iterationlayer Extract KPIs and Generate a Client Report
Marketing and consulting agencies use this pipeline to automate monthly client reporting — extracting performance metrics from analytics exports or campaign summaries and generating branded PDF reports ready for delivery.
APIs Used
Document Extraction (1 credit per page), Document Generation (1 credits/request)
Prerequisites
You need an Iteration Layer API key. Get one at platform.iterationlayer.com during the 7-day trial.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
Implementation
# Step 1: Extract KPIs from client document
EXTRACTION=$(curl -s -X POST https://api.iterationlayer.com/document-extraction/v1/extract \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"files": [
{
"type": "url",
"name": "campaign-summary-q1.pdf",
"url": "https://example.com/reports/campaign-summary-q1-2026.pdf"
}
],
"schema": {
"fields": [
{
"name": "client_name",
"type": "TEXT",
"description": "Client or company name"
},
{
"name": "report_period",
"type": "TEXT",
"description": "Reporting period, e.g. Q1 2026"
},
{
"name": "total_impressions",
"type": "INTEGER",
"description": "Total ad impressions"
},
{
"name": "total_clicks",
"type": "INTEGER",
"description": "Total ad clicks"
},
{
"name": "click_through_rate",
"type": "DECIMAL",
"description": "Click-through rate as a percentage"
},
{
"name": "total_conversions",
"type": "INTEGER",
"description": "Total conversions or leads generated"
},
{
"name": "cost_per_conversion",
"type": "CURRENCY_AMOUNT",
"description": "Average cost per conversion"
},
{
"name": "total_spend",
"type": "CURRENCY_AMOUNT",
"description": "Total advertising spend"
},
{
"name": "return_on_ad_spend",
"type": "DECIMAL",
"description": "Return on ad spend ratio"
}
]
}
}')
# Step 2: Generate a branded PDF report
curl -X POST https://api.iterationlayer.com/document-generation/v1/generate \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"format": "pdf",
"document": {
"metadata": {
"title": "Q1 2026 Campaign Performance — Greenfield Organics",
"author": "Spark Digital Agency"
},
"page": {
"size": {
"preset": "A4"
},
"margins": {
"top_in_pt": 54,
"right_in_pt": 54,
"bottom_in_pt": 54,
"left_in_pt": 54
}
},
"content": [
{
"type": "headline",
"level": "h1",
"text": "Spark Digital Agency"
},
{
"type": "headline",
"level": "h2",
"text": "Campaign Performance Report — Q1 2026"
},
{
"type": "paragraph",
"runs": [
{
"text": "Prepared for: ",
"font_weight": "bold"
},
{
"text": "Greenfield Organics"
}
]
},
{
"type": "separator"
},
{
"type": "headline",
"level": "h3",
"text": "Key Performance Indicators"
},
{
"type": "table",
"header": {
"cells": [
{
"text": "Metric"
},
{
"text": "Value"
}
]
},
"rows": [
{
"cells": [
{
"text": "Total Impressions"
},
{
"text": "1,245,800"
}
]
},
{
"cells": [
{
"text": "Total Clicks"
},
{
"text": "37,420"
}
]
},
{
"cells": [
{
"text": "Click-Through Rate"
},
{
"text": "3.00%"
}
]
},
{
"cells": [
{
"text": "Total Conversions"
},
{
"text": "1,870"
}
]
},
{
"cells": [
{
"text": "Cost per Conversion"
},
{
"text": "$12.45"
}
]
},
{
"cells": [
{
"text": "Total Spend"
},
{
"text": "$23,281.50"
}
]
},
{
"cells": [
{
"text": "Return on Ad Spend"
},
{
"text": "4.2x"
}
]
}
]
},
{
"type": "separator"
},
{
"type": "paragraph",
"runs": [
{
"text": "Report generated by Spark Digital Agency. For questions, contact reporting@sparkdigital.io"
}
]
}
]
}
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
// Step 1: Extract KPIs from client document
const extraction = await client.extractDocument({
files: [
{
type: "url",
name: "campaign-summary-q1.pdf",
url: "https://example.com/reports/campaign-summary-q1-2026.pdf",
},
],
schema: {
fields: [
{ name: "client_name", type: "TEXT", description: "Client or company name" },
{ name: "report_period", type: "TEXT", description: "Reporting period, e.g. Q1 2026" },
{ name: "total_impressions", type: "INTEGER", description: "Total ad impressions" },
{ name: "total_clicks", type: "INTEGER", description: "Total ad clicks" },
{ name: "click_through_rate", type: "DECIMAL", description: "Click-through rate as a percentage" },
{ name: "total_conversions", type: "INTEGER", description: "Total conversions or leads generated" },
{ name: "cost_per_conversion", type: "CURRENCY_AMOUNT", description: "Average cost per conversion" },
{ name: "total_spend", type: "CURRENCY_AMOUNT", description: "Total advertising spend" },
{ name: "return_on_ad_spend", type: "DECIMAL", description: "Return on ad spend ratio" },
],
},
});
const clientName = String(extraction["client_name"].value);
const reportPeriod = String(extraction["report_period"].value);
const totalImpressions = String(extraction["total_impressions"].value);
const totalClicks = String(extraction["total_clicks"].value);
const clickThroughRate = String(extraction["click_through_rate"].value);
const totalConversions = String(extraction["total_conversions"].value);
const costPerConversion = String(extraction["cost_per_conversion"].value);
const totalSpend = String(extraction["total_spend"].value);
const returnOnAdSpend = String(extraction["return_on_ad_spend"].value);
// Step 2: Generate a branded PDF report
const report = await client.generateDocument({
format: "pdf",
document: {
metadata: {
title: `${reportPeriod} Campaign Performance — ${clientName}`,
author: "Spark Digital Agency",
},
page: {
size: { preset: "A4" },
margins: { top_in_pt: 54, right_in_pt: 54, bottom_in_pt: 54, left_in_pt: 54 },
},
content: [
{ type: "headline", level: "h1", text: "Spark Digital Agency" },
{ type: "headline", level: "h2", text: `Campaign Performance Report — ${reportPeriod}` },
{
type: "paragraph",
runs: [
{ text: "Prepared for: ", font_weight: "bold" },
{ text: clientName },
],
},
{ type: "separator" },
{ type: "headline", level: "h3", text: "Key Performance Indicators" },
{
type: "table",
header: { cells: [{ text: "Metric" }, { text: "Value" }] },
rows: [
{ cells: [{ text: "Total Impressions" }, { text: totalImpressions }] },
{ cells: [{ text: "Total Clicks" }, { text: totalClicks }] },
{ cells: [{ text: "Click-Through Rate" }, { text: `${clickThroughRate}%` }] },
{ cells: [{ text: "Total Conversions" }, { text: totalConversions }] },
{ cells: [{ text: "Cost per Conversion" }, { text: costPerConversion }] },
{ cells: [{ text: "Total Spend" }, { text: totalSpend }] },
{ cells: [{ text: "Return on Ad Spend" }, { text: `${returnOnAdSpend}x` }] },
],
},
{ type: "separator" },
{
type: "paragraph",
runs: [{ text: "Report generated by Spark Digital Agency. For questions, contact reporting@sparkdigital.io" }],
},
],
},
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
# Step 1: Extract KPIs from client document
extraction = client.extract_document(
files=[
{
"type": "url",
"name": "campaign-summary-q1.pdf",
"url": "https://example.com/reports/campaign-summary-q1-2026.pdf",
}
],
schema={
"fields": [
{"name": "client_name", "type": "TEXT", "description": "Client or company name"},
{"name": "report_period", "type": "TEXT", "description": "Reporting period, e.g. Q1 2026"},
{"name": "total_impressions", "type": "INTEGER", "description": "Total ad impressions"},
{"name": "total_clicks", "type": "INTEGER", "description": "Total ad clicks"},
{"name": "click_through_rate", "type": "DECIMAL", "description": "Click-through rate as a percentage"},
{"name": "total_conversions", "type": "INTEGER", "description": "Total conversions or leads generated"},
{"name": "cost_per_conversion", "type": "CURRENCY_AMOUNT", "description": "Average cost per conversion"},
{"name": "total_spend", "type": "CURRENCY_AMOUNT", "description": "Total advertising spend"},
{"name": "return_on_ad_spend", "type": "DECIMAL", "description": "Return on ad spend ratio"},
]
},
)
client_name = extraction["client_name"]["value"]
report_period = extraction["report_period"]["value"]
total_impressions = extraction["total_impressions"]["value"]
total_clicks = extraction["total_clicks"]["value"]
click_through_rate = extraction["click_through_rate"]["value"]
total_conversions = extraction["total_conversions"]["value"]
cost_per_conversion = extraction["cost_per_conversion"]["value"]
total_spend = extraction["total_spend"]["value"]
return_on_ad_spend = extraction["return_on_ad_spend"]["value"]
# Step 2: Generate a branded PDF report
report = client.generate_document(
format="pdf",
document={
"metadata": {
"title": f"{report_period} Campaign Performance — {client_name}",
"author": "Spark Digital Agency",
},
"page": {
"size": {"preset": "A4"},
"margins": {"top_in_pt": 54, "right_in_pt": 54, "bottom_in_pt": 54, "left_in_pt": 54},
},
"content": [
{"type": "headline", "level": "h1", "text": "Spark Digital Agency"},
{"type": "headline", "level": "h2", "text": f"Campaign Performance Report — {report_period}"},
{
"type": "paragraph",
"runs": [
{"text": "Prepared for: ", "font_weight": "bold"},
{"text": client_name},
],
},
{"type": "separator"},
{"type": "headline", "level": "h3", "text": "Key Performance Indicators"},
{
"type": "table",
"header": {"cells": [{"text": "Metric"}, {"text": "Value"}]},
"rows": [
{"cells": [{"text": "Total Impressions"}, {"text": str(total_impressions)}]},
{"cells": [{"text": "Total Clicks"}, {"text": str(total_clicks)}]},
{"cells": [{"text": "Click-Through Rate"}, {"text": f"{click_through_rate}%"}]},
{"cells": [{"text": "Total Conversions"}, {"text": str(total_conversions)}]},
{"cells": [{"text": "Cost per Conversion"}, {"text": str(cost_per_conversion)}]},
{"cells": [{"text": "Total Spend"}, {"text": str(total_spend)}]},
{"cells": [{"text": "Return on Ad Spend"}, {"text": f"{return_on_ad_spend}x"}]},
],
},
{"type": "separator"},
{"type": "paragraph", "runs": [{"text": "Report generated by Spark Digital Agency. For questions, contact reporting@sparkdigital.io"}]},
],
},
)
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
result, err := client.ExtractDocument(il.ExtractDocumentRequest{
Files: []il.FileInput{
il.FileInput{
Type: "url",
Name: "campaign-summary-q1.pdf",
Url: "https://example.com/reports/campaign-summary-q1-2026.pdf",
},
},
Schema: il.ExtractionSchema{
Fields: []any{
il.TextFieldConfig{
Name: "client_name",
Type: "TEXT",
Description: "Client or company name",
},
il.TextFieldConfig{
Name: "report_period",
Type: "TEXT",
Description: "Reporting period, e.g. Q1 2026",
},
il.IntegerFieldConfig{
Name: "total_impressions",
Type: "INTEGER",
Description: "Total ad impressions",
},
il.IntegerFieldConfig{
Name: "total_clicks",
Type: "INTEGER",
Description: "Total ad clicks",
},
il.DecimalFieldConfig{
Name: "click_through_rate",
Type: "DECIMAL",
Description: "Click-through rate as a percentage",
},
il.IntegerFieldConfig{
Name: "total_conversions",
Type: "INTEGER",
Description: "Total conversions or leads generated",
},
il.CurrencyAmountFieldConfig{
Name: "cost_per_conversion",
Type: "CURRENCY_AMOUNT",
Description: "Average cost per conversion",
},
il.CurrencyAmountFieldConfig{
Name: "total_spend",
Type: "CURRENCY_AMOUNT",
Description: "Total advertising spend",
},
il.DecimalFieldConfig{
Name: "return_on_ad_spend",
Type: "DECIMAL",
Description: "Return on ad spend ratio",
},
},
},
})
if err != nil {
panic(err)
}
_ = result
}
{
"name": "Extract KPIs and generate client report in Iteration Layer",
"nodes": [
{
"parameters": {
"content": "## Extract KPIs and Generate a Client Report\n\nMarketing and consulting agencies use this pipeline to automate monthly client reporting — extracting performance metrics from analytics exports or campaign summaries and generating branded PDF reports ready for delivery.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes on self-hosted n8n, or add it directly on n8n Cloud with Verified Community Nodes enabled.",
"height": 280,
"width": 500,
"color": 2
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
200,
40
],
"id": "c3d4e5f6-a7b8-9012-cdef-012345678901",
"name": "Overview"
},
{
"parameters": {
"content": "### Step 1: Extract KPIs\nResource: **Document Extraction**\n\nConfigure the Document Extraction parameters below, then connect your credentials.",
"height": 160,
"width": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
475,
100
],
"id": "c3d4e5f6-a7b8-9012-cdef-012345678902",
"name": "Step 1 Note"
},
{
"parameters": {
"content": "### Step 2: Generate Report PDF\nResource: **Document Generation**\n\nConfigure the Document Generation parameters below, then connect your credentials.",
"height": 160,
"width": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
725,
100
],
"id": "c3d4e5f6-a7b8-9012-cdef-012345678903",
"name": "Step 2 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "c3d4e5f6-a7b8-9012-cdef-012345678904",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "documentExtraction",
"schemaInputMode": "rawJson",
"schemaJson": "{\"fields\":[{\"name\":\"client_name\",\"type\":\"TEXT\",\"description\":\"Client or company name\"},{\"name\":\"report_period\",\"type\":\"TEXT\",\"description\":\"Reporting period\"},{\"name\":\"total_impressions\",\"type\":\"INTEGER\",\"description\":\"Total ad impressions\"},{\"name\":\"total_clicks\",\"type\":\"INTEGER\",\"description\":\"Total ad clicks\"},{\"name\":\"click_through_rate\",\"type\":\"DECIMAL\",\"description\":\"Click-through rate as a percentage\"},{\"name\":\"total_conversions\",\"type\":\"INTEGER\",\"description\":\"Total conversions\"},{\"name\":\"cost_per_conversion\",\"type\":\"CURRENCY_AMOUNT\",\"description\":\"Average cost per conversion\"},{\"name\":\"total_spend\",\"type\":\"CURRENCY_AMOUNT\",\"description\":\"Total advertising spend\"},{\"name\":\"return_on_ad_spend\",\"type\":\"DECIMAL\",\"description\":\"Return on ad spend ratio\"}]}",
"files": {
"fileValues": [
{
"fileInputMode": "url",
"fileName": "campaign-summary-q1.pdf",
"fileUrl": "https://example.com/reports/campaign-summary-q1-2026.pdf"
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "c3d4e5f6-a7b8-9012-cdef-012345678905",
"name": "Extract KPIs",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
},
{
"parameters": {
"resource": "documentGeneration",
"format": "pdf",
"documentJson": "{\n \"metadata\": {\n \"title\": \"{{ $json.report_period }} Campaign Performance — {{ $json.client_name }}\",\n \"author\": \"Spark Digital Agency\"\n },\n \"page\": {\n \"size\": { \"preset\": \"A4\" },\n \"margins\": { \"top_in_pt\": 54, \"right_in_pt\": 54, \"bottom_in_pt\": 54, \"left_in_pt\": 54 }\n },\n \"content\": [\n { \"type\": \"headline\", \"level\": \"h1\", \"text\": \"Spark Digital Agency\" },\n { \"type\": \"headline\", \"level\": \"h2\", \"text\": \"Campaign Performance Report — {{ $json.report_period }}\" },\n { \"type\": \"paragraph\", \"runs\": [{ \"text\": \"Prepared for: \", \"font_weight\": \"bold\" }, { \"text\": \"{{ $json.client_name }}\" }] },\n { \"type\": \"separator\" },\n { \"type\": \"headline\", \"level\": \"h3\", \"text\": \"Key Performance Indicators\" },\n { \"type\": \"table\", \"header\": { \"cells\": [{ \"text\": \"Metric\" }, { \"text\": \"Value\" }] }, \"rows\": [{ \"cells\": [{ \"text\": \"Total Impressions\" }, { \"text\": \"{{ $json.total_impressions }}\" }] }, { \"cells\": [{ \"text\": \"Total Clicks\" }, { \"text\": \"{{ $json.total_clicks }}\" }] }, { \"cells\": [{ \"text\": \"CTR\" }, { \"text\": \"{{ $json.click_through_rate }}%\" }] }, { \"cells\": [{ \"text\": \"Total Conversions\" }, { \"text\": \"{{ $json.total_conversions }}\" }] }, { \"cells\": [{ \"text\": \"Cost per Conversion\" }, { \"text\": \"{{ $json.cost_per_conversion }}\" }] }, { \"cells\": [{ \"text\": \"Total Spend\" }, { \"text\": \"{{ $json.total_spend }}\" }] }, { \"cells\": [{ \"text\": \"ROAS\" }, { \"text\": \"{{ $json.return_on_ad_spend }}x\" }] }] },\n { \"type\": \"separator\" },\n { \"type\": \"paragraph\", \"runs\": [{ \"text\": \"Report generated by Spark Digital Agency.\" }] }\n ]\n}"
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
750,
300
],
"id": "c3d4e5f6-a7b8-9012-cdef-012345678906",
"name": "Generate Report PDF",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Extract KPIs",
"type": "main",
"index": 0
}
]
]
},
"Extract KPIs": {
"main": [
[
{
"node": "Generate Report PDF",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
Extract KPIs from the client document at [file URL], then generate a branded PDF report. Use the extract_document tool with these fields:
- client_name (TEXT): Client or company name
- report_period (TEXT): Reporting period, e.g. Q1 2026
- total_impressions (INTEGER): Total ad impressions
- total_clicks (INTEGER): Total ad clicks
- click_through_rate (DECIMAL): Click-through rate as a percentage
- total_conversions (INTEGER): Total conversions or leads generated
- cost_per_conversion (CURRENCY_AMOUNT): Average cost per conversion
- total_spend (CURRENCY_AMOUNT): Total advertising spend
- return_on_ad_spend (DECIMAL): Return on ad spend ratio
Then use the generate_document tool to create a branded A4 PDF report presenting these KPIs in a table with the agency and client name.
Response
{
"success": true,
"data": {
"buffer": "JVBERi0xLjQ...",
"mime_type": "application/pdf"
}
}