Internals of building a Customer Sentiment Intelligence with SerpAPI + System One

说明与用途

CSI管道自动收集、规范化、评分并路由来自Yelp和Google News的反馈，消除手动审核并加速关键问题响应。

问题

Manual review triage is a bottleneck; noisy data, inconsistent triage, late escalation, and unstructured records hinder CX teams.

结果

The CSI pipeline reduces manual triage workload, provides deterministic scoring, and routes feedback into clear actions, enabling faster and more consistent customer issue handling.

工作流

• Collect data via SerpAPI (Yelp search, Yelp reviews, Google News) without scrapers
• Normalize data into a single schema
• Score each item deterministically across seven dimensions using a rule engine
• Route items into DISCARD, QUEUE, ANALYZE, or ESCALATE based on score
• For ANALYZE/ESCALATE items, optionally run LLM-based deep analysis if API key available

证据

Manual review triage is a critical bottleneck. As review volumes grow daily, high-priority signals like churn risks and serious complaints routinely get buried under a mountain of noise.

来源

CSI aggregates public data like Yelp reviews and Google News into a single command. It instantly normalizes, deduplicates, and scores each item across seven dimensions, using an explainable rule engine to route data into four clear business actions: DISCARD, QUEUE, ANALYZE, or ESCALATE.

来源

Three design decisions worth noting: Per-item failure isolation, Backend-agnostic scoring, LLM spend is gated.

来源