‹ All Google Cloud Generative AI Leader questions

GCP Generative AI Leader Practice Question 15: Post Call Quality Analytics

Google Cloud Generative AI Leader · Test 2 · question 5 of 10

Google Cloud's Gen AI Offeringsmedium

A utility's quality assurance team samples about 2% of its recorded support calls by hand each month, so it never really knows why customers call or where sentiment turns negative. The director wants analytics over *completed* conversations: the topics driving call volume, caller and representative sentiment, and which interactions deserve a reviewer's attention, feeding a dashboard for her operations meeting. She is not asking for anything that changes what happens during a live call.

Which Google Cloud offering is built for this?

Show answer and explanation

Answer:

D. Conversational Insights, which analyzes contact center conversations for call topics, sentiment, and review

Conversational Insights (the name the current exam guide uses, and now branded Customer Experience Insights (CX Insights) in the product documentation) helps users detect and visualize patterns in their contact center data. Import raw interaction data and it runs machine learning analytics for agent and caller sentiment, entity identification, and call topics, automatically flags interactions that need further review, and exports to BigQuery for custom analysis or visualization in Looker, the dashboard the director wants. It analyzes conversations after the fact, which matches her explicit statement that nothing about the live call should change (option D).

- A is wrong because Agent Assist works in real time, helping a representative during a live conversation. That is the opposite of the after-the-fact analysis requested here. - B is wrong because Conversational Agents automate the customer-facing side of an interaction. Deflecting calls is a different business goal from understanding the calls that already happened. - C is wrong because Model Garden is a model library for discovering, testing, and deploying models. It is a builder's catalog, not a contact center analytics product.

Reference: Conversational Insights (Customer Experience Insights)

Practice Test 2 ›

Study guides for Google Cloud Generative AI Leader

Google Cloud Digital Leader exam: what's on it, who it's forGoogle Cloud Digital Leader: August 2026 exam update, six sections, US$99 price as of November 2026, renewal, study plan and ACE comparison.

Agentic AI certification: Oracle, Google, GitHub, NVIDIAAgentic AI certifications in 2026: Oracle's free exam, GitHub GH-600, Google, NVIDIA and Claude, compared by status, price and role.

Google Cloud Generative AI Leader vs AWS AI PractitionerGoogle Cloud Generative AI Leader vs AWS AI Practitioner: format, cost, topics, free preparation and which certification to take first.

Best AI certifications 2026: AWS, Google, Microsoft, ClaudeThe best AI certifications in 2026 from AWS, Google, Microsoft, Claude and Databricks, by level, with price, status and which one to take first.

Google Cloud certification path: is ACE worth it?Is Google's Associate Cloud Engineer certification worth it? The Google Cloud certification path in 2026, with cost, format and which exam to take first.

Google Professional Agentic Architect: what it isGoogle's Professional Agentic Architect certification explained - beta status, the two-part exam, the five domains, price, validity and how to prepare.

What Is RAG? How Retrieval-Augmented Generation WorksWhat RAG is and how it works: chunking, embeddings, vector search, hybrid search, reranking, GraphRAG and agentic RAG on AWS, Google and Azure.

Google Cloud's generative AI offerings, mappedGemini app, Gemini for Workspace, Gemini Enterprise, Agent Search, the contact center suite and Agent Platform: which one a business should pick, and why.

Prompt engineering vs RAG vs fine-tuningWhen to use prompt engineering, retrieval-augmented generation, fine-tuning or continued pre-training, compared on cost, freshness, hallucination and privacy.