AI Predictive Targeting is an add-on available in both Web Experimentation and Feature Experimentation.
For more details, please contact your Customer Success Manager.
Kameleoon AI Predictive Targeting is part of Kameleoon AI Copilot, an AI-driven set of capabilities that support every aspect of your experimentation program. AI Predictive Targeting leverages in-house machine learning algorithms to generate propensity scores. These scores enable you to adapt and target your offers and content in real-time based on your visitors’ buying behavior and intent.
For more information on Kameleoon AI Predictive Targeting, please read this documentation.
Step 1: Define a KPI to track the conversion onsite and activate Kameleoon’s AI
Kameleoon enables you to define as many KPIs as necessary and activate machine learning algorithms that automatically calculate, in real-time, the likelihood of a visitor converting against each of your important KPIs.
Once your goal is defined, the only action required to use AI predictive targeting with it is to enable the “Use this goal for machine learning” option from the Advanced settings of your goal.
n this Advanced Settings pop-up, you can also select the moment of the customer journey for calculating the AI propensity score for your goal. Kameleoon enables you to define triggers for each moment.
Note: A trigger characterizes a precise event that may occur during a visit. You will find the trigger builder in the Advanced Tools section, where you will be able to define the triggers that are relevant for the user experience of your product. You can configure the Kameleoon AI to calculate conversion propensity scores for this goal at any of the triggers you have defined. This will then allow you to use predictive targeting conditions when defining your personalization targetings. You can find more information on this here, here and here.
Kameleoon Predict will then automatically rank each visitor based on their Likelihood to convert, from 0 to 100. A Likelihood to convert of 0 means the visitor has the lowest chance to convert compared to other visitors. A Likelihood to convert of 100 means that they have the highest chance of converting compared to other visitors.
Then click on Save > Save to validate.
More information on activating Predictive Targeting
When you create a goal in Kameleoon, for example getting your visitors to add a product to their cart, you can decide whether you want to enable Predictive Targeting.
Once Predictive Targeting is activated for a goal, you are able to use it in an experiment or personalization once the following conditions are met:
- Our AI has learned from 100,000 visits;
- And our AI has learned from one full week of data.
For example, if your website receives 100,000 visits in one day, our AI will still need one full week to learn. Or if your website gets 50,000 visits per week, our AI will need two weeks to learn.
Once the learning phase is complete, you will have the ability to create a segment where you target visitors under the exact probability range you define.
Note: These criteria do not apply to the triggers you create. To achieve optimal performance, ensure they target a reasonable portion of your audience and that your goals have a decent conversion rate within them.
2. Create a segment with the Likelihood to convert range you want to target
Create a segment by using the Likelihood to convert criteria available in the segment builder. In this case, we want to target visitors with the highest chance of converting, meaning we select the 70-100 range.
We could have also directly selected a range from the dropdown menu:
- Very low [0%; 20%[
- Low [20%; 40%[
- Moderate [40%; 60%[
- High [40%; 60%[
- Very high [80%; 100%]
Select the goal on which you activated Kameleoon’s machine learning algorithms (Step 1) and the “trigger”.
Then validate the creation of your segment.
Step 3: Create a personalization, a web experiment or a feature experiment
We can then use the segment in a web experiment, a personalization campaign or a feature experiment.