How does Dataro compare to tools like Salesforce's Einstein?

Dataro has been developed specifically for not-for-profit fundraising and it requires minimal configuration to get started. In contrast, Salesforce Einstein, like the Salesforce CRM, is more of a platform for data, rather than a ready-to-go product. There is the potential, theoretically, for such modelling platforms to do almost anything, but you would need an implementation partner in order to implement any specific analytics or predictive models. 

Dataro state-of-the-art machine learning techniques to produce scores for donors across a number of fundraising campaigns: appeals, upgrades, churn, reactivation, conversion, etc. The propensity scores are updated weekly, so you always have the most up to date scores ready to go when you want to generate a campaign list, and models are constantly checked and refreshed.

On a more technical level, our analysis suggests generalist tools (i.e. not specific to NFPs) would not be capable of generating scores as accurate as those produced by our system. The algorithms commonly used in generalist libraries are not as performant as the ones Dataro uses. We also question the idea that an implementation partner could produce an as effective modelling system for a single charity client as we have developed over several years across 30 not-for-profits in Australia and New Zealand. 

In summary, Dataro is specifically built for, tested and is proven on NFP data sets and is much simpler to turn on and use.