How Marketing Agencies Can Use Technology Detection to Win More Clients

# marketing# python# api# business
How Marketing Agencies Can Use Technology Detection to Win More ClientsDAPDEV

Most agencies walk into pitch meetings with generic proposals. Here's how to walk in knowing exactly...

Most agencies walk into pitch meetings with generic proposals. Here's how to walk in knowing exactly what a prospect is running — and exactly what they need.

The Problem

You're pitching a new client. You know their industry, you've looked at their website, maybe you've read their blog. But do you know:

  • What CMS they're using? (WordPress with 30 plugins? Webflow? Custom?)
  • Do they have analytics set up? (Google Analytics? Nothing?)
  • Are they using a CDN? (Cloudflare? None — meaning their site is probably slow)
  • What marketing tools are already installed? (HubSpot? Mailchimp? Nothing?)

Knowing this before the call completely changes the conversation.

Technology Detection as a Sales Weapon

I built a workflow using the Technology Detection API that scans prospect websites before every pitch. It detects 141+ technologies across 15 categories.

Here's a Python script that generates a pre-call brief:

import requests
import json

RAPIDAPI_KEY = "YOUR_RAPIDAPI_KEY"

def scan_prospect(url):
    resp = requests.get(
        "https://technology-detection-api.p.rapidapi.com/detect",
        params={"url": url},
        headers={
            "x-rapidapi-host": "technology-detection-api.p.rapidapi.com",
            "x-rapidapi-key": RAPIDAPI_KEY,
        },
    )
    resp.raise_for_status()
    data = resp.json()
    technologies = data.get("technologies", [])

    # Organize by category
    categories = {}
    for tech in technologies:
        cat = tech.get("category", "Other")
        name = tech.get("name") or tech.get("technology", "Unknown")
        if cat not in categories:
            categories[cat] = []
        categories[cat].append(name)

    print(f"\n{'='*50}")
    print(f"  PRE-CALL BRIEF: {url}")
    print(f"{'='*50}\n")

    for cat, techs in sorted(categories.items()):
        print(f"  {cat}: {', '.join(techs)}")

    # Flag opportunities
    tech_names = [t.get("name", "").lower() for t in technologies]
    print(f"\n  --- TALKING POINTS ---")

    if not any("analytics" in t.get("category", "").lower() for t in technologies):
        print("  > No analytics detected — pitch analytics setup")

    if not any("cdn" in t.get("category", "").lower() for t in technologies):
        print("  > No CDN detected — pitch performance optimization")

    if "wordpress" in tech_names:
        print("  > WordPress detected — pitch maintenance/security/migration")

    if not any(t in tech_names for t in ["hubspot", "mailchimp", "klaviyo", "sendgrid"]):
        print("  > No email marketing tool detected — pitch email automation")

    return data

# Scan before your next pitch
scan_prospect("https://prospect-website.com")
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Competitive Benchmarking

Even more powerful: scan the top 10 competitors in your client's space.

def competitive_benchmark(urls):
    all_techs = {}
    for url in urls:
        try:
            resp = requests.get(
                "https://technology-detection-api.p.rapidapi.com/detect",
                params={"url": url},
                headers={
                    "x-rapidapi-host": "technology-detection-api.p.rapidapi.com",
                    "x-rapidapi-key": RAPIDAPI_KEY,
                },
            )
            resp.raise_for_status()
            techs = resp.json().get("technologies", [])
            for t in techs:
                name = t.get("name") or t.get("technology", "Unknown")
                if name not in all_techs:
                    all_techs[name] = 0
                all_techs[name] += 1
        except Exception as e:
            print(f"Error scanning {url}: {e}")

    print(f"\n  TECHNOLOGY ADOPTION ACROSS {len(urls)} COMPETITORS")
    print(f"  {'='*45}")
    for tech, count in sorted(all_techs.items(), key=lambda x: x[1], reverse=True):
        pct = count / len(urls) * 100
        bar = "#" * int(pct / 5)
        print(f"  {tech:.<30} {count}/{len(urls)} ({pct:.0f}%) {bar}")

competitors = [
    "https://competitor1.com",
    "https://competitor2.com",
    "https://competitor3.com",
]
competitive_benchmark(competitors)
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This tells you things like: "7 out of 10 competitors use Cloudflare, but your client doesn't" or "Everyone has Google Analytics except your client." These become concrete, data-backed recommendations in your proposal.

What This Does for Your Close Rate

When you walk into a call and say:

"I noticed you're running WordPress 5.x with no CDN. Your page load time is probably 4-5 seconds. Your top 3 competitors are all on Cloudflare with sub-2-second loads. We can fix that in a week."

...that's a completely different conversation than "We do web optimization."

Specificity wins deals.

Getting Started

The Technology Detection API has a free tier (50 requests/month) and paid plans starting at $9/month for 2,000 scans.

For an agency scanning 20-30 prospects per month plus competitor analysis, the free tier might be enough to start. The $9 plan covers most small agencies easily.

Python wrapper on GitHub: techdetect-python

How do you research prospects before pitching? I'd love to hear what other tools or workflows agencies are using for competitive intelligence.