KlickTipp This workflow corresponds to n8n.io template #16573 — we link there as the canonical source.
This workflow follows the Agent → OpenAI Chat recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "5cLAXSzFC5fMxoad",
"name": "AI greeting generator for email messaging via OpenAI and KlickTipp",
"tags": [],
"nodes": [
{
"id": "7bf7120e-0a73-4bc9-a32d-a250b4d51a22",
"name": "2. Get Gender based on First Name from KlickTipp",
"type": "n8n-nodes-base.stickyNote",
"position": [
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"parameters": {
"color": 7,
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"content": "## 2. Get Gender based on First Name from KlickTipp"
},
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{
"id": "942d5b36-2e9e-4bcc-a2e2-8f57a65e3502",
"name": "1. Trigger from a KlickTipp",
"type": "n8n-nodes-base.stickyNote",
"position": [
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"parameters": {
"color": 7,
"width": 232,
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"content": "## 1. Trigger from a KlickTipp"
},
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},
{
"id": "dcb16b46-8c13-49b5-ac1f-175c43cd43dd",
"name": "4. Get Gender and First Name based on Email address from KlickTipp",
"type": "n8n-nodes-base.stickyNote",
"position": [
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"parameters": {
"color": 7,
"width": 680,
"height": 636,
"content": "## 4. Get Gender and First Name based on Email address from KlickTipp"
},
"typeVersion": 1
},
{
"id": "c8b0b9ed-acf7-4873-b6cb-9aaaae89888c",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
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],
"parameters": {
"jsonSchemaExample": "{\n \"first_name\": \"\u2026\",\n \"last_name\": \"\u2026\",\n \"first_name_probability\": 0,\n \"last_name_probability\": 0,\n \"gender\": \"male|female|neutral\",\n \"gender_probability\": 0\n}\n"
},
"typeVersion": 1.3
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{
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"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
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"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-5-mini",
"cachedResultName": "gpt-5-mini"
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{
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"position": [
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"parameters": {
"jsonSchemaExample": "{\n \"gender\": \"male|female|neutral\",\n \"gender_probability\": 0\n}\n"
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"position": [
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"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-5-mini",
"cachedResultName": "gpt-5-mini"
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{
"id": "ab0f2c4d-2f09-493f-b1e0-316c6cb67d4c",
"name": "Get First Name and Gender via AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
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],
"parameters": {
"text": "=Process this email address:\n\"{{ $json.email }}\"",
"options": {
"systemMessage": "=**Role / Context** \nYou are a **smart name parser and gender estimator** for email addresses. \n\n**Task / Goal** \nExtract and return only the JSON object, no explanation or extra text. \n\n---\n\n**Parsing Rules** \n\n1. **Source priority** \n - Use the local part before \u201c@\u201d. \n - If the local part is a generic mailbox (`info`, `contact`, `sales`, `support`, `help`, `team`, `office`, `admin`, `webmaster`, `noreply`, `newsletter`), try to extract a name from the domain (exclude TLD). \n - If domain tokens look like **business/industry words** (e.g., \u201cfirst\u201d, \u201cplanner\u201d, \u201ctravel\u201d, \u201cdesign\u201d, \u201cmedia\u201d), treat them as **not names**. \n - If the domain contains a hyphenated two-word pattern resembling a real human name (e.g., `hermann-scherer.com`), map to first and last names. \n\n2. **Tokenization** \n - Split on `.`, `_`, `-`, `+`, and digits. \n - Remove digits. \n - Preserve hyphens in surnames (e.g., `smith-jones` \u2192 `Smith-Jones`). \n\n3. **Honorifics & suffixes** \n - Remove: `mr`, `mrs`, `ms`, `dr`, `prof`, `jr`, `sr`, `ii`, `iii`, `iv`, `phd`, `md`, `mba`. \n\n4. **Normalization**\n - Restore diacritics where obvious:\n - `Juergen` \u2192 `J\u00fcrgen`\n - `Joerg` \u2192 `J\u00f6rg`\n - `Goetz` \u2192 `G\u00f6tz`\n - `Schoen` \u2192 `Sch\u00f6n`\n\n - **German umlaut transliterations for selected name tokens (deterministic with guardrails):**\n - Apply the following ONLY to tokens that you have already selected as `first_name` or `last_name` AND that you believe are real human names.\n - If the selected name token contains these sequences, convert them.\n - **Important: treat `ae/oe/ue` as transliteration digraphs (2 letters \u2192 1 character):**\n - Replace the full sequence (`ae`, `oe`, `ue`) with the umlaut character (`\u00e4`, `\u00f6`, `\u00fc`) as **one character**.\n - **Do NOT keep the trailing `e`** after conversion.\n - Avoid invalid outcomes like: `Kl\u00fcenter`, `M\u00fceller`, `Sch\u00e4efer`.\n - Conversions:\n - `ae` \u2192 `\u00e4` (and `Ae` \u2192 `\u00c4`)\n - `oe` \u2192 `\u00f6` (and `Oe` \u2192 `\u00d6`)\n - `ue` \u2192 `\u00fc` (and `Ue` \u2192 `\u00dc`)\n - **Do NOT convert** if any of these exclusions apply:\n - `ue` occurs immediately after `q` (e.g., `que...`, `queue...`)\n - the entire token is an obvious English word (e.g., `blue`, `true`, `glue`)\n - the token was not confidently classified as a human name\n - Examples (correct):\n - `Kluenter` \u2192 `Kl\u00fcnter` (NOT `Kl\u00fcenter`)\n - `Mueller` \u2192 `M\u00fcller` (NOT `M\u00fceller`)\n - `Schaefer` \u2192 `Sch\u00e4fer` (NOT `Sch\u00e4efer`)\n - `Goetz` \u2192 `G\u00f6tz` (NOT `G\u00f6etz`)\n - Post-check:\n - After normalization, the output must not contain the patterns `\u00e4e`, `\u00f6e`, `\u00fce` created by a failed transliteration.\n - If such a pattern appears, fix it by removing the extra `e` (e.g., `Kl\u00fcenter` \u2192 `Kl\u00fcnter`).\n - If conversion is applied, keep Title Case and reduce the corresponding probability by **5\u201310 points** (unless it is a very common case like `Mueller` \u2192 `M\u00fcller`).\n\n - Use **Title Case**.\n - Do not invent longer names from single letters (e.g., `\"u\"` \u2260 `\"Uwe\"`).\n - If unsure about normalization, leave unchanged.\n\n5. **Real names only** \n - Assign `first_name_probability` and `last_name_probability` between 0\u2013100. \n - `100` = certain it is a valid first/last name, `0` = clearly not a human name. \n - Reject non-names: single letters and strings without clear meaning (e.g., grd), generic words, common nouns, professions, or concepts.\n - Use your general world knowledge of real given names and surnames across cultures.\n - Be conservative: if in doubt, lower probability rather than guessing.\n\n---\n\n**Name Ordering** \n- If `first.last` pattern \u2192 assign directly. \n- If ambiguous, choose the token with higher **given-name probability** as `first_name`. \n- If only one valid name is found \u2192 set as `first_name`, leave `last_name` empty. \n- Preserve hyphenated surnames. \n- Keep aliases/nicknames (e.g., `Katie`). \n- Always Title Case names. \n\n---\n\n**Gender & Probability Rules** \n- Base gender **only on first_name**. \n- `gender` \u2208 `{male, female, neutral}`. \n- `gender_probability` \u2208 `[0\u2013100]`. \n- If `<85` \u2192 set `gender = neutral`. \n- **Ambiguous names** (Chris, Alex, Sam, Pat, Taylor, Jordan, Robin): reduce gender probability by **15\u201325 points** from usual. If below 85, set neutral. \n- Do not infer gender from last_name. \n- If no valid first_name \u2192 set:\n{\n \"first_name\": \"\",\n \"last_name\": \"\",\n \"first_name_probability\": 0,\n \"last_name_probability\": 0,\n \"gender\": \"neutral\",\n \"gender_probability\": 0\n}\n\n---\n\n**Few-shot Guidance (do not echo back)** \n- `janet.smith@company.com` \u2192 `{\"first_name\":\"Janet\",\"last_name\":\"Smith\",\"first_name_probability\":100,\"last_name_probability\":100,\"gender\":\"female\",\"gender_probability\":95}` \n- `alex.johnson@domain.org` \u2192 `{\"first_name\":\"Alex\",\"last_name\":\"Johnson\",\"first_name_probability\":100,\"last_name_probability\":100,\"gender\":\"neutral\",\"gender_probability\":82}` \n- `michael.jr@service.com` \u2192 `{\"first_name\":\"Michael\",\"last_name\":\"\",\"first_name_probability\":100,\"last_name_probability\":0,\"gender\":\"male\",\"gender_probability\":95}` \n- `patricia_m@techfirm.net` \u2192 `{\"first_name\":\"Patricia\",\"last_name\":\"\",\"first_name_probability\":100,\"last_name_probability\":0,\"gender\":\"female\",\"gender_probability\":95}` \n- `chris.martin@company.co` \u2192 `{\"first_name\":\"Chris\",\"last_name\":\"Martin\",\"first_name_probability\":100,\"last_name_probability\":100,\"gender\":\"neutral\",\"gender_probability\":75}` \n- `taylor.smith-jones@workplace.org` \u2192 `{\"first_name\":\"Taylor\",\"last_name\":\"Smith-Jones\",\"first_name_probability\":100,\"last_name_probability\":100,\"gender\":\"neutral\",\"gender_probability\":67}` \n- `info@hermann-scherer.com` \u2192 `{\"first_name\":\"Hermann\",\"last_name\":\"Scherer\",\"first_name_probability\":100,\"last_name_probability\":100,\"gender\":\"male\",\"gender_probability\":95}`"
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2.1
},
{
"id": "d44349b4-33c3-44b0-9ae9-d2101e0f4e41",
"name": "Get Gender via AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
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],
"parameters": {
"text": "=Process this first name: \n`\"{{ $('Contact Tagged in KlickTipp').item.json.fieldFirstName }}\"`",
"options": {
"systemMessage": "=**Role / Context** \nYou are a **gender estimator for first names**. \n\n---\n\n**Task / Goal** \nEstimate the most likely gender for a given first name. \nReturn a JSON object with: \n- `gender`: `\"male\"`, `\"female\"`, or `\"neutral\"` \n- `gender_probability`: integer between 0\u2013100 \n\n---\n\n**Constraints / Rules** \n\n\u2705 Rules for classification: \n- Use only the **first_name** for gender estimation. \n- `gender_probability` must be an integer (0\u2013100). \n- If `gender_probability < 85` \u2192 set `gender = \"neutral\"`. \n- If the input is not a valid first name \u2192 \n{\n gender = \"neutral\"\n gender_probability = 0\n}\n\n\n\u274c Do not: \n- Infer gender from last names. \n- Output anything other than the required JSON object. \n\n\u2696\ufe0f Ambiguous / diminutive name handling: \n- If the name is a well-known short form, diminutive, or unisex nickname (e.g., Chris, Alex, Sam, Pat, Taylor, Jordan, Robin), **reduce gender certainty by 15\u201325 points** from the usual most-likely value. \n- If this reduction pushes probability below 85, return `\"neutral\"`. \n- Example: `\"Chris\"` \u2192 originally ~90% male \u2192 reduce to ~75% \u2192 return `\"neutral\"`. "
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2.1
},
{
"id": "d99918d6-f44d-45b7-9d47-3320286003ce",
"name": "Contact Tagged in KlickTipp",
"type": "n8n-nodes-klicktipp.klicktippTrigger",
"position": [
544,
496
],
"parameters": {},
"credentials": {},
"typeVersion": 1
},
{
"id": "e5c7ccaf-728a-4e4b-ad15-baf393ad1632",
"name": "Update Contact in KlickTipp",
"type": "n8n-nodes-klicktipp.klicktipp",
"position": [
2400,
352
],
"parameters": {
"fields": {
"dataFields": [
{
"fieldId": "field228721",
"fieldValue": "=Lieber {{ $('Contact Tagged in KlickTipp').item.json.fieldFirstName }},<br /><br />"
}
]
},
"resource": "subscriber",
"operation": "update",
"subscriberId": "={{ $('Contact Tagged in KlickTipp').item.json.id }}"
},
"credentials": {},
"typeVersion": 2
},
{
"id": "f95456bd-4d82-4617-8520-b038afc08df8",
"name": "Update Contact in KlickTipp1",
"type": "n8n-nodes-klicktipp.klicktipp",
"position": [
2400,
160
],
"parameters": {
"fields": {
"dataFields": [
{
"fieldId": "field228721",
"fieldValue": "=Liebe {{ $('Contact Tagged in KlickTipp').item.json.fieldFirstName }},<br /><br />"
}
]
},
"resource": "subscriber",
"operation": "update",
"subscriberId": "={{ $('Contact Tagged in KlickTipp').item.json.id }}"
},
"credentials": {},
"typeVersion": 2
},
{
"id": "b2a312fc-df88-46cc-8c22-7598c8308c9a",
"name": "Update Contact in KlickTipp2",
"type": "n8n-nodes-klicktipp.klicktipp",
"position": [
2400,
-48
],
"parameters": {
"fields": {
"dataFields": [
{
"fieldId": "field228721",
"fieldValue": "=Hallo {{ $('Contact Tagged in KlickTipp').item.json.fieldFirstName }},<br /><br />"
}
]
},
"resource": "subscriber",
"operation": "update",
"subscriberId": "={{ $('Contact Tagged in KlickTipp').item.json.id }}"
},
"credentials": {},
"typeVersion": 2
},
{
"id": "ee011a0d-1783-4e70-a11e-ebe6305c0065",
"name": "Documentation",
"type": "n8n-nodes-base.stickyNote",
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"parameters": {
"width": 679,
"height": 940,
"content": "Community Node Disclaimer: This workflow uses KlickTipp community nodes.\n\n## Introduction\nThis workflow automatically generates a personalized **email greeting** for KlickTipp contacts using **OpenAI**, and stores it as a reusable KlickTipp custom field. When a contact is tagged, the workflow creates a suitable greeting such as **\u201cLieber Ren\u00e9,\u201d**, **\u201cLiebe Laura,\u201d**, or a safe fallback like **\u201cHallo Ren\u00e9,\u201d** when the gender is uncertain. It also returns **confidence scores (0\u2013100)** so you can decide whether the detected gender and/or extracted name is reliable enough to use.\n\nThis automation is especially useful for marketers, coaches, creators, agencies, and service-based businesses who want consistent personalization at scale, while keeping messaging safe through confidence-based fallbacks and reducing the need for manual contact cleanup.\n\n## How it works\n1. **Trigger: Contact tagged in KlickTipp** (e.g., `HTML AI greeting for email messaging`)\n2. **Check contact data**\n - If **first name exists** \u2192 OpenAI estimates gender based on the first name.\n - If **first name is missing but email exists** \u2192 OpenAI extracts a first name from the email and estimates gender.\n3. **Filter by confidence**\n - If confidence is high (e.g., **>= 85**) \u2192 allow gendered greeting (**Lieber/Liebe**)\n - Otherwise \u2192 use neutral greeting (**Hallo {FirstName},**)\n4. **Update contact in KlickTipp**\n - Save the final **HTML greeting** into a dedicated custom field (reusable in all email templates)\n - Update the first name if it was extracted from email\n\n## Setup Instructions\n1. **KlickTipp preparation**\n - Create a trigger **tag** (e.g., `HTML AI greeting for email messaging`)\n - Create **custom field**:\n - **HTML AI placeholders | greeting**\n - Add **webhook**:\n - **Activation tag:** `HTML AI greeting for email messaging`\n - **Activation URL:** webhook URL from triggers\n\n2. **Credential Configuration**\n - Authenticate your KlickTipp connection with **username/password** credentials (API access required).\n - Connect your OpenAI account using an **API Key**.\n\n## Customization\n- **Threshold**: increase (stricter) or decrease (more coverage)\n- **Adjust greeting style**: if needed, change \u201cLieber/Liebe/Hallo\u201d to other words and phrases"
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"id": "39fd6111-411d-4e87-b715-7610ae562160",
"name": "Update Contact in KlickTipp5",
"type": "n8n-nodes-klicktipp.klicktipp",
"position": [
2400,
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],
"parameters": {
"fields": {
"dataFields": [
{
"fieldId": "field228721",
"fieldValue": "=Hallo {{ $json.output.first_name }},<br /><br />"
},
{
"fieldId": "fieldFirstName",
"fieldValue": "={{ $json.output.first_name }}"
},
{
"fieldId": "fieldLastName",
"fieldValue": "={{ $json.output.last_name_probability >= 85 ? $json.output.last_name : $('Contact Tagged in KlickTipp').item.json.fieldLastName }}"
}
]
},
"resource": "subscriber",
"operation": "update",
"subscriberId": "={{ $('Contact Tagged in KlickTipp').item.json.id }}"
},
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{
"id": "8d7fc29f-a881-403f-be47-f000ecd298ce",
"name": "Update Contact in KlickTipp4",
"type": "n8n-nodes-klicktipp.klicktipp",
"position": [
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],
"parameters": {
"fields": {
"dataFields": [
{
"fieldId": "field228721",
"fieldValue": "=Liebe {{ $json.output.first_name }},<br /><br />"
},
{
"fieldId": "fieldFirstName",
"fieldValue": "={{ $json.output.first_name }}"
},
{
"fieldId": "fieldLastName",
"fieldValue": "={{ $json.output.last_name_probability >= 85 ? $json.output.last_name : $('Contact Tagged in KlickTipp').item.json.fieldLastName }}"
}
]
},
"resource": "subscriber",
"operation": "update",
"subscriberId": "={{ $('Contact Tagged in KlickTipp').item.json.id }}"
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{
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"name": "Update Contact in KlickTipp3",
"type": "n8n-nodes-klicktipp.klicktipp",
"position": [
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"parameters": {
"fields": {
"dataFields": [
{
"fieldId": "field228721",
"fieldValue": "=Lieber {{ $json.output.first_name }},<br /><br />"
},
{
"fieldId": "fieldFirstName",
"fieldValue": "={{ $json.output.first_name }}"
},
{
"fieldId": "fieldLastName",
"fieldValue": "={{ $json.output.last_name_probability >= 85 ? $json.output.last_name : $('Contact Tagged in KlickTipp').item.json.fieldLastName }}"
}
]
},
"resource": "subscriber",
"operation": "update",
"subscriberId": "={{ $('Contact Tagged in KlickTipp').item.json.id }}"
},
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{
"id": "d3b1634e-218e-4b78-af4c-1c55b67dc67c",
"name": "Gender probability >= 85% ?",
"type": "n8n-nodes-base.switch",
"notes": "How the probability field works:\n\u2022 It ranges from 0 to 1 (or 0-100 %).\n\u2022 It reflects how often that name appeared with the returned gender in the dataset.\n\u2022 The higher the value, the more confident the service is.\n\nProbability \u2265 0.95 - Very strong signal - safe to use (examples: Laura, Michael)\nProbability 0.85 - 0.94 - High confidence - good for personalised greeting (examples: Claudia, Thomas)\nProbability 0.70 - 0.84 - Medium - fine for light personalisation, but expect a few errors (examples: Kim (female-leaning), Alex (male-leaning))\nProbability < 0.70 - Weak/unisex - treat as \"unknown\" (examples: Pat, Sam)",
"position": [
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"parameters": {
"rules": {
"values": [
{
"outputKey": "No",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
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"conditions": [
{
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"operator": {
"type": "number",
"operation": "lt"
},
"leftValue": "={{ $json.output.gender_probability }}",
"rightValue": 85
}
]
},
"renameOutput": true
},
{
"outputKey": "Yes",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
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"combinator": "and",
"conditions": [
{
"id": "471264b3-1008-4dae-b787-ddd88d72a8f6",
"operator": {
"type": "number",
"operation": "gte"
},
"leftValue": "={{ $json.output.gender_probability }}",
"rightValue": 85
}
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"typeVersion": 3.2
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{
"id": "584f04a1-39a4-4546-a89c-5c4bea31c492",
"name": "First name probability >= 85%",
"type": "n8n-nodes-base.filter",
"position": [
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"parameters": {
"options": {},
"conditions": {
"options": {
"version": 3,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
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{
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"operator": {
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"leftValue": "={{ $json.output.first_name_probability }}",
"rightValue": 85
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{
"id": "6d206b87-3a1c-459b-aadd-9d583ac48bad",
"name": "Gender probability >= 85% ?1",
"type": "n8n-nodes-base.switch",
"notes": "How the probability field works:\n\u2022 It ranges from 0 to 1 (or 0-100 %).\n\u2022 It reflects how often that name appeared with the returned gender in the dataset.\n\u2022 The higher the value, the more confident the service is.\n\nProbability \u2265 0.95 - Very strong signal - safe to use (examples: Laura, Michael)\nProbability 0.85 - 0.94 - High confidence - good for personalised greeting (examples: Claudia, Thomas)\nProbability 0.70 - 0.84 - Medium - fine for light personalisation, but expect a few errors (examples: Kim (female-leaning), Alex (male-leaning))\nProbability < 0.70 - Weak/unisex - treat as \"unknown\" (examples: Pat, Sam)",
"position": [
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"parameters": {
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{
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"conditions": {
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"caseSensitive": true,
"typeValidation": "strict"
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"operator": {
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"leftValue": "={{ $json.output.gender_probability }}",
"rightValue": 85
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"renameOutput": true
},
{
"outputKey": "Yes",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "471264b3-1008-4dae-b787-ddd88d72a8f6",
"operator": {
"type": "number",
"operation": "gte"
},
"leftValue": "={{ $json.output.gender_probability }}",
"rightValue": 85
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"notesInFlow": true,
"typeVersion": 3.2
},
{
"id": "0bb0edac-8625-43b1-ac06-0022c5655db8",
"name": "Route via gender",
"type": "n8n-nodes-base.switch",
"position": [
2048,
144
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "Neutral",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "51346472-68bb-437e-b9dd-76530f946f4d",
"operator": {
"type": "string",
"operation": "notRegex"
},
"leftValue": "={{ $json.output.gender }}",
"rightValue": "male"
}
]
},
"renameOutput": true
},
{
"outputKey": "Female",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "ed64f4e2-bfa3-4a55-b190-58f654465198",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.output.gender }}",
"rightValue": "female"
}
]
},
"renameOutput": true
},
{
"outputKey": "Male",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "471264b3-1008-4dae-b787-ddd88d72a8f6",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.output.gender }}",
"rightValue": "male"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "17c778b7-0072-489e-96d7-e9be7c95ab24",
"name": "Route via gender1",
"type": "n8n-nodes-base.switch",
"position": [
2048,
800
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "Neutral",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "51346472-68bb-437e-b9dd-76530f946f4d",
"operator": {
"type": "string",
"operation": "notRegex"
},
"leftValue": "={{ $json.output.gender }}",
"rightValue": "male"
}
]
},
"renameOutput": true
},
{
"outputKey": "Female",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "ed64f4e2-bfa3-4a55-b190-58f654465198",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.output.gender }}",
"rightValue": "female"
}
]
},
"renameOutput": true
},
{
"outputKey": "Male",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "471264b3-1008-4dae-b787-ddd88d72a8f6",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.output.gender }}",
"rightValue": "male"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "5860379c-e51e-4a96-b547-011a2897420a",
"name": "3. Filter results and update contacts with greeting",
"type": "n8n-nodes-base.stickyNote",
"position": [
1440,
-96
],
"parameters": {
"color": 7,
"width": 1144,
"height": 636,
"content": "## 3. Filter results and update contacts with greeting"
},
"typeVersion": 1
},
{
"id": "7b3a96d6-a6b3-4f1f-b31c-555afe3a0f99",
"name": "5. Filter results and update contacts with greeting and first name",
"type": "n8n-nodes-base.stickyNote",
"position": [
1440,
560
],
"parameters": {
"color": 7,
"width": 1144,
"height": 636,
"content": "## 5. Filter results and update contacts with greeting and first name"
},
"typeVersion": 1
},
{
"id": "44dd68bd-7c74-4691-99b8-0bbdc23da3da",
"name": "First name present",
"type": "n8n-nodes-base.filter",
"position": [
848,
144
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 3,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "a84bed0c-e1c3-46d9-a022-c2001216edc8",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.fieldFirstName }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.3
},
{
"id": "8ae4f5c8-fb00-4a29-92da-b4f18fc87187",
"name": "First name absent, email present",
"type": "n8n-nodes-base.filter",
"position": [
864,
800
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 3,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "a84bed0c-e1c3-46d9-a022-c2001216edc8",
"operator": {
"type": "string",
"operation": "empty",
"singleValue": true
},
"leftValue": "={{ $json.fieldFirstName }}",
"rightValue": ""
},
{
"id": "1bc8c842-8449-499e-a10d-9b7ef743539e",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.email }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.3
}
],
"active": false,
"settings": {
"binaryMode": "separate",
"executionOrder": "v1"
},
"versionId": "c081765d-6915-4bf9-a5a6-3733cbe0aaf1",
"nodeGroups": [],
"connections": {
"Route via gender": {
"main": [
[
{
"node": "Update Contact in KlickTipp2",
"type": "main",
"index": 0
}
],
[
{
"node": "Update Contact in KlickTipp1",
"type": "main",
"index": 0
}
],
[
{
"node": "Update Contact in KlickTipp",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Get First Name and Gender via AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Route via gender1": {
"main": [
[
{
"node": "Update Contact in KlickTipp5",
"type": "main",
"index": 0
}
],
[
{
"node": "Update Contact in KlickTipp4",
"type": "main",
"index": 0
}
],
[
{
"node": "Update Contact in KlickTipp3",
"type": "main",
"index": 0
}
]
]
},
"First name present": {
"main": [
[
{
"node": "Get Gender via AI Agent",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "Get Gender via AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Get Gender via AI Agent": {
"main": [
[
{
"node": "Gender probability >= 85% ?",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Get First Name and Gender via AI Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Structured Output Parser1": {
"ai_outputParser": [
[
{
"node": "Get Gender via AI Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Contact Tagged in KlickTipp": {
"main": [
[
{
"node": "First name present",
"type": "main",
"index": 0
},
{
"node": "First name absent, email present",
"type": "main",
"index": 0
}
]
]
},
"Gender probability >= 85% ?": {
"main": [
[
{
"node": "Update Contact in KlickTipp2",
"type": "main",
"index": 0
}
],
[
{
"node": "Route via gender",
"type": "main",
"index": 0
}
]
]
},
"Gender probability >= 85% ?1": {
"main": [
[
{
"node": "Update Contact in KlickTipp5",
"type": "main",
"index": 0
}
],
[
{
"node": "Route via gender1",
"type": "main",
"index": 0
}
]
]
},
"First name probability >= 85%": {
"main": [
[
{
"node": "Gender probability >= 85% ?1",
"type": "main",
"index": 0
}
]
]
},
"First name absent, email present": {
"main": [
[
{
"node": "Get First Name and Gender via AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Get First Name and Gender via AI Agent": {
"main": [
[
{
"node": "First name probability >= 85%",
"type": "main",
"index": 0
}
]
]
}
}
}
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About this workflow
This workflow triggers when a contact is tagged in KlickTipp, uses OpenAI to estimate gender from the contact’s first name or to extract a name from the email address, and then writes an HTML greeting (Lieber/Liebe/Hallo) back to a KlickTipp custom field. Triggers when a contact…
Source: https://n8n.io/workflows/16573/ — original creator credit. Request a take-down →
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