Changelog

The Outcomes view now includes various features that were previously stored in the technical model report, such as lift table and features of importance. The full technical model report can still be accessed via the three dots in the upper right when viewing an outcome.

Managed connections to your favorite martech platforms like HubSpot, Iterable, and Facebook are now easier than ever to use. If they're part of your subscription, head to Connections and enter your credentials.

Ever wondered what Faraday “scores” really represent? Starting now, we’re returning true probability values. That means that someone with a propensity score of 0.8 for a given Outcome truly has an 80% probability of achieving that Outcome. The calibration process we added also has the benefit of improving accuracy, which you will see by default in all new models. Check out our probability scores blog post for more details.

Now, when creating a deployment in Faraday, you can use the filter advanced settings pulldown (after selecting your deployment format) to select specific payload elements (personas, outcomes, and cohorts) to include in the deployment. This change includes moving the percentile filtering from the limit pulldown into this new filter pulldown. Limit will now exclusively be used to limit a deployment's row count.

For more info on how this new feature functions, check out our Pipelines documentation.

In a dataset's data tab, you are now able to download previously-uploaded CSVs so that you can compare them to new data that you'd like to upload to ensure that their columns match. This is accomplished via the three dots (...) to the right of the row.

Enable test mode via the toggle that appears when clicking your organization's name in the upper left. Enabling test mode saves all of your current data in Faraday and brings you to an instance of your account exclusively populated by artifical data, where you can test various features in sandbox mode. Use the same toggle to return to your regular Faraday account.

Find documentation for help getting started, full guides for Faraday prediction recipes from end-to-end, as well as walkthroughs for every part of Faraday.

When creating a deployment, in the advanced settings step's structure tab, you can select from various ad platforms such as Facebook, LinkedIn, Google Ads, and Pinterest to have the deployment automatically format in a way that's appropriate for that destination.

Places enables API users to designate points of interest around which they can focus predictions, and our new lead scoring quickstart guide details how you can quickly begin scoring leads in real-time using the developer API.

When creating a pipeline deployment, you're now able to select human friendly deployments, which changes column headers to the names of the outcome or persona set in use. This also includes full customization of column header names, if desired. These changes should make it easier to tell, at-a-glance, what each column header represents.