The fundraising landscape is constantly evolving with new and proven digital fundraising strategies that deliver great results. For corporations and nonprofits alike, data is king. Data science, analytics and machine learning are extremely powerful techniques that help cut costs and increase revenue. According to a 2020 McKinsey survey, privately held companies are increasing their revenue by developing and implementing Machine Learning (ML) strategies. Despite its benefits, ML largely remains in the private sector for now. Nonprofit organizations are yet to integrate the technology in their operations. However, this technology is not going anywhere; it is expected to grow by an annual rate of 44% through 2022. As your nonprofit gears up for a digital transformation, consider machine to learn how it can really help your organization grow.
What is Machine Learning?
“Machine learning” is a set of powerful computer algorithms with the ability to read, process and analyze large amounts of data. It’s a process that involves the use of computers to do the work previously done by humans.
Essentially, your computer learns and improves on its own without you giving instructions. As a result, you improve accuracy, performance and insights from the same data your already have. The algorithm here works by reading and making sense of patterns. It is called “machine learning” because the system is getting smarter with every new piece of information added to the algorithm. For instance, Alexa and Siri are fruits of machine learning. It is important to note, the benefits of ML are not limited to the tech world.
Machine Learning for Nonprofits
ML is expected to grow by an annual rate of 44% through 2022. As your nonprofit gears up for a digital transformation, consider machine learning and how it can really help your organization.
To begin with, your nonprofit must have a strong dataset and a problem that is solvable. If you don’t have a problem or question, your organization wouldn’t know which direction to take. You also need a robust database from which your ML model will derive useful information. Finding big donors from a pool of all your donors is an example.
To create an effective model – which is a combination of features and metrics, you need people with experience in data science. This may take some time but it sure is worth the wait.
#Personalized Digital Experience
The data analytics algorithm in ML helps a nonprofit organization in improving their prospect pool segmentation. It suggests the best suitable offer to present to a donor. Designing personalized messages out of a deep understanding of your audience helps you build stronger bonds. Conversations with site visitors in the form of chatbots are convenient but sometimes, there are questions that chatbots cannot answer. Natural language processing algorithms and machine learning come in handy at such times by creating smooth communications with both internal and external users.
#Boost the Fundraising Process
Machine learning helps you ask for the right donation amount and propose the right program to your supporters. Communication over social platforms is getting stronger by the day and the interests of your audience may keep changing. Developing an intense learning algorithm helps to extract useful insights on both your current and potential donors. This also helps your organization figure out the ways in which you can boost online donations.
#Handle Administrative Tasks & Business Needs
We all aim to increase revenues for our nonprofits. In addition to that, ML can be used for many administrative jobs. This is useful for smaller nonprofits with limited human resource. The hiring processes and performance can be managed with the use of machine learning. Financial records can be well tracked as well.
#Identify Resource Urgency
As a nonprofit organization it is extremely important to identify departments or constituents that need resources urgently. ML helps you effectively allocate time and resources according to your priority.
#Level Up on Your Communication
Communication is the key to perfecting the art of storytelling. And by analyzing your engagement metrics, machine learning helps you craft the right messages. The algorithms work in such a way that it informs your organization about open rates and send time, then makes recommendations based on the data. This input improves the results of your upcoming social media or email campaigns. In other words, its a much sophisticated donor management software.
Conclusion
Over the next five years, machine learning is expected to become more prevalent in the nonprofit and fundraising domain. It is not a fictional theory anymore but a reality that is creating good change. It reduces the time we spend on repetitive tasks and gives nonprofit professionals more time to focus on building relationships. Moreover, Machine learning doesn’t replace humans, rather, it’s a technology that enhances and simplifies work for them.
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