Our weekly analytics reports are designed to help you understand the performance of your recommendation API and its impact on your e-commerce or B2C business. This guide provides an overview of the various metrics and measures included in the reports, helping you to make data-driven decisions and optimize your recommendation strategy.

Purpose of the Analytics Reports

Our analytics reports aim to:

1. Provide insights into the performance of the AI-powered recommendation engine.
2. Track key performance indicators (KPIs) related to user engagement, conversion, and revenue generation.
3. Help you identify areas for improvement and optimize your recommendations to better serve your customers.

Where to Find those Reports

You can find your analytics reports (monthly or weekly) under the section "Results and KPIs > Reports"

Report Contents

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Below is a brief description of the various metrics included in the weekly analytics reports:

Total Revenue

This is the total revenue generated by your e-commerce or B2C platform during the reporting period. This metric helps you track your overall business performance and growth.

Average Order Value (AOV)

AOV represents the average amount spent per order on your platform during the reporting period. This metric is useful for understanding customer spending patterns and identifying potential upsell or cross-sell opportunities.

Revenue Generated by Crossing Minds

This metric shows the revenue generated specifically through recommendations provided by our AI-powered platform. It allows you to evaluate the direct impact of the recommendation engine on your business's bottom line.

Counts of Recommendations Delivered

This metric displays the total number of recommendations served by the platform during the reporting period. It helps you gauge the level of engagement and the reach of the recommendation system.

User-to-Items

User-to-Items recommendations are personalized suggestions made for individual users based on their preferences, browsing history, and other behavioral data. This metric measures the performance of these personalized recommendations.

Item-to-Items

Item-to-Items recommendations suggest similar or complementary products to the ones users are currently viewing. This metric helps you understand the effectiveness of these contextual recommendations.

Session Based

Session-based recommendations are made based on users' activities within a single session, regardless of their past interactions. This metric measures the impact of these real-time recommendations on user engagement.

Counts of Recommendations Clicked

This metric tracks the number of times users clicked on recommendations during the reporting period. It helps you evaluate the relevance and attractiveness of the suggested items.

Count of Sessions Receiving Recommendations

This metric shows the number of user sessions during which recommendations were served. It helps you understand the reach of your recommendation engine and identify potential opportunities for improvement.

Counts of Sessions Converting After Clicking on Recommendations

This metric measures the number of user sessions where a conversion (e.g., purchase) occurred after clicking on a recommended item. It helps you assess the effectiveness of the recommendation system in driving conversions and revenue.

Comparison of Existing/Recurring Customers vs. New Ones

This metric compares the performance of the recommendation engine for existing or recurring customers with that of new customers. It helps you identify trends, patterns, and potential areas of improvement for customer retention and acquisition strategies.

Average Type of Interactions

This metric shows the average number of interactions users have with the recommendation system, such as clicks, views, and conversions. It helps you gauge user engagement and the overall effectiveness of your recommendation strategy.

We hope this documentation helps you better understand the purpose and content of our weekly analytics reports. By leveraging these insights, you can optimize your recommendation strategy to improve user experience, increase conversions, and grow your business. If you have any questions or need further assistance, please don't hesitate to reach out to our support team.

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