You will have noticed that some Dataro models come with two new fields in your CRM: the 'Score' field and the 'Rank' field. You might be wondering why.

**Scores**

Dataro Scores are a number on a scale from 0.0-1.0, and approximate the probability of a person taking an action. The higher the score, the higher the probability of an individual taking the associated action. So if we were trying to predict direct mail giving, a person with a score of 0.76 would have roughly a 76 percent chance of giving in the upcoming DM appeal, according to our modelling.

Scores are available for the following modules:

- Appeals module
- Convert to Regular Giving module
- Regular Giving module

**Ranks**

Ranks simply order your donors from most to least likely to take a particular action. So a person with Rank 1 is the most likely and rank 10,000 is the 10,000th most likely, etc.

Ranks are available for all modules.

**Why have ranks & scores?**

Ranks and Scores are the output of different models, as explained below. They are different ways of looking at the same information.

It is possible to construct a campaign using either ranks or scores, however, we generally advise newer users to use the ranks and our suggested campaign sizes (on the homepage of the app) to build their campaigns, simply because it is easier. Ranks allow you to easily and quickly build campaigns to your desired size by targeting the top donors.

The scores are useful for calculating expected values on a per-donor-basis and can therefore be used to accurately calculate ROI curves and determine who should be included in a campaign. However, this is a significantly more complex method and we only advise this for more advanced users.

Some models like major giving and gift-in-will predictions only have ranks and no scores. This is simply because these are rarer events and there isn’t enough data at any organisation to produce actionable probability scores.