Intercom Cost Tuning

Overview

Reduce Intercom API costs through smart caching, search optimization, webhook-driven architecture, and usage monitoring. Intercom pricing is primarily seat-based and feature-based, but API efficiency reduces infrastructure costs and avoids rate limits.

Intercom Pricing Model

Key insight: The API itself is free to use, but hitting rate limits (10K req/min) forces you to build queuing infrastructure. Reducing requests saves engineering time and infrastructure costs.

Instructions

Step 1: Audit Current API Usage

// Instrument all API calls to track usage patterns
class IntercomUsageTracker {
  private calls = new Map<string, { count: number; totalMs: number }>();

  track(endpoint: string, durationMs: number): void {
    const existing = this.calls.get(endpoint) || { count: 0, totalMs: 0 };
    existing.count++;
    existing.totalMs += durationMs;
    this.calls.set(endpoint, existing);
  }

  report(): void {
    console.log("\n=== Intercom API Usage Report ===");
    const sorted = [...this.calls.entries()].sort((a, b) => b[1].count - a[1].count);

    for (const [endpoint, stats] of sorted) {
      console.log(
        `${endpoint}: ${stats.count} calls, avg ${(stats.totalMs / stats.count).toFixed(0)}ms`
      );
    }

    const total = sorted.reduce((sum, [, s]) => sum + s.count, 0);
    console.log(`\nTotal: ${total} API calls`);
    console.log(`Estimated rate: ${(total / 60).toFixed(0)} req/min (limit: 10,000)`);
  }
}

Step 2: Replace Polling with Webhooks

// BAD: Polling for new conversations every 30 seconds
// Cost: ~2,880 requests/day for ONE check
setInterval(async () => {
  const conversations = await client.conversations.list();
  // Check for new conversations...
}, 30000);

// GOOD: Webhook-driven (0 requests, instant notification)
app.post("/webhooks/intercom", (req, res) => {
  const notification = req.body;
  if (notification.topic === "conversation.user.created") {
    handleNewConversation(notification.data.item);
  }
  res.status(200).json({ received: true });
});

Step 3: Cache Contact Lookups

import { LRUCache } from "lru-cache";

const contactCache = new LRUCache<string, any>({
  max: 10000,
  ttl: 10 * 60 * 1000, // 10 min TTL
});

// Before: 1 API call per contact lookup
async function getContactName(contactId: string): Promise<string> {
  const contact = await client.contacts.find({ contactId });
  return contact.name;
}

// After: API call only on cache miss
async function getContactNameCached(contactId: string): Promise<string> {
  let name = contactCache.get(contactId) as string | undefined;
  if (!name) {
    const contact = await client.contacts.find({ contactId });
    name = contact.name;
    contactCache.set(contactId, name);
  }
  return name;
}

// Invalidate cache via webhooks
function onContactUpdated(contactId: string): void {
  contactCache.delete(contactId);
}

Step 4: Use Search Instead of List + Filter

// BAD: Fetch all contacts, filter client-side
// Cost: N pages * 1 request each
let startingAfter: string | undefined;
const matchingContacts = [];
do {
  const page = await client.contacts.list({ perPage: 50, startingAfter });
  matchingContacts.push(...page.data.filter(c => c.customAttributes?.plan === "pro"));
  startingAfter = page.pages?.next?.startingAfter;
} while (startingAfter);

// GOOD: Server-side search (1 request for up to 150 results)
const proUsers = await client.contacts.search({
  query: {
    operator: "AND",
    value: [
      { field: "role", operator: "=", value: "user" },
      { field: "custom_attributes.plan", operator: "=", value: "pro" },
    ],
  },
  pagination: { per_page: 150 },
});

Step 5: Batch Conversation Lookups

// BAD: N individual conversation lookups
for (const id of conversationIds) {
  const convo = await client.conversations.find({ conversationId: id });
  process(convo);
}

// GOOD: Search conversations with filter
const conversations = await client.conversations.search({
  query: {
    operator: "AND",
    value: [
      { field: "state", operator: "=", value: "open" },
      { field: "admin_assignee_id", operator: "=", value: adminId },
    ],
  },
  pagination: { per_page: 50 },
});

Step 6: Monitor Request Budget

class RequestBudgetMonitor {
  private requestsThisMinute = 0;
  private resetTime = Date.now() + 60000;

  async checkBudget(): Promise<void> {
    if (Date.now() > this.resetTime) {
      this.requestsThisMinute = 0;
      this.resetTime = Date.now() + 60000;
    }

    this.requestsThisMinute++;

    // Warn at 80% of limit
    if (this.requestsThisMinute > 8000) {
      console.warn(
        `[Intercom] High request rate: ${this.requestsThisMinute}/10000 per minute`
      );
    }

    // Hard stop at 95% to prevent 429s
    if (this.requestsThisMinute > 9500) {
      const waitMs = this.resetTime - Date.now();
      console.warn(`[Intercom] Throttling: waiting ${waitMs}ms`);
      await new Promise(r => setTimeout(r, waitMs));
    }
  }
}

Cost Reduction Checklist

• Replace polling loops with webhooks
• Cache contact and conversation lookups (5-10 min TTL)
• Use search instead of list + client-side filter
• Batch related lookups into single search queries
• Track API request volume per endpoint
• Set up alerts at 80% rate limit usage
• Remove unnecessary API calls in hot paths

Error Handling

Resources

• Intercom Pricing
• Rate Limiting
• Search Contacts

Next Steps

For architecture patterns, see intercom-reference-architecture.