The method
Use this prompt after collecting website analytics data (Google Analytics, etc.). Input key metrics like bounce rate, conversion rate, and top exit pages. Target e-commerce, SaaS, or lead-generation sites for maximum impact.
The prompts
Prompt 1
Analyze the following website data and provide 5 actionable recommendations to improve conversion rates:
* Bounce Rate: 65%
* Conversion Rate: 2.5%
* Top Exit Page: /pricing
* Average Session Duration: 2 minutes
* Mobile Traffic: 40%
Consider user experience, pricing strategy, and call-to-action placement. Prioritize recommendations that can be implemented quickly and have the highest potential impact. Explain your reasoning for each recommendation, referencing the provided data. Specifically, address why the /pricing page is a top exit page and suggest improvements. Focus on strategies that would benefit mobile users.
* Bounce Rate: 65%
* Conversion Rate: 2.5%
* Top Exit Page: /pricing
* Average Session Duration: 2 minutes
* Mobile Traffic: 40%
Consider user experience, pricing strategy, and call-to-action placement. Prioritize recommendations that can be implemented quickly and have the highest potential impact. Explain your reasoning for each recommendation, referencing the provided data. Specifically, address why the /pricing page is a top exit page and suggest improvements. Focus on strategies that would benefit mobile users.
Prompt 2
I want to analyze website behavior based on data from Google Analytics, specifically focusing on e-commerce conversion funnel optimization for a store that sells hand-crafted coffee brewing equipment. My conversion funnel is structured as follows: Homepage -> Product Page -> Cart -> Checkout -> Order Confirmation. My data shows a significant drop-off between the 'Cart' and 'Checkout' stages. Provide a list of 5 hypotheses for why users are abandoning their carts, considering factors such as shipping costs, payment options, and security concerns. For each hypothesis, suggest 2 A/B tests that could be conducted to validate or invalidate it. Outline the key metrics to track for each A/B test and the criteria for determining a winning variation. Assume that website is optimized for both desktop and mobile users.