Lead generation platform that gives you real-time info about companies and people that visit your website. Turning anonymous web traffic into actionable data.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
The LeadBoxer API lets you track and score leads using web and email behavior data. With this API on Pipedream, you can automate the collection of lead insights, trigger actions based on lead scores or activities, and integrate this data into your CRM or other business tools. By tapping into webhooks and Pipedream's serverless platform, you can create workflows that react in real-time to lead interactions, enrich lead profiles, or sync information across multiple services.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
leadboxer: {
type: "app",
app: "leadboxer",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://kibana.leadboxer.com/api/views/c_view_leads`,
headers: {
"Content-Type": `application/json`,
},
params: {
apiKey: `${this.leadboxer.$auth.api_key}`,
site: `${this.leadboxer.$auth.dataset_id}`,
},
})
},
})
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.
This includes installing PyPI packages, within your code without having to manage a requirements.txt
file or running pip
.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}