A/B Splitter card allows you to randomly split the customers into two groups and send them different display cards or rules cards. You can use an A/B Splitter card to test different messages, media, or buttons and measure their effectiveness.
Common Use Cases For A/B Spitter Card
Testing Different Conversation Starters to Improve User Engagement:
Example:
Variation A (Original): "Hello! How can I assist you today?"
Variation B (Alternative): "Hi there! Ready to explore our latest deals?"
Outcome: By using "A/B Splitter Cards" to test these conversation starters, we can analyze which one generates higher engagement rates and encourages users to interact more with the chatbot.
Comparing Variations of Product Recommendations to Boost Sales:
Example:
Variation A (Original Recommendation): "Based on your preferences, we recommend product X."
Variation B (Alternative Recommendation): "Customers like you have found product Y to be a best-seller."
Outcome: By comparing these variations, we can determine which recommendation strategy leads to higher conversion rates and increased sales of the recommended products.
Experimenting with Different Phrasing for Calls to Action to Enhance Click-Through Rates:
Example:
Variation A (Original CTA): "Click here to learn more."
Variation B (Alternative CTA): "Discover the details now."
Outcome: A/B testing the phrasing of calls to action can reveal which one resonates better with users and results in higher click-through rates, leading to increased user engagement.
Evaluating Variations of Customer Support Responses to Improve User Satisfaction:
Example:
Variation A (Original Response): "I apologize for the inconvenience. We'll resolve your issue ASAP."
Variation B (Alternative Response): "I'm really sorry to hear that. Let's work together to get this sorted out."
Outcome: Testing these response variations can help identify which one leads to higher user satisfaction and a better customer support experience.
Testing Different Responses for Resolving Common User Queries More Efficiently:
Example:
Variation A (Original Response): "Please provide your order number, and I'll look into your query."
Variation B (Alternative Response): "To assist you better, could you share your order number with me, please?"
Outcome: A/B testing these responses can help determine which approach is more effective in encouraging users to provide necessary information quickly, streamlining query resolution.
How It Works:
When a user reaches an "A/B Splitter Card" in the conversation flow, the card randomly assigns the user to one of several variations (e.g., Variation A and Variation B).
Each variation represents a different version of the conversation. These variations may differ in terms of wording, tone, layout, call-to-action buttons, or any other relevant factors.
As users interact with the assigned variation, the chatbot collects data on their behavior and responses. This data includes metrics like click-through rates, engagement time, conversion rates, and user feedback.
After a sufficient sample size has been collected, the performance of each variation is analyzed. This involves comparing the data from each variation to determine which one achieved the desired objective more effectively.
Based on the analysis, chatbot developers can identify the most effective variation and make informed decisions about which conversation or response to permanently implement. It's a way to continually optimize chatbot interactions for better results.
Using A/B Splitter Card
Split Groups
You need to adjust the slider to set the percentage of customers that will be assigned to each group. You can choose any percentage from 0% to 100% for each group.
For example, you can set 50% for group A and 50% for group B, or 30% for group A and 70% for group B, etc.
Assign groups
You need to select the blocks that you want to send to each group. A block is a unit of message or action that you create and arrange in your journey/flow.
For example, you can select a block that shows the customer a video of your product for group A, and a block that shows the customer an image of your product for group B.
