SparkPoint: Linking service profiles with client progress
SparkPoint is an anti-poverty organization in the San Francisco Bay Area that helps low-income individuals and families reach financial stability. Clients work together with SparkPoint coaches to design a personalized path towards their financial goals. A central theme of this approach is the freedom to choose from a variety of services, including those that support access to financial planning, social assistance, and educational or employment opportunities.
Statistics for Social Good analyzed several years’ worth of client data to help SparkPoint gain a better understanding of client characteristics and outcomes at each of the nine SparkPoint drop-in centers in the Bay Area. Our site-level analysis identified notable differences in the demographics of clients and the distribution of services provided across centers. SparkPoint was particularly interested in studying the effect of a “magic bundle”combining employment and financial budgeting services. To this end, for each of the four SparkPoint outcomes of interest — debt-to-income ratio, credit score, income, and savings — we used a combination of data visualization and regression modeling to analyze the improvement over baseline that was achieved by clients receiving the bundled service, compared to those receiving other services.
