In the current search ecosystem, Google has pivoted toward "Short Video" integration. For SEO professionals and brand managers, tracking how Instagram Reels appear in Google Search results is the new frontier of visibility.
While traditional rank tracking focuses on blue links, tracking the "Short Videos" shelf requires a specialized approach. In this guide, Actowiz Solutions breaks down how to build a resilient Python-based scraper using Playwright to monitor this high-value SERP real estate.
Google’s algorithm now prioritizes multi-modal content. When a user searches for "Best desert safari Dubai" or "Easy pasta recipes," Google often inserts a horizontal carousel of vertical videos.
Scraping these results is more complex than standard web scraping because:
For this implementation, we utilize Python with the Playwright library. Unlike Selenium, Playwright is faster, more reliable for modern SPAs (Single Page Applications), and offers better "out-of-the-box" bypasses for common bot detection patterns.
Key Advantages for Actowiz Clients:
First, ensure your environment is configured with the necessary drivers.
Bash
pip install playwright
playwright install chromium
To ensure high success rates, we use a Persistent Context. This stores session data, making our scraper appear as a legitimate, returning user.
Python
import json
import time
import random
from playwright.sync_api import sync_playwright
def scrape_reel_rankings(keyword):
with sync_playwright() as p:
# Launching a persistent browser to mimic human behavior
browser_context = p.chromium.launch_persistent_context(
user_data_dir="./actowiz_session",
headless=False, # Set to True for scale
args=["--disable-blink-features=AutomationControlled"]
)
page = browser_context.new_page()
page.goto(f"https://www.google.com/search?q={keyword.replace(' ', '+')}")
# Human-like interaction: Random scrolling to trigger lazy loading
page.mouse.wheel(0, 800)
time.sleep(random.uniform(2, 4))
return parse_video_shelf(page)
Google uses specific ARIA roles to categorize the video shelf. Instead of relying on brittle class names like .v78xqz, we target the accessibility tree.
Python
def parse_video_shelf(page):
video_data = []
# Locate the container for Short Videos
# We use 'region' or 'main' as anchors
containers = page.get_by_role("link").all()
for item in containers:
href = item.get_attribute("href")
# Filter specifically for Instagram Reels
if href and "instagram.com/reels" in href:
# Metadata is usually stored in the aria-label
label = item.get_attribute("aria-label")
# Actowiz Logic: Clean the label to extract Title and Creator
# Expected format: "Video Title by @Username"
try:
parts = label.split(" by ")
title = parts[0]
creator = parts[1].split(" ")[0]
except (AttributeError, IndexError):
title, creator = "N/A", "N/A"
video_data.append({
"source": "Instagram",
"title": title,
"creator": creator,
"url": href
})
return video_data
While the script above works for a single query, scaling to 100,000 keywords requires a more sophisticated infrastructure—which is where Actowiz Solutions provides the competitive edge.
Google will quickly block a single IP. Our infrastructure rotates through a pool of 10M+ Residential Proxies, ensuring each request originates from a unique, local ISP.
When Google presents a "Human Verification" challenge, Actowiz utilizes machine learning-based solvers that navigate these hurdles without interrupting the data flow.
Instagram Reel rankings vary by city. We can simulate searches from specific coordinates (e.g., Downtown Dubai vs. Marina) to provide hyper-local insights.
A typical data delivery from our platform looks like this:
| Ranking Position | Video Title | Creator Handle | Platform | Engagement Hint |
|---|---|---|---|---|
| 1 | How to Style Linen in 2026 | @fashion_uae | High | |
| 2 | Top 5 Cafes in Jumeirah | @dubai_eats | Rising | |
| 3 | Travel Vlog: Abu Dhabi | @globetrotter | High |
Maintaining an in-house scraper for Google is a constant battle against algorithm updates. Every time Google changes its UI, your code breaks.
Actowiz Solutions offers:
You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!By leveraging Actowiz Solutions, your business stays ahead of the competition, armed with actionable insights from every marketplace.
Our web scraping expertise is relied on by 3,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.
Watch how businesses like yours are using Actowiz data to drive growth.
From Zomato to Expedia — see why global leaders trust us with their data.
Backed by automation, data volume, and enterprise-grade scale — we help businesses from startups to Fortune 500s extract competitive insights across the USA, UK, UAE, and beyond.
We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.
How IHG Hotels & Resorts data scraping enables real-time rate tracking, improves availability monitoring, and boosts revenue decisions.
How a top-10 UK grocery retailer used Actowiz grocery price scraping to achieve 300% promotional ROI and reduce competitive response time from 5 days to same-day.

Track UK Grocery Products Daily Using Automated Data Scraping across Morrisons, Asda, Tesco, Sainsbury’s, Iceland, Co-op, Waitrose, and Ocado for insights.
Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.