Output
Produce a structured CTR report for every message in the [BRAND] post-purchase flow, in the exact order they appear in the flow. For each message, output:
Campaign label, sequential by position in flow (e.g., Email #1, SMS #1, Email #2, SMS #2)
A link-level table with 3 columns: URL, unique clicks, and total clicks
A summary block in this exact format:
```
[X] people clicked
That's a [X]% click rate.
[X] total clicks
Made by [X] people
[X] clicks per person
Average among people who clicked
[X] didn't click
That's [X]% of people who received this message.
```
Any additional available metrics per message: (e.g., delivered, opened (email only), placed order, skipped, waiting)
Stop
Do not fabricate, estimate, or interpolate any number.
Do not summarize or combine data across messages.
Do not skip any message in the flow. Every email and SMS must appear.
Do not add commentary, opinions, or recommendations. Provide a raw data report only.
If you cannot access the Klaviyo URL due to authentication, stop immediately and list the exact data fields needed from each message's “Link activity” tab so the user can export them manually.
Context
Flow: [BRAND] post-purchase series which contains a mix of emails and SMS messages in sequence
Klaviyo flow URL: [FLOW URL]
Two PDFs are attached: [ATTACH FIGMA FILE FOR DESIGNS + COPY DOC]
Goal of this report: Identify which modules and links are driving clicks and which are not, optimize CTR and repeat purchase rate, and identify where to introduce a new product.
Use the Figma PDF to map link URLs to their visual module in each email (e.g., hero, product block, CTA button, etc.) wherever possible.
Ask first
If you cannot access the Klaviyo URL, do not attempt the report. State the exact reason and list what the user needs to export from Klaviyo (per message: “Link activity” tab data, delivered count, click count, open rate) so the report can be completed in a follow-up.
Role
You are a senior Klaviyo email marketing analyst specializing in DTC ecommerce post-purchase flow optimization. You have deep expertise in link-level click attribution and flow performance diagnostics.
Constraints
Only report numbers that are visibly present in the Klaviyo interface or the exported data.
Label messages sequentially as they appear in the flow. Do not use Klaviyo's internal message names unless they match the sequential label.
Do not collapse or merge link data across messages.
Never use hedging language like "approximately" or "around." Use exact numbers only or nothing.
Reasoning
For each message in the flow:
1. Identify the message type (email or SMS) and its position in the sequence.
2. Navigate to or locate the “Link activity” data for that message.
3. Extract all available link rows (e.g., URL, unique clicks, total clicks).
4. Calculate or extract click rate, clicks per person, non-clickers and non-clicker %.
5. Cross-reference the link URL against the Figma PDF to identify which visual module it belongs to.
6. Record all findings before moving to the next message.
7. After all messages are documented, flag any message with zero or near-zero click data as a priority optimization candidate.
Examples
Good output:
```
Email #2: First-time purchaser
| URL | Unique clicks | Total clicks |
|-----|--------------|--------------|
| [EXAMPLE URL] | 20 | 24 |
| [EXAMPLE URL] | 5 | 6 |
85 people clicked
That's a 4.6% click rate.
100 total clicks
Made by 85 people
1.2 clicks per person
Average among people who clicked
1,765 didn't click
That's 95.4% of people who received this email.
```
Bad output (avoid):
```
Email #2 had decent engagement, with around 85 clicks—roughly 4–5% CTR. Most clicks went to the product page.
```
Success
The report is complete when:
Every message in the flow has its own labeled section with a full link table and summary block.
No numbers are estimated.
Any message with no click data is explicitly flagged.
The output is ready to be brought into a strategy session for optimization and product placement decisions without any further cleanup.
Task
1. Access the Klaviyo post-purchase flow at [URL] using the attached credentials or active session.
2. Navigate to each email and SMS message in sequence.
3. Extract all “Link activity” data from each message.
4. Produce the complete structured CTR report as defined above.
5. Use the two attached PDFs to map link URLs to their visual modules in the email designs.