CSAT Analyzer

1import { relay } from "@relayplane/workflows";
2
3const result = await relay
4  .workflow("csat-analyzer")
5
6  // Step 1: Categorize feedback themes
7  .step("categorize")
8  .with("openai:gpt-4o")
9  .prompt(`Analyze these CSAT responses and categorize feedback:
10
11Responses (CSV format):
12{{csvResponses}}
13
14Categories to detect:
15- Product bugs/issues
16- Feature requests
17- Onboarding experience
18- Support quality
19- Performance/speed
20- Pricing concerns
21- Documentation quality
22
23Return JSON array:
24[{
25  "response_id": "id",
26  "score": 1-5,
27  "primary_theme": "category",
28  "sentiment": "positive|neutral|negative",
29  "actionable": boolean,
30  "urgency": "low|medium|high"
31}]`)
32
33  // Step 2: Identify root causes for low scores
34  .step("root-cause-analysis")
35  .with("anthropic:claude-3.5-sonnet")
36  .depends("categorize")
37  .prompt(`Analyze patterns in low-scoring responses (1-2 stars):
38
39Categorized Data: {{categorize.output}}
40
41Identify:
42- Most common complaints (with frequency)
43- Specific features/flows causing friction
44- Support interaction issues
45- Any critical bugs mentioned multiple times
46
47Group by theme and rank by impact.`)
48
49  // Step 3: Extract feature requests
50  .step("extract-requests")
51  .with("openai:gpt-4o")
52  .depends("categorize")
53  .prompt(`Extract feature requests from this CSAT data:
54
55{{categorize.output}}
56
57For each feature request, return:
58- Feature description
59- How many users requested it
60- User pain point it solves
61- Potential impact (low/med/high)
62
63Format as prioritized list.`)
64
65  // Step 4: Generate executive summary
66  .step("executive-summary")
67  .with("anthropic:claude-3.5-sonnet")
68  .depends("categorize", "root-cause-analysis", "extract-requests")
69  .prompt(`Create an executive summary for this CSAT analysis:
70
71Overall Data: {{categorize.output}}
72Root Causes: {{root-cause-analysis.output}}
73Feature Requests: {{extract-requests.output}}
74
75Include:
761. Overall satisfaction score and trend
772. Top 3 areas of concern
783. Top 3 feature requests
794. Immediate action items
805. 30-day improvement plan
81
82Target audience: Product & Engineering leadership
83Keep under 500 words.`)
84
85  .run({
86    csvResponses: surveyResponses,
87  });
88
89console.log("Summary:", result.steps["executive-summary"].output);
90console.log("Root Causes:", result.steps["root-cause-analysis"].output);

1// Schedule weekly CSAT analysis
2import { relay } from "@relayplane/workflows";
3import { sendEmail } from "./notifications";
4
5async function weeklyCSATReport() {
6  // Fetch last 7 days of responses
7  const responses = await fetchCSATResponses({
8    startDate: new Date(Date.now() - 7 * 24 * 60 * 60 * 1000),
9  });
10
11  const result = await relay
12    .workflow("csat-analyzer")
13    .run({
14      csvResponses: convertToCSV(responses),
15    });
16
17  // Email to leadership
18  await sendEmail({
19    to: ["product@company.com", "eng@company.com"],
20    subject: `Weekly CSAT Analysis - ${new Date().toLocaleDateString()}`,
21    body: result.steps["executive-summary"].output,
22    attachments: [{
23      filename: "root-causes.txt",
24      content: result.steps["root-cause-analysis"].output,
25    }],
26  });
27}

1# Schedule with cron
2relayplane schedules create weekly-csat \
3  --workflow csat-analyzer \
4  --cron "0 9 * * MON" \
5  --timezone "America/New_York"