Zigzag + UserTesting

Zigzag would need to assess important aspects of the AI chat function, now affectionately known as Ziggy. The team sought to ensure subscriber growth, confirm user willingness to pay for the solution, measure user satisfaction with the answers they receive, evaluate whether users understand the feature, and validate that users would ultimately prefer the AI chat over searching with Google.

They conducted the following tests to refine their approach: 

• User interviews. Interviews helped Jack and Marija gather insights about user behaviors and preferences. From these interviews, they learned that users hesitate to bother puppy coaches with what they perceive as trivial questions, but are comfortable asking questions to the AI chatbot. 
• Proposed solution testing. Zigzag developed multiple variations for the look and feel of the AI solution. They tested these solutions with users to gauge acceptance and effectiveness. 
• Prompt testing. Jack and Marija tested the prompts in their prototypes and also the outputs to users. This helped Zigzag observe user interactions and gather feedback regarding usability and engagement. 

The team conducted multiple rounds of Figma prototype testing that focused on key aspects: discoverability, first impressions, and user willingness to engage with Ziggy. The results of these tests allowed them to refine the designs and the functionality. 

Key findings

• Genuine interest in AI chat. Initial tests revealed that more than 90% of users were interested in the AI chat feature.
• Value proposition engagement. Only 60% of users expressed interest in reading the value proposition about the AI chat, so the Zigzag team separated the value proposition into smaller pieces across three pages, rather than the long description they had featured in the prototype version. 
• Successful prompt implementation. 100% of testers successfully interacted with Ziggy’s initial prompts. They enjoyed the first interactions and this indicated to Zigzag that they had successfully designed the first step in the process. 

Marija says, “Findings from the tests made us change the way we present information at the first point of entry into the AI chat feature. That got us thinking about how we can make Ziggy more fun and engaging for users. Adding more screens into the app is always scary, but it was important for us to pace the experience so the users could easily understand the value of the chat function. Multiple tests since then have helped us identify which features we could include in the initial launch and others that we should adjust.”

Business metrics demonstrate the impact of implementing the AI chat feature within the Zigzag app. The results reflect improvements in user engagement, conversion, customer satisfaction, feature adoption, and operational efficiency. By addressing user needs and delivering a superior experience, Zigzag’s AI chat feature launch has contributed to the success of the app and will help to drive business growth overall. 

• The AI chat function received 96% positive feedback from customers
• Within the first six months, customers have interacted with Ziggy more than 80,000 times
• Even as the user base grows, Zigzag has seen a 27% reduction in requests for support from human trainers. This will enable Zigzag to cost-effectively grow the business, with the ability to offer human training support for the users who need it most