Restaurant Reputation Analyst
A reputation operator for restaurant owners. On the 1st of each month, it pulls new Google Maps and TripAdvisor reviews from the past 30 days, runs sentiment analysis across food, service, value, wait time, and ambiance, deduplicates against reviews already analyzed, and clusters complaints into named friction points and staff excellence callouts. The output is an HTML email digest with star-trend, top issues, named staff highlights, and three concrete actions for the week.
Agent snapshot
Built for hospitality tourism work, not a generic template.
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template use
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catalog view
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integrations used
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labels matched
Sample input
Build an agent to restaurant Reputation Analyst. Use Gmail, Google Sheets, and Slack. Focus on operations. Return a ready-to-review result after each run.
Sample output
Monthly, scrapes Google Maps and TripAdvisor reviews from the last 30 days, scores food, service, value, wait time, and ambiance, surfaces friction points and staff wins, and emails you an HTML executive report.
Workflow brief
Where Restaurant Reputation Analyst fits in a hospitality tourism automation system
Restaurant Reputation Analyst is designed for a specific recurring job: a reputation operator for restaurant owners. On the 1st of each month, it pulls new Google Maps and TripAdvisor reviews from the past 30 days, runs sentiment analysis across food, service, value, wait time, and ambiance, deduplicates against reviews already analyzed, and clusters complaints into named friction points and staff excellence callouts. The output is an HTML email digest with star-trend, top issues, named staff highlights, and three concrete actions for the week. The agent page keeps the workflow concrete by showing the connected apps, the input a team can give Twin, and the output the run is expected to produce.
A team can start from this public template, adjust the instructions, connect the relevant accounts, and schedule the agent once the review path is clear. That makes it useful for repeatable work where the same research, update, summary, or follow-up needs to happen again.
In this setup Twin uses Gmail, Google Sheets, and Slack as source systems, action targets, or reporting destinations. The agent can combine those tools with browser automation and API calls when the workflow crosses systems.
What this agent automates
This run includes 7 concrete steps from the published agent data.
On the configured cadence, fetch new reviews from each selected review source for the configured restaurant and location
Hash each review by source, author handle, date, and first 80 chars; skip rows already in the agent database
Run sentiment scoring across the configured dimensions and tag each review positive, neutral, or negative
Cluster negative reviews into friction points and positive reviews into staff or dish excellence callouts
Compute star trend, NPS-style net sentiment, and biggest movers vs the previous period
Render an HTML report with summary, dimension scores, top friction points, top excellence callouts, and three recommended actions
Integrations used
Restaurant Reputation Analyst connects Gmail, Google Sheets, and Slack.
Gmail
Connected in this agent
Google Sheets
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Slack
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Plans start at €20/mo