Skip to content
FlowHubFluxonLab
C
PostgreSQLfree

Enrich up to 1500 emails per hour with Dropcontact batch requests

by victor de costeradapted from n8n official workflow galleryUpdated Aug 2026
RequiresCCodeHTTP RequestHTTP RequestPostgresPostgresSlack
Share Post Share
AgAggregatePROFILES QUERYHRBULK DROPCONTACT REQUESTSBULK DROPCONTAC…SILoop Over Items2SOSplit OutPostgresHRBULK DROPCONTACT DOWNLOADBULK DROPCONTAC…WaWait2CoDATA TRANSFORMATIONDATA TRANSFORMA…SlackScSchedule Trigger1234567891011
1/5
STEPS · 11
Runs on a schedule

The template allows to make Dropcontact batch requests up to 250 requests every 10 minutes (1500/hour). Valuable if high volume email enrichment is expected. Dropcontact will look for email & basic email qualification if first_name, last_name, company_name is provided. +++++++++++++++++++++++++++++++++++++++++ Step 1: Node "Profiles Query" Connect your own source (Airtable, Google Sheets, Supabase,...) the template is using Postgres by default. Note I: Be careful your source is only returning a maximum of 250 items. Note II: The next node uses the next variables, make sure you can map these from your source file: first_name last_name website (company_name would work too) full_name (see note) Note III: This template is using the Dropcontact Batch API, which works in a POST & GET setup. Not a GET request only to retrieve data, as Dropcontact needs to process the batch data load properly. +++++++++++++++++++++++++++++++++++++++++ Step 2: Node "Data Transformation" Will transform the input variables in the proper json format. This json format is expected from the Dropcontact API to make a batch request.

Tags

n8nreference-onlypostgresslack
Connects
CCodeWHTTP RequestpostgresPostgresSlack
CategoryPostgreSQL
Triggermanual
Complexitymedium
Nodes11
AddedMay 21, 2024

Related workflows

See all PostgreSQL
CWpostgres
free

🤖 Advanced Slackbot with n8n

Use case Slackbots are super powerful. At n8n, we have been using them to get a lot done.. But it can become hard to manage and maintain many different operations that a workflow can do. This is the base workflow we use for our most powerful internal Slackbots. They handle a lot from running e2e tests for Github branch to deleting a user. By splitting the workflow into many subworkflows, we are able to handle each command seperately, making it easier to debug as well as support new usecases. In this template, you can find eveything to setup your own Slackbot (and I made it simple, there's only one node to configure 😉). After that, you need to build your commands directly. This bot can create a new thread on an alerts channel and respond there. Or reply directly to the user. It responds for help request to return a help page. It automatically handles unknown commands. It also supports flags and environment variables. For example /cloudbot-test info mutasem --full-info -e env=prod would give you the following info, when calling subworkflow. How to setup Add Slack command and point it up to the webhook. For example. Add the following to the Set config node alerts_channel with alerts

by Mutasem
CWpostgresyoutube
free

Youtube Outlier Detector (Find trending content based on your competitors)

Video explanation This n8n workflow helps you identify trending videos within your niche by detecting outlier videos that significantly outperform a channel's average views. It automates the process of monitoring competitor channels, saving time and streamlining content research. Included in the Workflow Automated Competitor Video Tracking Monitors videos from specified competitor channels, fetching data directly from the YouTube API. Outlier Detection Based on Channel Averages Compares each video’s performance against the channel’s historical average to identify significant spikes in viewership. Historical Video Data Management Stores video statistics in a PostgreSQL database, allowing the workflow to only fetch new videos and optimize API usage. Short Video Filtering Automatically removes short videos based on duration thresholds. Flexible Video Retrieval Fetches up to 3 months of historical data on the first run and only new videos on subsequent runs. PostgreSQL Database Integration Includes SQL queries for database setup, video insertion, and performance analysis. Configurable Outlier Threshold Focuses on videos published within the last two weeks with view counts at least twic

by Leonardo Grigorio
postgres
free

Watchdog: Update All Workflows With Default Error Workflow

Do you consistently forget to set a Default Error Workflow when creating new workflows? Then this helper workflow is for you! When activated, this helper workflow will: Scan ALL other workflows every 4 hours Make sure ALL workflows have a default error workflow set (based on what Workflow ID you provide) This helper will SKIP OVER any workflows that have the default_error:false tag set (make sure your default error workflow has the default_error:false tag set, so that you don't end up with recursive loops during errors) Setup Nodes: Once imported, edit the Set Vars node with your default_error_workflow_id value. If you want to change the default_error:false tag to some other tag name, you can do so here as well. You need to update the Set Default Error Workflow node with your PostgreSQL credentials to access the n8n database.

by Darien Kindlund