About PX Insights

PX Insights is an advanced module designed to bridge the gap between market performance and your product catalog. By gathering data on SEO, AI discoverability, and customer sentiment, the tool transforms raw signals into actionable intelligence that helps you scale your product data quality.

Bridging the Data Gap

Most teams have access to valuable feedback—such as Google Shopping performance and customer reviews—but this data often remains siloed from the actual product catalog. PX Insights integrates these disconnected signals directly into your product model, ensuring your catalog is continuously optimized and truly AI-ready.

Our "Sense-Suggest-Scale" Framework

The module operates on a continuous feedback loop designed to turn market signals into results:

• Generative Engine Optimization (GEO): Analyze and improve your product visibility within AI assistants and chatbots (e.g., ChatGPT, Perplexity, and Google Gemini).
• Consumer Sentiment Analysis: Conduct automated market research by tracking and transforming customer feedback into product improvements.
• Performance Optimization: Identify and resolve Google Shopping feed errors to reduce wasted media spend and maximize your Return on Ad Spend (ROAS).

PX Insights: Available Signals & Features

PX Insights centralizes four key data streams within your PIM to help you move from basic data management to Product Experience (PX) Intelligence.

Discoverability (AI & SEO)

This feature helps you transition from traditional SEO to Generative Engine Optimization (GEO).

• Analyze AI Visibility: See how your products appear in generative AI results (e.g., ChatGPT, Google Gemini).
• Identify Ranking Factors: Understand which specific product attributes are driving visibility.
• Enrich for AI: Use the PIM to add AI-ready content, such as contextual FAQs and usage guides.

Core Tools:

• AI Readiness: Measures if your product data is structured correctly for machine readability.
• AI Discoverability: Evaluates if your product is being recommended for specific shopper intents.

Rating & reviews (Customer Sentiment)

Bridge the gap between customer feedback and your product catalog to reduce returns.

• Close Experience Gaps: Identify where product descriptions don't match reality based on customer reviews.
• AI-Generated Insights: Use AI to summarize reviews into improved descriptions or to prioritize specific product media.
• Actionable Workflows: Trigger content updates automatically when sentiment scores dip.
   

How to Connect:

• Pre-packaged Apps: Connect Yotpo or Bazaarvoice in a few clicks via the Akeneo App Store.
• Custom Integration: Use our Public API to pull sentiment data from any other third-party system.

Shopping performance

Protect your ad spend by identifying and fixing channel errors before they impact revenue.

• Real-time Alerts: Detect Google Shopping feed issues directly within the PIM.
• Business-First Prioritization: Sort data fixes based on business impact (campaigns, low-performing products)
• Automated Correction: Use rules and AI-assisted enrichment to fix errors at scale.
• Continuously sync improvements back to activation channels

How to Connect:

Install the Google Shopping App from the Akeneo App Store to sync performance metrics instantly.

Sales & Return

Align your catalog management with your bottom line.

• Prioritize High-Value Products: Identify top-revenue items that require "perfect" data.
• Reduce Returns: Spot high-return items and investigate if missing data or misleading descriptions are the cause.

How to Connect:

• All PX Insights packages support importing sales and return figures via flat file (CSV/XLSX).

Preparing Your Product Strategy for AI-Driven Search

To maximize your performance today while preparing for the future of AI-driven search, we recommend a dual-focus approach: Optimizing for Now and Getting Ready for What’s Next.

Strategy Overview

Actionable Next Steps

1. Protect Your Current Revenue
The foundation of AI readiness is a high-quality product feed. By refining your current listings, you aren't just improving your current ROI; you are providing the high-quality data that AI models require to recommend your products.

2. Leverage Feedback as a Content Engine
Don't just view customer reviews as a metric. Use the insights gathered from "Optimisation" to create contextual content. AI thrives on specific, high-intent data, so the more you learn from your customers now, the better your AI-driven content will perform later.

3. Transition to Machine-Readable Data
Traditional SEO is about human-readable content, but AI-driven search requires machine-readability.

• The Audit: Review your technical schema and metadata.
• The Goal: Ensure AI crawlers can instantly understand the attributes, benefits, and context of your products.

Tip: High-quality, structured data is the single most important factor in whether your products appear in AI-generated "best of" lists and search summaries.