Lead Enrichment

This example demonstrates how to take a list of raw lead notes and enrich them with structured data like industry, company size, and recommended follow-up actions.

The Scenario

You have a list of potential leads with unstructured notes. You want to turn this:

“Signed up after webinar, growth-stage SaaS, 80 employees. Wants a live demo next week.”

Into this:

{
  "company_name": "Acme Analytics",
  "industry": "Software",
  "company_size": "Mid-market",
  "recommended_follow_up": "Call"
}

Implementation

1. Define the Schema

First, we define the structure of the data we want to extract.

import { z } from 'zod';

const LeadInsights = z.object({
  company_name: z.string(),
  industry: z.string(),
  company_size: z.enum(['SMB', 'Mid-market', 'Enterprise']),
  recommended_follow_up: z.enum(['Call', 'Email', 'Event']),
});

2. Create the Function

We use createArrayFn because we want to process multiple leads at once.

import { Nua } from 'nuabase';

const nua = new Nua({ apiKey: 'YOUR_API_KEY' });

const enrichLeads = nua.createArrayFn({
  prompt: `Summarize each inbound lead by extracting company_name, industry, 
           company_size bucket (SMB, Mid-market, Enterprise), and the 
           recommended_follow_up channel (Call, Email, or Event) based on their notes.`,
  output: {
    name: 'leadInsights',
    schema: LeadInsights,
  },
});

3. Prepare Data

Each row needs a unique identifier (primary key).

const rows = [
  {
    leadId: 'lead-101',
    name: 'Acme Analytics',
    notes: 'Signed up after webinar, growth-stage SaaS, 80 employees. Wants a live demo next week.',
  },
  {
    leadId: 'lead-102',
    name: 'Bright Logistics',
    notes: 'Regional freight operator asking for pricing via email. 12 depots across the Midwest.',
  },
  {
    leadId: 'lead-103',
    name: 'Nimbus Retail',
    notes: 'Enterprise retailer. Mentioned they will send the procurement team to our booth at NRF.',
  },
];

4. Execute and Handle Results

// 'leadId' is the primary key field
const response = await enrichLeads(rows, 'leadId');

if (response.isError) {
  console.error(response.error);
  return;
}

// Iterate through the enriched results
response.data.forEach(({ leadId, leadInsights }) => {
  console.log(`[${leadId}] ${leadInsights.company_name}: ${leadInsights.recommended_follow_up}`);
});

/* Output:
[lead-101] Acme Analytics: Call
[lead-102] Bright Logistics: Email
[lead-103] Nimbus Retail: Event
*/

Why this is powerful

Structured Data: You didn’t have to write regex or complex parsing logic.
Type Safety: The leadInsights object is fully typed in your IDE.
Caching: If you run this again with the same leads, Nuabase returns the cached results instantly for free.

Getting Started

Workflows

API

Core Concepts

Examples

Console

The Scenario

Implementation

1. Define the Schema

2. Create the Function

3. Prepare Data

4. Execute and Handle Results

Why this is powerful

​The Scenario

​Implementation

​1. Define the Schema

​2. Create the Function

​3. Prepare Data

​4. Execute and Handle Results

​Why this is powerful

The Scenario

Implementation

1. Define the Schema

2. Create the Function

3. Prepare Data

4. Execute and Handle Results

Why this is powerful