Empower Your Business With The Magic Of Machine Learning!
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Empower Your Business With The Magic Of Machine Learning!
Your intelligent paint and home improvement assistant identifies key performance indicators (KPIs) and data points that provide valuable insights to your business.
Here are 20 KPIs and the relevant dashboard.
Main Dashboard (Overview)
The main dashboard provides a high-level summary of the most critical KPIs and metrics. It is visually engaging with charts, graphs, and summary widgets.
1. Header:
– Title: Intelligent Paint & Home Improvement Assistant Dashboard
– Date Range Selector: Allows users to filter data by specific time periods.
– User Profile: Profile picture, name, and a logout button.
2. Main Dashboard and KPIs:
-Users: The number of users per day
– Task Completion Rate: Pie chart showing the ratio of completed vs. incomplete tasks.
– Response Time: Line chart showing average response time over the selected period.
– Accuracy Rate: Gauge chart indicating the accuracy percentage.
– Usage Frequency: Bar chart comparing usage frequency across different periods.
3. User Engagement:
– Interaction Heatmap: Heatmap highlighting the most interacted sections of the assistant.
– Engagement Metrics: Number of interactions per session, average session duration.
4. Customer Satisfaction:
– Feedback Scores: Average feedback score with a distribution chart of ratings.
– Satisfaction Rate: Percentage of satisfied users displayed in a gauge chart.
5. Financial Impact:
– Revenues: Total amount of money generated by recommendations to users.
– Recommended Products: Bar chart for volume of recommended products.
Additional Tabs
1. Marketing and Sales
Provides insights to marketing and sales from the impact of the assistant on users.
-Product Enquires: Product keywords and enquires that users make
-Products Recommendations: Product recommendations made.
– Resellers Recommendations: Bar chart of recommended resellers.
– Conversion Rate: Funnel chart showing the conversion process from interaction to sale.
2. User Information
Aggregates user feedback and suggestions for product enhancements.
– Feedback Scores: Distribution of customer recommendations with sentiment analysis.
– User Recommendations: Word cloud or list of the most common recommendations.
– Support Tickets Analysis: Trends and common issues from support tickets.
See an example in the food industry below:
3. User Insights
Provides insights into user demographics and behavior patterns.
– User Demographics: Charts showing age, gender, and location distributions.
– Time of Use: Heatmap showing peak usage times throughout the day and week.
– Churn Rate Analysis: Line chart showing user churn rates over time.
4. Advanced Analytics
Offers advanced insights and predictive analytics for product development.
– Predictive Models: Predictive analytics for feature adoption and user engagement.
– Trend Analysis: Identifies emerging trends in user behavior and preferences.
5. Performance Analysis
Focuses on detailed performance metrics and trends over time.
– Response Time Analysis: Detailed line chart with filters for different time periods and user segments.
– Accuracy Rate Breakdown: Detailed report on accuracy rates by type of query.
– Error Rate Trends: Historical data and trends for error rates.
– User Retention Analysis: Cohort analysis showing retention rates over different periods.
6. Feature Usage
Analyzes which features are most and least used, helping identify areas for improvement.
– Feature Usage Statistics: Bar charts or heatmaps showing usage frequency of each feature.
– New Feature Adoption: Adoption rates of newly released features with comparative line charts.
– Support Tickets: Number of support tickets categorized by feature, displayed in a pie chart.
This structure ensures that the dashboard is intuitive and provides valuable insights at a glance while allowing your company to delve deeper into specific areas as needed.
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