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Michael
Michael

Posted on • Originally published at getmichaelai.com

Deconstructing a 45% Lead Conversion Win: How We Replaced Manual SQL Scripts with a Simple API

As engineers, we often get pulled into building and maintaining internal tools for sales and marketing. One of the most common—and often frustrating—is the lead routing and scoring system. It usually starts as a simple script, then morphs into a complex web of SQL queries, cron jobs, and brittle business logic that nobody wants to touch.

This was the exact situation at FinAnalytica, a B2B FinTech platform. Their manual process was slow, error-prone, and couldn't keep up with their growth. The result? A leaky sales funnel and frustrated engineers.

This case study breaks down how they swapped their legacy system for a single API endpoint and boosted their lead-to-opportunity conversion rate by 45% in one quarter. No marketing fluff, just the technical steps.

The Challenge: When if/else Logic Hits Its Limit

FinAnalytica's system was typical for a growing SaaS company. When a new lead signed up:

  1. A webhook fired, adding the lead to a staging database table.
  2. A nightly cron job ran a massive SQL script to enrich the data (using Clearbit) and score the lead based on a rigid, hard-coded ruleset.
  3. Another script assigned the lead to a sales rep based on territory and a simple round-robin logic.

The problems were obvious to the engineering team:

  • Lead Latency: Leads waited 12-24 hours for follow-up. In B2B SaaS, that's an eternity.
  • Inflexibility: Changing the scoring logic required a code change, PR review, and deployment. The marketing team couldn't iterate quickly.
  • Maintenance Overhead: The script would frequently break due to API changes or unexpected data, creating yet another ticket for the dev team.

The Solution: Real-Time AI Scoring with LeadSift AI

We decided to replace the entire Rube Goldberg machine with a single API call to our product, LeadSift AI. The goal was to qualify, score, and route leads in real-time, the moment they signed up.

Here’s the step-by-step implementation.

Step 1: Capturing Leads with a Serverless Function

First, they replaced their old webhook receiver with a simple serverless function (e.g., AWS Lambda or Vercel Function). This function's only job is to catch the payload from their signup form (hosted on Hubspot) and pass it to the LeadSift AI API.

Here's a simplified look at the Node.js/Express-style handler:

// Vercel Serverless Function: /api/handle-signup.js

export default async function handler(req, res) {
  if (req.method !== 'POST') {
    return res.status(405).json({ message: 'Method Not Allowed' });
  }

  const { email, companyName, companyDomain } = req.body;

  // Basic validation
  if (!email || !companyDomain) {
    return res.status(400).json({ message: 'Missing required lead data' });
  }

  try {
    // Forward the data to our AI scoring service
    const aiResponse = await scoreAndRouteLead({ email, companyName, companyDomain });

    // TODO: Use aiResponse to update CRM (see Step 3)

    res.status(200).json({ success: true, routing: aiResponse });
  } catch (error) {
    console.error('Error processing lead:', error);
    res.status(500).json({ message: 'Internal Server Error' });
  }
}
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This immediately cut the lead processing time from hours to seconds.

Step 2: Defining the 'Ideal Customer' as a JSON Object

Instead of hard-coded SQL CASE statements, FinAnalytica defined their Ideal Customer Profile (ICP) and routing rules in a simple JSON object. This object is sent along with the lead data to the LeadSift AI API.

The AI uses this profile to score the lead's fit and intent.

async function scoreAndRouteLead(leadData) {
  const LEADS_API_KEY = process.env.LEADSIFT_API_KEY;
  const endpoint = 'https://api.leadsiftai.com/v1/score';

  const payload = {
    lead: {
      email: leadData.email,
      domain: leadData.companyDomain
    },
    // This is where the magic happens
    icp: {
      min_company_size: 50,
      max_company_size: 1000,
      industries: ['Financial Services', 'Technology', 'Software'],
      technologies: ['Salesforce', 'AWS', 'Stripe'],
      negative_signals: ['competitor_domain', 'free_email_provider']
    },
    routing_rules: {
      strategy: 'round_robin',
      teams: {
        enterprise: ['alex@finanalytica.com', 'brie@finanalytica.com'],
        smb: ['casey@finanalytica.com', 'drew@finanalytica.com']
      }
    }
  };

  const response = await fetch(endpoint, {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'Authorization': `Bearer ${LEADS_API_KEY}`
    },
    body: JSON.stringify(payload)
  });

  if (!response.ok) {
    throw new Error(`API call failed with status: ${response.status}`);
  }

  return response.json();
}
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This decouples the business logic from the application code. Marketing can now tweak the ICP in a simple config file without needing an engineer.

Step 3: Pushing the AI-Powered Decision to the CRM

The LeadSift AI API returns a clean, actionable JSON response:

{
  "score": 92,
  "tier": "Enterprise",
  "reasoning": ["Matches industry: Financial Services", "Company size > 50", "Uses AWS"],
  "assigned_to": "alex@finanalytica.com",
  "status": "success"
}
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The final step was to take this response and use it to create/update a contact in their Salesforce CRM. The serverless function was updated to perform this final action.

// Inside the try block of our handler from Step 1...

const aiResponse = await scoreAndRouteLead({ email, companyName, companyDomain });

// Assuming a helper function to interact with Salesforce API
await updateSalesforce({ 
  email: email,
  ownerEmail: aiResponse.assigned_to,
  leadScore: aiResponse.score,
  leadTier: aiResponse.tier,
  aiNotes: aiResponse.reasoning.join(', ')
});

res.status(200).json({ success: true, routing: aiResponse });
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Now, a highly qualified lead is in the right sales rep's hands, with context on why they're a good fit, within 5 seconds of submitting a form.

The Results: A 45% Lift and Happier Devs

By replacing a brittle, high-maintenance internal system with a single API, FinAnalytica achieved:

  • A 45% Increase in Lead-to-Opportunity Conversion Rate: Faster, more accurate routing meant their sales team could engage the best leads instantly.
  • ~10 Hours/Month of Engineering Time Saved: No more debugging SQL scripts or managing cron jobs for lead routing.
  • Zero Lead Leakage: Every lead was processed and routed instantly and reliably.
  • Empowered Marketing Team: They could now refine their targeting strategy by modifying a JSON config, without filing a single JIRA ticket.

This project was a huge win, demonstrating how a well-designed API can not only drive significant business ROI but also eliminate technical debt and free up engineering resources for core product development.


Originally published at https://getmichaelai.com/blog/how-customer-industry-increased-their-lead-conversion-by-45-

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