How to connect Harvest and LinkedIn Data Scraper
Create a New Scenario to Connect Harvest and LinkedIn Data Scraper
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Harvest, triggered by another scenario, or executed manually (for testing purposes). In most cases, Harvest or LinkedIn Data Scraper will be your first step. To do this, click "Choose an app," find Harvest or LinkedIn Data Scraper, and select the appropriate trigger to start the scenario.

Add the Harvest Node
Select the Harvest node from the app selection panel on the right.


Harvest

Add the LinkedIn Data Scraper Node
Next, click the plus (+) icon on the Harvest node, select LinkedIn Data Scraper from the list of available apps, and choose the action you need from the list of nodes within LinkedIn Data Scraper.


Harvest
⚙
LinkedIn Data Scraper

Authenticate LinkedIn Data Scraper
Now, click the LinkedIn Data Scraper node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your LinkedIn Data Scraper settings. Authentication allows you to use LinkedIn Data Scraper through Latenode.
Configure the Harvest and LinkedIn Data Scraper Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Harvest and LinkedIn Data Scraper Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

JavaScript
⚙
AI Anthropic Claude 3
⚙
LinkedIn Data Scraper
Trigger on Webhook
⚙

Harvest
⚙
⚙
Iterator
⚙
Webhook response

Save and Activate the Scenario
After configuring Harvest, LinkedIn Data Scraper, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Harvest and LinkedIn Data Scraper integration works as expected. Depending on your setup, data should flow between Harvest and LinkedIn Data Scraper (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Harvest and LinkedIn Data Scraper
LinkedIn Data Scraper + Harvest + Slack: When someone views your LinkedIn profile, scrape their profile data, start a timer in Harvest to track time spent on lead follow-up, and send a notification to the sales team in Slack to follow up.
LinkedIn Data Scraper + Harvest + Google Sheets: Scrape LinkedIn profiles for potential clients. For each profile scraped, start a timer in Harvest to track prospecting time, and then add the scraped data to a Google Sheet for record-keeping and analysis.
Harvest and LinkedIn Data Scraper integration alternatives

About Harvest
Automate time tracking with Harvest in Latenode. Sync time entries to accounting, payroll, or project management. Create flows that auto-generate invoices or trigger alerts for budget overruns. Latenode provides the flexibility to connect Harvest data to other apps and add custom logic, avoiding manual updates and delays.
Related categories
About LinkedIn Data Scraper
Need LinkedIn data for leads or market insights? Automate scraping profiles and company info inside Latenode workflows. Extract data, enrich it with AI, then push it to your CRM or database. Latenode's visual editor and affordable pricing make data-driven outreach scalable and cost-effective.
Similar apps
Related categories
See how Latenode works
FAQ Harvest and LinkedIn Data Scraper
How can I connect my Harvest account to LinkedIn Data Scraper using Latenode?
To connect your Harvest account to LinkedIn Data Scraper on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Harvest and click on "Connect".
- Authenticate your Harvest and LinkedIn Data Scraper accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate time tracking based on LinkedIn lead status?
Yes, you can! Latenode allows you to trigger time entries in Harvest when a lead's status changes in LinkedIn Data Scraper. Leverage no-code blocks and custom JavaScript for granular control.
What types of tasks can I perform by integrating Harvest with LinkedIn Data Scraper?
Integrating Harvest with LinkedIn Data Scraper allows you to perform various tasks, including:
- Automatically create Harvest projects from new LinkedIn Data Scraper leads.
- Log time against specific LinkedIn Data Scraper contact outreach campaigns.
- Update Harvest client details when LinkedIn Data Scraper profiles are updated.
- Generate invoices in Harvest based on time spent on LinkedIn Data Scraper tasks.
- Send Harvest reports to team members based on LinkedIn Data Scraper activity.
Can I use JavaScript with my Harvest automations in Latenode?
Yes! Latenode allows you to incorporate JavaScript at any step, giving you ultimate control over data transformations and custom logic within your Harvest workflows.
Are there any limitations to the Harvest and LinkedIn Data Scraper integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by Harvest and LinkedIn Data Scraper may affect performance.
- Historical data migration between the two apps may require manual configuration.
- Complex data transformations may require JavaScript knowledge for optimal results.