique supporter base best.

Donor Survey Feedback

Definition: Donor survey feedback includes all forms of responses you receive from questionnaires, polls, and other types of donor inquiries. This metric provides direct insights into donor motivations, satisfaction, and preferences.

How to measure it: Gather a mix of qualitative and quantitative data through direct donor communications. For example, you might ask donors to rate their giving experience on a scale of 1 to 5 or request open-ended comments describing their level of satisfaction. 

Operational Metrics

Operational metrics cover data related to your organization’s day-to-day workflows. Here are the commonly tracked metrics in this category:

Revenue Reliability

Definition: Revenue reliability measures how heavily you rely on certain revenue streams, such as monthly gifts or an online store. This metric is essential for financial planning, budgeting, and ensuring long-term sustainability.

How to measure it: Use the following formula to gauge revenue reliability:

• Total revenue from a specific source / Total revenue

While there isn’t a widely accepted industry standard for revenue reliability, most financial experts agree that revenue diversification is critical to nonprofit sustainability. A high result from the above formula may indicate that your nonprofit relies too heavily on one revenue stream.

Cost Per Dollar Raised

Definition: Cost per dollar raised is the total expense your nonprofit incurs to raise one dollar of revenue. This metric is a key indicator of fundraising efficiency and financial health.

How to measure it: Calculate the cost your nonprofit spends for each dollar it raises using the following formula:

• Total fundraising expenses / Total funds raised

According to RallyUp, the target cost per dollar raised varies by fundraising method. However, efficient organizations typically spend less than $0.10 per $1 raised. 

Program Expense Ratio

Definition: Program expense ratio equals the percentage of your nonprofit’s total expenses that go toward programs and services. This metric measures the proportion of an organization's spending that directly supports its mission.

How to measure it: Calculate your program expense ratio using the following formula:

• (Total program expenses / Total organizational expenses) x 100

It’s generally recommended that nonprofits spend 65% of their total expenses on program activities, although your organization’s exact breakdown will depend on how long it has been in existence and its overall financial stability.

Staff Retention

Definition: Staff retention is the percentage of employees who continue working for your nonprofit over a certain period of time. High staff retention indicates a positive work environment, reduced recruitment costs, and continuity in operations.

How to measure it: Your nonprofit can calculate staff retention with the following formula:

• (Number of employees who continued employment over a certain period of time / Number of employees at the start of the period) x 100

Research has historically shown that nonprofits experience higher employee turnover rates than for-profit entities, making retention a unique challenge for mission-driven organizations. On average, the annual nonprofit employee turnover rate is 19%, meaning retention hovers around 81%. 

Volunteer Engagement

Definition: Volunteer engagement refers to the strength of volunteers’ relationships with your organization. This metric is crucial for understanding how volunteer support impacts an organization’s ability to achieve its mission.

How to measure it: Volunteer engagement encompasses a range of quantitative and qualitative data, such as shift attendance rates and satisfaction with the volunteer experience. 

Marketing Metrics

Marketing metrics indicate whether your outreach efforts are reaching the right people and resonating with your audience. Here are a few examples of commonly tracked marketing metrics:

Marketing Return on Investment (ROI)

Definition: Marketing return on investment (ROI) measures the revenue generated from a specific campaign, after taking costs into consideration. This metric helps nonprofits assess the profitability of their marketing efforts.

How to measure it: Use the following formula to calculate marketing ROI:

• (Revenue from campaign - Cost of campaign) / Cost of campaign) x 100

What’s considered a “good” marketing ROI varies greatly depending on the campaign you’re hosting. At a base level, your calculation should be positive, indicating that you actually profited from the marketing campaign. 

Conversion Rates

Definition: Conversion rate equals the percentage of users who take a desired action after interacting with your content. This metric indicates the effectiveness of your calls to action and provides insight into your audience’s responsiveness.

How to measure it: Conversion rate is typically measured according to a specific platform. It’s commonly referenced in the context of your website and specifically, your donation page. The formula is:

• (Total donations / Total page views) x 100

According to the M + R Benchmarks report, the average donation page conversion rate is 11% for desktop users and 8% for mobile. 

Average Amount Raised Per Campaign

Definition: Average amount raised per campaign is exactly what it sounds like—the amount of revenue generated from a specific marketing channel, like email, direct mail, or social media. This metric provides a direct measure of the financial success of individual campaigns.

How to measure it: Simply calculate the total revenue generated as a direct result of a specific marketing campaign. 

Engagement Rates

Definition: Engagement rates vary across different marketing platforms, but generally indicate how much your communications resonate with your target audience. This metric indicates audience interest and interaction with content.

Here are a few specific measurements to consider:

• Email click-through rate (CTR): The percentage of recipients who click on a link in an email.
• Email unsubscribe rate: The percentage of recipients who opt out of email communications.
• Average website session duration: The average amount of time users spend on a website during a single visit.

Target engagement rates vary depending on the channel you’re using, but the best way to gauge whether you’re moving in the right direction is by tracking engagement trends over time. For example, is engagement increasing or decreasing on a specific platform?

Marketing Material Responses

Definition: Marketing material responses include any type of interaction you share with supporters as a result of your marketing messages. This metric measures the direct impact and effectiveness of marketing collateral.

How to measure it: Track event RSVPs, social media comments, and other donor responses to your marketing content.

Impact Data

Impact data is the measurable information surrounding your nonprofit’s effectiveness in achieving its mission and goals. Again, this is a category of data that varies greatly depending on your nonprofit’s mission and activities. Here are just a few examples of metrics that fall into this category:

Program Reach or Volume

Definition: Program reach or volume refers to the number of beneficiaries served through your nonprofit’s activities. This metric is a fundamental measure of an organization's scale and direct impact.

How to measure it: Calculate the total number of individuals or groups who participated in or received services through your program during a specific period.

Service Utilization Rate

Definition: Service utilization rate is the percentage of your program’s capacity that was reached in a certain period. This metric helps nonprofits assess efficiency, resource allocation, and unmet demand for services.

How to measure it: Use the following formula to calculate your service utilization rate: 

• (Number of participants served / Maximum number of participants the program is designed to accommodate in a given period) x 100.

Beneficiary Satisfaction

Definition: Beneficiary satisfaction is the level of happiness your program participants feel toward the services rendered. This metric directly reflects the quality and effectiveness of programs from the perspective of those served.

How to measure it: Collect qualitative and quantitative feedback through post-program surveys, interviews, and feedback forms.

Supporter Satisfaction

Definition: Similar to beneficiary satisfaction, supporter satisfaction refers to the happiness of your nonprofit’s supporters with their giving experience and your organization’s work. This metric is crucial for fostering long-term relationships and encouraging continued support.

How to measure it: Use structured surveys, conversations, and polling to assess donor and volunteer satisfaction with various aspects of their experience. For example, you might ask about their opinion of your nonprofit’s communication or level of transparency.

Beneficiary Outcomes

Definition: Beneficiary outcomes are the actual, long-term changes in the lives of those you serve. This metric is the ultimate measure of an organization's impact and mission achievement.

How to measure it: Set and track Key Impact Indicators (KIIs) related to the desired change after beneficiaries have completed the program.

Final Thoughts on Nonprofit Data Analytics

The goal of nonprofit data analytics is not simply to collect numbers, but rather to gain actionable insights that maximize your organization’s social or environmental impact. Adopting a systematic approach to data analytics enables nonprofits to identify what works and improve where needed.

Ultimately, leveraging data allows you to make data-driven decisions, streamline reporting, and drive accelerated social and environmental change. If you want to learn more about measuring your nonprofit’s performance and improving your impact, check out the following resources:

• Social Return on Investment (SROI): Measure the Intangible
• How to Build a Data-Driven Culture in Your Organization
• The Ultimate Beginner's Guide to Nonprofit Storytelling