To easily analyze the performance of your funnels on your product goals, this release adds a new model hub operation called funnel_conversion. With this new operation, you can get an easy-to-digest overview that shows all the relevant metrics in one go, which you can optionally filter to any area of your product, timeframe, marketing campaign, etcetera.

For any funnel in your product (e.g. signup, purchase, requesting a quote, etc.), the new funnel_conversion operation calculates the following for each step in the funnel:

• location: The location considered as a step, e.g. a feature or root location;
• n_users: The number of users who started the funnel;
• n_users_completed_step: The number of users who completed the step (defined as whether the user went to any other step in the funnel);
• step_conversion_rate: The conversion rate to completing the step;
• full_conversion_rate: The conversion rate to completing the step, looking at all users who started the funnel (= the ‘full’ conversion rate); and
• dropoff_share: The percentage of users in the entire funnel, who dropped off in that step.

The only prerequisite is to provide a DataFrame with just the locations that are in the funnel, such as the main pages or clicks on buttons. This also allows you to filter it to - for example - any area of your product, a certain timeframe, specific marketing campaigns, or any other segmentation.

An example

Take a purchase funnel that can also lead to additional questions and a way to get in touch for more information, as illustrated below:

The example purchase funnel

You can run the funnel_conversion operation for this funnel directly on your data store, using the DataFrame that contains the funnel, and an optional location_stack parameter that defines where to find the funnel steps (which can be either the column name, or any slice of a SeriesLocationStack):

Results for the funnel_conversion operation

How to get it

To work with Objectiv, install the modelhub/Bach packages from PyPI:

pip install objectiv-modelhub

Or upgrade if you’ve already installed it:

pip install --upgrade objectiv-modelhub

To try Objectiv out in a lightweight setup, see how to run the Docker-based demo.

info

Office Hours

If you have any questions about this release or anything else, or if you just want to say 'Hi!' to team Objectiv, we have Office Hours every Thursday at 4pm CET, 10am EST that you can freely dial in to. If you're in a timezone that doesn’t fit well, just ping us on Slack and we'll send over an invite for a better moment.

Join the Office Hours