Fix a retailer's discovery and service gaps — decision exercise
Exercise: fix a retailer's discovery and service gaps
Original fictional scenario. No cloud account, API calls or paid services are required. Difficulty: intermediate · Estimated duration: 15–20 minutes
Northwind Home, an invented furniture retailer, lists five complaints from its customer operations review. Each needs one primary Google Cloud offering.
| # | Complaint |
|---|---|
| 1 | Shoppers type "sofa for small flat" and the site search returns nothing unless they type a product code. |
| 2 | The help chatbot invents a returns window instead of quoting Northwind's own policy. |
| 3 | Half of all calls are "where is my order?" and wait in the queue for a person. |
| 4 | Representatives handling disputes search four manuals mid-call and write notes for ten minutes afterwards. |
| 5 | Managers cannot say why call volume rose last month or how callers felt. |
Your decision
- Assign one offering to each complaint and give the one-line reason.
- Order a single customer contact through the products you chose for complaints 3–4, naming what happens when the first step cannot resolve the issue.
- One manager proposes Grounding with Google Search for complaint 2. Explain why it is the wrong source.
- If Northwind also wanted the chatbot to mention a public holiday announced this morning, what would change, and what would stay the same?
Rubric (10 house points)
- 5 points: one correct offering per complaint, with its reason.
- 2 points: the contact flow — virtual agent first, handoff to a person with Agent Assist when unresolved.
- 2 points: explain that Google Search grounding uses public web data, which does not contain Northwind's policy.
- 1 point: add web grounding for the public fact while keeping policy answers grounded on Northwind's documents.
Reference solution
1 → Agent Search over Northwind's site: it builds search for public websites and replaces keyword matching with conversational search. 2 → grounding on Northwind's own documents in Agent Search, so answers come from its policy. 3 → a virtual agent built in CX Agent Studio, answering order-status questions without a person. 4 → Agent Assist, which suggests documents and responses during the call and summarizes the interaction when it ends. 5 → CX Insights, which analyses caller sentiment and call topics.
The contact flow: the contact center platform queues and routes the contact to the virtual agent; if it cannot resolve the issue, the conversation is handed off to a human agent, who receives Agent Assist suggestions.
Rejected alternatives: Grounding with Google Search for the policy (public web data cannot know Northwind's rules); Agent Assist for complaint 3 (it helps representatives, but the goal is to avoid needing one); Insights for complaint 4 (it analyses afterwards, not during the call).
For the holiday announcement, add Grounding with Google Search for current public facts; the returns policy stays grounded on Northwind's documents. Grounding source follows the question.
Sources and scope
All organisations, names, numbers, thresholds, the rubric and the conclusions above are house-authored. The product facts the reasoning depends on are grounded in:
- https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/vertex-ai-search
- https://cloud.google.com/products/gemini-enterprise-agent-platform/agent-search
- https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/grounding/grounding-with-google-search
- https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/grounding/overview
- https://docs.cloud.google.com/gemini-enterprise-cx/cx-agent-studio
- https://docs.cloud.google.com/gemini-enterprise-cx/agent-assist/basics
- https://cloud.google.com/gemini-enterprise-cx/agent-assist
- https://docs.cloud.google.com/gemini-enterprise-cx/insights
- https://docs.cloud.google.com/contact-center/ccai-platform/docs