Case Study: Data Science Analysis of Donations and Sponsorships

Women for Women, International

About Women for Women, International

Women for Women International supports the most marginalized women in countries affected by conflict and war. Our programs enable them to earn and save money, improve health and well-being, influence decisions in their home and community, and connect to networks for support. By utilizing skills, knowledge, and resources, women are able to create sustainable change for themselves, their family, and community.

The Challenge

As Women for Women continued to grow in size through their sponsorship and donation vehicles, they began to take a more strategic approach to fundraising. This shift required that the organization take an analytical look at who was contributing to their cause. This presented a number of challenges and opportunities, including:

  • Understand the demographic make-up of their past and current contributors.
  • Develop a broader view of the donor market.
  • Develop an understanding of key indicators which predict, to a high degree of confidence, if a donor is likely to remain a donor or if a donor is likely to discontinue their donation. These are two different modeling questions.
  • Use data analysis to help drive fundraising efforts and set donation targets.
  • Develop feedback processes to analyze future results against model expectations.

The Solution

Kickstep worked with Women for Women to combine their internal donation information with several 3rd party sources of information including census data, wealth data and national demographic data.

  • ML and Data Science practices were employed to help identify donation trends which might provide insight into future fundraising strategies.
  • Use insights gained from data analysis to develop business cases associated with new giving and retention strategies.
  • Monitor actual outcomes to expected outcomes in order to update business case models and working hypotheses for aquiring and retaining donors.

The Benefits

Benefit 1 - Identified donation demographic cluster outliers which provided insight into using wealth information for donation requests.

Benefit 2 - Developed a donation market penetration map to better focus outreach campaigns. This allowed W4W to look at the country as a whole and evaluate who their best donors are, where that market segment is concentrated and where that have little to no penetration.

Benefit 3 - Provided a mechanism to evaluate expected outcomes to actual results in order to adjust fundraising tactics more proactively.

About Kickstep Technologies, Inc and Amazon Web Services

Kickstep Technologies is a leading technology firm providing cloud consulting, software development, data analytics and machine learning services. We use our experience to ensure clients have the best technical solutions to solve their business challenges and deliver value for their organization. We are fully committed to the success of our clients and commit to always putting their needs and interests before our own.