The AI and machine learning buzz has reached a fever pitch, with product providers working hard to harness public fascination by incorporating ChatGPT (or ChatGPT-like) tools into everything from office productivity tools to donation page ask amounts to composing first drafts of donor emails and grant applications. It’s an exciting time in technology to determine how AI can help nonprofits maximize their impact by working smarter.
In 2018, ROI Solutions had its “aha” moment when it embarked on a journey to create MiLo Intelligence, its machine learning platform to develop innovative custom models that move the needle across the constituent lifecycle for nonprofit organizations. Fueled by the same spirit of innovation and intellectual curiosity that has driven our growth as a technology company, the team behind MiLo works directly with our clients to target desired outcomes for any marketing or fundraising challenge.
Guided by 20+ years of expertise in nonprofit enterprise data management and direct marketing fundraising, ROI Solutions is uniquely positioned to identify and ask MiLo questions based on the ideas and input of our clients. We feed the platform with a client’s rich, curated data and allow MiLo to do what it does best – identify models that impact audience results. MiLo can run thousands of data elements and interactions across hundreds of time-tested statistical models to determine predictive client-specific data that will perform best for the organization and maximize mailing and marketing spend.
The data leveraged goes far beyond the traditional cross-organization giving variables typically employed in a Coop model. MiLo considers transactional data, contact history, interactions, engagement points, and appended demographic data. Each model we deliver is client-specific because, for each client, the data that is found to be predictive is unique.
MiLo models have yielded very strong results across the multiple iterations we have built for clients. ROI Solutions continues to partner with additional organizations to identify new questions that can be explored by our MiLo models across the constituent lifecycle in a variety of channels.
As Susan Paine, Director of Analytics & Strategy at Human Rights Campaign, said, “We have used various predictive models over the years. We have been very impressed with the results from MiLo in both our recent and very deep-lapsed audiences. We have found those elusive needles in a haystack’’ among our deepest lapsed donors that we would likely have never touched using our regular segmentation and modeling efforts.”