Understanding Shopper Intelligence Turn AI Conversations into Actionable Business Insights

Understanding Shopper Intelligence: Turn AI Conversations into Actionable

Business Insights

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Introduction Shopper Intelligence gives you a comprehensive view of how customers interact with your AI Concierge. By analyzing customer conversations, emotions, and behaviors, this dashboard helps you identify opportunities to improve product discovery, enhance support, and increase conversions. What You'll Find in Shopper Intelligence

Forms of Assistance What it shows: A breakdown of topics your AI Concierge is handling in customer conversations.

How to use it

View the pie chart to see which topics are most frequent

1. Check the "% of conversations" column to understand topic distribution
2. Review "Reported as helpful/unhelpful" metrics to identify areas for improvement
3. Use the tabs to filter between different conversation contexts:
4. All: Shows all conversation topics regardless of context

Unhelpful: Filters to show only topics marked as unhelpful by customers Sales: Shows topics related to product questions, recommendations, and purchasing Support: Shows topics related to customer service issues, returns, and assistance

Pro Tips

Clicking on any topic row will navigate you to the Conversations page with that topic pre- filtered, allowing you to review specific conversation examples A single conversation may be assigned multiple topics (for example, both "Product availability" and "Pricing"), so the total number of topic-tagged conversations may exceed

your total conversation count This section helps you understand what customers are asking about most frequently and how effectively your AI is resolving these inquiries. Visitor Drop-Off Reasons (Beta) What it shows: AI-generated categorization explaining why shoppers didn't complete their purchase.

How to use it

Review the most common drop-off reasons in the chart

1. Check the conversation count and percentage for each issue
2. Focus on high-percentage issues first to make the biggest impact
3. Common drop-off reasons might include product availability issues, complicated exchange

processes, or lack of product information. Addressing these issues can help reduce abandoned carts and increase conversions. Shopper Emotion Analysis (Beta) What it shows: The emotional motivation or tone detected in customer conversations when they initially engage with your AI.

How to use it

See what emotions drive customers to initially engage with your AI

1. Identify emotional patterns that might affect purchasing decisions
2. Use this insight to adjust your AI's tone and approach
3. This analysis reveals the initial sentiment of shoppers when they begin a conversation - before

any interaction with your AI Concierge. Understanding these starting emotions like "Seeking Clarity," "Needs Assistance," or "High Interest" helps you identify common customer mindsets and optimize your experience accordingly. By analyzing these initial emotions, you can better understand what brings customers to seek

assistance and tailor your AI's responses to address these starting points effectively. Top 10 Products Added to Cart by the Concierge What it shows: Products most frequently added to carts through AI-assisted conversations.

How to use it

Identify which products convert best through AI conversations

1. Compare this data with your overall best-sellers
2. Consider featuring high-converting products more prominently
3. This insight helps you understand which products perform best when recommended by your AI

Concierge. Top 10 PDP Redirects by the Concierge What it shows: Product pages that customers most frequently visit after AI recommendations.

How to use it

See which products generate high customer interest

1. Identify products that customers want to learn more about
2. Compare with cart additions to spot conversion opportunities
3. This section highlights products that generate interest but may need additional information or

incentives to convert to sales. Making the Most of Shopper Intelligence

For best results, follow this workflow

Start with "Forms of Assistance" to understand what customers need help with most

1. Check "Drop-Off Reasons" to identify and fix major conversion blockers
2. Use "Emotion Analysis" to evaluate customer initial sentiments and adjust your approach
3. Review top products to optimize your catalog and AI training
4. Troubleshooting

Issue: Data inconsistencies between charts Ensure you're using the same date range for all comparisons Remember that some metrics only track web conversations (not email) Issue: Percentages don't add up to exactly 100% This is normal due to rounding in the display and won't affect your analysis Issue: Some conversations appear without topics

This may happen for very short interactions or when topics can't be confidently determined Issue: Total topic numbers seem higher than total conversations This is expected because one conversation can have multiple topics assigned to it