Use the predict last session date and predict last purchase date fields to identify leads who have visited your site but not yet bought anything.

Combine them with predict last session time spent and predict last session categories to gauge their level of engagement and the products they are interested in, and target them with incentives accordingly.

Use the predict last session categories, predict last abandoned categories and predict last purchase categories fields to segment contacts you know to be interested in these products and target them with stock-clearance and back-in-stock campaigns, as well as cross- and up-sell campaigns.

How many of your shopping carts are abandoned? Use the predict last abandoned date and predict last abandoned categories fields to trigger timely reminders to customers of what they left behind.

Combine it with predict last abandoned total price to offer different incentives based on total cart value. In this way you can recover up to 20% of your abandoned purchases!

If you don’t want to keep sending recovery campaigns for items that have been left in the cart for a long time, check if the predict last abandoned products field has changed or not.

The fields predict last session date and predict last purchase date give you a good indication of when customers are beginning to defect. Combine them with predict last purchase categories to offer targeted incentives.

See our example on how to use the web behavior fields to create a great lookalike audience.

You can also use these fields to personalize sections of batch email campaigns with dynamic content that will increase click-through-rates and conversions. For example:

• Use the predict last session/abandoned/purchase categories fields to select the right content based on their last preference.
• Use the predict last abandoned session/cart/purchase fields to segment your audience according to their level of engagement and treat them accordingly.

Targeted lists can be generated based on the data collected through our JavaScript API and subsequently exported for use in other marketing activities. For example:

• A high value for predict last session time spent with no corresponding predict last purchase date may indicate problems with your shopping experience.
• A high predict last purchase total price may merit one-to-one interaction from your Customer Services, such as invitation to a loyalty scheme.
• You can also match purchase activity with email responses and consider targeting individuals through other channels for better conversion.